v10.1.0

Rolling 20220104
2025-12-07 12:06:58 +03:00 · 2022-01-09 09:47:16 +01:00 · 2022-01-09 09:43:22 +01:00 · 2022-01-04 21:17:20 +01:00 · 2022-01-03 17:32:01 +01:00 · 2022-01-01 08:57:07 +01:00
452 changed files with 27447 additions and 10395 deletions
--- a/Changelog.md
+++ b/Changelog.md
@@ -2,6 +2,99 @@



+##### 8.5.0 - Multi Meter Support (2021-10-07)
+
+* Upgrade digital CNN to v13.1.0 (added new images)
+* bug fix: wlan password with space, double digit output
+
+##### 8.4.0 - Multi Meter Support (2021-09-25)
+
+* License change (remove MIT license, remark see below)
+
+* html: show hostname in title and main page
+
+* configuration: 
+
+  * moved setting `ExtendedResolution` to individual number settings
+  * New parameter `IgnoreLeadingNaN` (delete leading NaN's specifically)
+  * **ATTENTION**: update of the `config.ini` needed (open, adjust `ExtendedResolution`, save)
+
+* Bug fixing (html, images of recognized numbers)
+
+  
+
+### **ATTENTION: LICENSE CHANGE - removal of MIT License.** 
+
+- Currently no licence published - copyright belongs to author
+- If you are interested in a commercial usage or dedicated versions please contact the developer
+  - no limits to private usage
+
+
+
+##### 8.3.0 - Multi Meter Support (2021-09-12)
+
+* Upgrade digital CNN to v12.1.0 (added new images)
+* Dedicated NaN handling, internal refactoring (CNN-Handling)
+* HTML: confirmation after config.ini update
+* Bug fixing
+
+##### 8.2.0 - Multi Meter Support (2021-08-24)
+
+* Improve server responsiveness
+* Flow status and prevalue status in overview
+* Improved prevalue handling 
+
+##### 8.1.0 - Multi Meter Support (2021-08-12)
+
+* GPIO: using the general mqtt main topic for GPIO
+
+* Upgrade digital CNN to v12.0.0  (added new images)
+* Update tfmicro to new master (2021-08-07)
+* Bug fix: remove text in mqtt value, remove connect limit in wlan reconnet
+
+##### 8.0.5 - Multi Meter Support (2021-08-01)
+
+* NEW 8.0.5: bug fix: saving prevalue
+* NEW 8.0.4: bug fix: load config.ini after upgrade
+* NEW 8.0.3: bug fix: reboot during `config.ini` handling, html error
+* NEW 8.0.2: saving roundes prevalue, bug fix html server
+* NEW 8.0.1: bug fix: html handling of parameter `FixedExposure` and `ImageSize`
+* Dual / multi meter support (more than 1 number to be recognized)
+  This is implemented with the feature "number" on the ROI definition as well as selected options
+* MQTT: standardization of the naming - including new topics (`json`,  `freeMem `, `uptime`)c
+* Preparation for extended GPIO support (thanks to Zwerk2k) - not tested and fully functional yet
+* Bug fixing: html server, memory leak, MQTT connect, hostname, turn of flash LED
+
+<span style="color: red;">**ATTENTION: the configuration and prevalue files are modified automatically and will not be backward compatible!**</span> 
+
+##### 7.1.2 MQTT-Update - (2021-06-17)
+
+* NEW: 7.1.2: bug fix setting hostname, Flash-LED not off during reboot
+
+* NEW: 7.1.1: bug fix wlan password with "="  (again)
+
+* MQTT error message: changes "no error", send retain flag
+
+* Update wlan handling to esp-idf 4.1
+
+* Upgrade digital CNN to v8.7.0  (added new images)
+
+* Bug fix: MQTT, WLAN, LED-Controll, GPIO usage, fixed IP, calculation flow rate
+
+  
+
+##### 7.0.1 MQTT-Update - (2021-05-13)
+
+* NEW: 7.0.1: bug fix wlan password with "=" 
+
+* Upgrade digital CNN to v8.5.0  (added new images)
+
+* New MQTT topics: flow rate (units/minute), time stamp (last correct read readout)
+
+* Update MQTT/Error topic to " " in case no error (instead of empty string)
+
+* Portrait or landscape image orientation in rotated image (avoid cropping)
+
 ##### 6.7.2 Image Processing in Memory - (2021-05-01)

 * NEW 6.7.2: Updated html for setup modus - remove reboot on edit configuration)
--- a/FeatureRequest.md
+++ b/FeatureRequest.md
@@ -11,6 +11,71 @@

 ____

+#### #17 Direct InfluxDB connection
+
+* https://github.com/jomjol/AI-on-the-edge-device/issues/534
+* Direct interface to a InfluxDB data base
+* Integrate InfluxDB interface in firmware
+* Adapt html web page for configuration
+
+
+#### #16 Serial Communication
+
+* https://github.com/jomjol/AI-on-the-edge-device/issues/512
+* Send the readout value via RX/TX interface with a dedicated TAG
+* Make dedicated communication FlowModule
+* Modification of RX/TX communication
+* Configuration interfache
+
+
+#### #15 Calibration for FishEye image
+
+* https://github.com/jomjol/AI-on-the-edge-device/issues/507
+
+1.  The development of such a correction algorithm with the libraries, that are available for the ESP32 environment.
+2. New module for integration of the flow into the image processing flow.
+3. Extension of the configuration (config.ini) and html-pages
+4. Parameter adjustment and testing for every different fish-eye module
+5. Maintenance for further updates / modules, ...
+
+
+
+#### #14 Backup and restore option for configuration
+
+* https://github.com/jomjol/AI-on-the-edge-device/issues/459
+
+* Implement a zip file compression for store and restore
+
+* Update the html to handle it
+
+  
+
+#### #13 Manage non linear gauge without CNN re-training
+
+* https://github.com/jomjol/AI-on-the-edge-device/issues/443
+
+* Implement a look up table for non linear analog meters
+
+  
+
+#### #12 Less reboots due to memory leakage
+
+* Issue: #414 & #425  #430
+
+  
+
+#### #11 MQTT - configurable payload
+
+* https://github.com/jomjol/AI-on-the-edge-device/issues/344
+
+  
+
+#### #10 Improve and bug fix logging of images
+
+* https://github.com/jomjol/AI-on-the-edge-device/issues/307
+
+  
+
 #### #9 Basic auth for the UI

 * https://github.com/jomjol/AI-on-the-edge-device/issues/283
--- a/21
+++ b/21
@@ -1,21 +0,0 @@
-MIT License
-
-Copyright (c) 2020 jomjol
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
--- a/README.md
+++ b/README.md
@@ -6,6 +6,8 @@ This is an example of Artificial Intelligence (AI) calculations on a very cheap

 A 3d-printable housing can be found here: https://www.thingiverse.com/thing:4573481

+or here https://www.thingiverse.com/thing:5028229
+
 respectively ESP32-Cam housing only: https://www.thingiverse.com/thing:4571627

 <img src="https://raw.githubusercontent.com/jomjol/AI-on-the-edge-device/master/images/watermeter_all.jpg" width="200"><img src="https://raw.githubusercontent.com/jomjol/AI-on-the-edge-device/master/images/main.jpg" width="200"><img src="https://raw.githubusercontent.com/jomjol/AI-on-the-edge-device/master/images/size.png" width="200"> 
@@ -32,59 +34,84 @@ If you have any technical topics, you can file a issue in this repository.

 In other cases you can contact the developer via email: <img src="https://raw.githubusercontent.com/jomjol/AI-on-the-edge-device/master/images/mail.jpg" height="25"> 

-## Change log
+------
+## Coming next
+
+* Automated update of the neural network file (tflite) to make the learing of additional pictures much easier and automated (GitHub action)
+* New "hyprid" neural network for digital numbers --> allowing the detection of intermediate states ("ring between two numbers") as a subdigit
+

 ------
-
+## Change log
 ### Known Issues

 * slow response of web server during picture analysis
 * spontaneous reboots (mostly due to html access during image processing) - self recovery implemented

------
-
 **General remark:** Beside the `firmware.bin`, typically also the content of `/html` needs to be updated!

-
-
-##### 8.0.3 - Multi Meter Support (2021-07-25)
-
-* NEW 8.0.3: bug fix: reboot during `config.ini` handling, html error
-* NEW 8.0.2: saving roundes prevalue, bug fix html server
-* NEW 8.0.1: bug fix html handling of parameter `FixedExposure` and `ImageSize`
-* Dual / multi meter support (more than 1 number to be recognized)
-  This is implemented with the feature "number" on the ROI definition as well as selected options
-* MQTT: standardization of the naming - including new topics (`json`,  `freeMem `, `uptime`)c
-* Preparation for extended GPIO support (thanks to Zwerk2k) - not tested and fully functional yet
-* Bug fixing: html server, memory leak, MQTT connect, hostname, turn of flash LED
-
-<span style="color: red;">**ATTENTION: the configuration and prevalue files are modified automatically and will not be backward compatible!**</span> 
+------



-##### 7.1.2 MQTT-Update - (2021-06-17)
+##### 10.1.0 - Stability Increase (2022-01-09)

-* NEW: 7.1.2: bug fix setting hostname, Flash-LED not off during rebootNEW: 7.1.1: bug fix wlan password with "="  (again)
-* MQTT error message: changes "no error", send retain flag
-* Update wlan handling to esp-idf 4.1
-* Upgrade digital CNN to v8.7.0  (added new images)
-* Bug fix: MQTT, WLAN, LED-Controll, GPIO usage, fixed IP, calculation flow rate
+- Reduce ESP32 frequency to 160MHz
+
+- Update tflite (new source: https://github.com/espressif/tflite-micro-esp-examples)
+
+- Update analog neural network (ana-s3-q-20220105.tflite)
+
+- Update digital neural network (dig-s1-q-20220102.tflite)
+
+- Increased web-server buffers
+- bug fix: compiler compatibility
+
+##### 10.0.2 - Stability Increase (2022-01-01)
+
+- NEW v10.0.2: Corrected JSON error
+
+- Updated compiler toolchain to ESP-IDF 4.3
+
+- Removal of memory leak
+
+- Improved error handling during startup (check PSRAM and camera with remark in logfile)
+
+- MQTT: implemented raw value additionally, removal of regex contrain
+
+- Normalized Parameter ``MaxRateValue``  to "change per minute" 
+
+- HTML: improved input handling
+
+- Corrected error handling: in case of error the old value, rate, timestamp are not transmitted any more

  

-##### 7.0.1 MQTT-Update - (2021-05-13)
+##### 9.2.0 - External Illumination (2021-12-02)

-* NEW: 7.0.1: bug fix wlan password with "=" 
+- Direct JSON access: ``http://IP-ADRESS/json`` 
+- Error message in log file in case camera error during startup
+- Upgrade analog CNN to v9.1.0
+- Upgrade digital CNN to v13.3.0 (added new images)
+- html: support of different ports

-* Upgrade digital CNN to v8.5.0  (added new images)
+##### 9.1.1 - External Illumination (2021-11-16)
+
+- NEW 9.1.1 bug fix: LED implemenetation
+- External LEDs: change control mode (resolve bug with more than 2 LEDs)
+- Additional info into log file
+- Bug fix: decimal shift, html, log file
+
+##### 9.0.0 - External Illumination (2021-10-23)
+
+* Implementation of external illumination to adjust positioning, brightness and color of the illumination now individually
+  * Technical details can be found in the wiki: https://github.com/jomjol/AI-on-the-edge-device/wiki/External-LED
+  <img src="https://raw.githubusercontent.com/jomjol/ai-on-the-edge-device/master/images/intern_vs_external.jpg" width="500">
+* New housing published for external LEDs and small clearing: https://www.thingiverse.com/thing:5028229

-* New MQTT topics: flow rate (units/minute), time stamp (last correct read readout)

-* Update MQTT/Error topic to " " in case no error (instead of empty string)

-* Portrait or landscape image orientation in rotated image (avoid cropping)

-  


 ## Additional ideas
@@ -97,6 +124,10 @@ There are some ideas and feature request, which are not followed currently - mai

 ## History

+##### 8.5.0 - Multi Meter Support (2021-10-07)
+
+##### 7.1.2 MQTT-Update - (2021-06-17)
+
 ##### 6.7.2 Image Processing in Memory - (2021-05-01)

 ##### 5.0.0 Setup Modus - (2020-12-06)
@@ -119,8 +150,3 @@ There are some ideas and feature request, which are not followed currently - mai

 #### [Full Changelog](Changelog.md)

-
-
-## Solved topics
-
-* n.a.
--- a/code/.helper/copy-esp-idf.bat
+++ b/code/.helper/copy-esp-idf.bat
@@ -0,0 +1,3 @@
+copy "..\..\code\build\esp32cam-server-only.bin" "..\..\firmware\firmware.bin"
+copy "..\..\code\build\bootloader\bootloader.bin" "..\..\firmware\bootloader.bin"
+copy "..\..\code\build\partition_table\partition-table.bin" "..\..\firmware\partitions.bin"
--- a/code/components/jomjol_configfile/configFile.cpp
+++ b/code/components/jomjol_configfile/configFile.cpp
@@ -39,18 +39,27 @@ bool ConfigFile::GetNextParagraph(std::string& aktparamgraph, bool &disabled, bo
 bool ConfigFile::getNextLine(std::string *rt, bool &disabled, bool &eof)
 {
    eof = false;
-	char zw[1024];
+	char zw[1024] = "";
 	if (pFile == NULL)
 	{
 		*rt = "";
 		return false;
 	}
-	fgets(zw, 1024, pFile);
-	printf("%s", zw);
-	if ((strlen(zw) == 0) && feof(pFile))
+
+	if (fgets(zw, 1024, pFile))
+	{
+		printf("%s", zw);
+		if ((strlen(zw) == 0) && feof(pFile))
+		{
+			*rt = "";
+			eof = true;
+			return false;
+		}
+	}
+	else
 	{
 		*rt = "";
-        eof = true;
+		eof = true;
 		return false;
 	}
 	*rt = zw;
--- a/code/components/jomjol_controlGPIO/Color.cpp
+++ b/code/components/jomjol_controlGPIO/Color.cpp
@@ -0,0 +1,132 @@
+#include "Color.h"
+#include <algorithm>
+#include <cmath>
+#include <cassert>
+
+namespace {
+
+// Int -> fixed point
+int up( int x ) { return x * 255; }
+
+} // namespace
+
+int iRgbSqrt( int num ) {
+    // https://en.wikipedia.org/wiki/Methods_of_computing_square_roots#Binary_numeral_system_.28base_2.29
+    assert( "sqrt input should be non-negative" && num >= 0 );
+    assert( "sqrt input should no exceed 16 bits" && num <= 0xFFFF );
+    int res = 0;
+    int bit = 1 << 16;
+    while ( bit > num )
+        bit >>= 2;
+    while ( bit != 0 ) {
+        if ( num >= res + bit ) {
+            num -= res + bit;
+            res = ( res >> 1 ) + bit;
+        } else
+            res >>= 1;
+        bit >>= 2;
+    }
+    return res;
+}
+
+Rgb::Rgb( Hsv y ) {
+    // https://stackoverflow.com/questions/24152553/hsv-to-rgb-and-back-without-floating-point-math-in-python
+    // greyscale
+    if( y.s == 0 ) {
+        r = g = b = y.v;
+        return;
+    }
+
+    const int region = y.h / 43;
+    const int remainder = ( y.h - ( region * 43 ) ) * 6;
+
+    const int p = ( y.v * ( 255 - y.s ) ) >> 8;
+    const int q = ( y.v * ( 255 - ( ( y.s * remainder ) >> 8 ) ) ) >> 8;
+    const int t = ( y.v * ( 255 - ( ( y.s * (255 -remainder ) ) >> 8 ) ) ) >> 8;
+
+    switch( region ) {
+        case 0: r = y.v; g = t; b = p; break;
+        case 1: r = q; g = y.v; b = p; break;
+        case 2: r = p; g = y.v; b = t; break;
+        case 3: r = p; g = q; b = y.v; break;
+        case 4: r = t; g = p; b = y.v; break;
+        case 5: r = y.v; g = p; b = q; break;
+        default: __builtin_trap();
+    }
+
+    a = y.a;
+}
+
+Rgb& Rgb::operator=( Hsv hsv ) {
+    Rgb r{ hsv };
+    swap( r );
+    return *this;
+}
+
+Rgb Rgb::operator+( Rgb in ) const {
+    auto copy = *this;
+    copy += in;
+    return copy;
+}
+
+Rgb& Rgb::operator+=( Rgb in ) {
+    unsigned int red = r + in.r;
+    r = ( red < 255 ) ? red : 255;
+    unsigned int green = g + in.g;
+    g = ( green < 255 ) ? green : 255;
+    unsigned int blue = b + in.b;
+    b = ( blue < 255 ) ? blue : 255;
+    return *this;
+}
+
+Rgb& Rgb::blend( Rgb in ) {
+    unsigned int inAlpha = in.a * ( 255 - a );
+    unsigned int alpha = a + inAlpha;
+    r = iRgbSqrt( ( ( r * r * a ) + ( in.r * in.r * inAlpha ) ) / alpha );
+    g = iRgbSqrt( ( ( g * g * a ) + ( in.g * in.g * inAlpha ) ) / alpha );
+    b = iRgbSqrt( ( ( b * b * a ) + ( in.b * in.b * inAlpha ) ) / alpha );
+    a = alpha;
+    return *this;
+}
+
+uint8_t IRAM_ATTR Rgb::getGrb( int idx ) {
+    switch ( idx ) {
+        case 0: return g;
+        case 1: return r;
+        case 2: return b;
+    }
+    __builtin_unreachable();
+}
+
+Hsv::Hsv( Rgb r ) {
+    int min = std::min( r.r, std::min( r.g, r.b ) );
+    int max = std::max( r.r, std::max( r.g, r.b ) );
+    int chroma = max - min;
+
+    v = max;
+    if ( chroma == 0 ) {
+        h = s = 0;
+        return;
+    }
+
+    s = up( chroma ) / max;
+    int hh;
+    if ( max == r.r )
+        hh = ( up( int( r.g ) - int( r.b ) ) ) / chroma / 6;
+    else if ( max == r.g )
+        hh = 255 / 3 + ( up( int( r.b ) - int( r.r ) ) ) / chroma / 6;
+    else
+        hh = 2 * 255 / 3 + ( up( int( r.r ) - int( r.g ) ) ) / chroma / 6;
+
+    if ( hh < 0 )
+        hh += 255;
+    h = hh;
+
+    a = r.a;
+}
+
+Hsv& Hsv::operator=( Rgb rgb ) {
+    Hsv h{ rgb };
+    swap( h );
+    return *this;
+}
--- a/code/components/jomjol_controlGPIO/Color.h
+++ b/code/components/jomjol_controlGPIO/Color.h
@@ -0,0 +1,69 @@
+#pragma once
+
+#include <cstdint>
+#include "esp_attr.h"
+union Hsv;
+
+union Rgb {
+    struct __attribute__ ((packed)) {
+        uint8_t r, g, b, a;
+    };
+    uint32_t value;
+
+    Rgb( uint8_t r = 0, uint8_t g = 0, uint8_t b = 0, uint8_t a = 255 ) : r( r ), g( g ), b( b ), a( a ) {}
+    Rgb( Hsv c );
+    Rgb& operator=( Rgb rgb ) { swap( rgb ); return *this; }
+    Rgb& operator=( Hsv hsv );
+    Rgb operator+( Rgb in ) const;
+    Rgb& operator+=( Rgb in );
+    bool operator==( Rgb in ) const { return in.value == value; }
+    Rgb& blend( Rgb in );
+    void swap( Rgb& o ) {  value = o.value; }
+    void linearize() {
+        r = channelGamma(r);
+        g = channelGamma(g);
+        b = channelGamma(b);
+    }
+
+    uint8_t IRAM_ATTR getGrb( int idx );
+
+    void stretchChannels( uint8_t maxR, uint8_t maxG, uint8_t maxB ) {
+        r = stretch( r, maxR );
+        g = stretch( g, maxG );
+        b = stretch( b, maxB );
+    }
+
+    void stretchChannelsEvenly( uint8_t max ) {
+        stretchChannels( max, max, max );
+    }
+
+private:
+    uint8_t stretch( int value, uint8_t max ) {
+        return ( value * max ) >> 8;
+    }
+
+    uint8_t channelGamma( int channel ) {
+        /* The optimal gamma correction is x^2.8. However, this is expensive to
+         * compute. Therefore, we use x^3 for gamma correction. Also, we add a
+         * bias as the WS2812 LEDs do not turn on for values less than 4. */
+        if (channel == 0)
+            return channel;
+        channel = channel * channel * channel * 251;
+        channel >>= 24;
+        return static_cast< uint8_t >( 4 + channel );
+    }
+};
+
+union Hsv {
+    struct __attribute__ ((packed)) {
+        uint8_t h, s, v, a;
+    };
+    uint32_t value;
+
+    Hsv( uint8_t h, uint8_t s = 0, uint8_t v = 0, uint8_t a = 255 ) : h( h ), s( s ), v( v ), a( a ) {}
+    Hsv( Rgb r );
+    Hsv& operator=( Hsv h ) { swap( h ); return *this; }
+    Hsv& operator=( Rgb rgb );
+    bool operator==( Hsv in ) const { return in.value == value; }
+    void swap( Hsv& o ) { value = o.value; }
+};
--- a/code/components/jomjol_controlGPIO/SmartLeds.cpp
+++ b/code/components/jomjol_controlGPIO/SmartLeds.cpp
@@ -0,0 +1,63 @@
+#include "SmartLeds.h"
+
+IsrCore SmartLed::_interruptCore = CoreCurrent;
+intr_handle_t SmartLed::_interruptHandle = NULL;
+
+SmartLed*& IRAM_ATTR SmartLed::ledForChannel( int channel ) {
+    static SmartLed* table[8] = { nullptr };
+    assert( channel < 8 );
+    return table[ channel ];
+}
+
+void IRAM_ATTR SmartLed::interruptHandler(void*) {
+    for (int channel = 0; channel != 8; channel++) {
+        auto self = ledForChannel( channel );
+
+        if ( RMT.int_st.val & (1 << (24 + channel ) ) ) { // tx_thr_event
+            if ( self )
+                self->copyRmtHalfBlock();
+            RMT.int_clr.val |= 1 << ( 24 + channel );
+        } else if ( RMT.int_st.val & ( 1 << (3 * channel ) ) ) { // tx_end
+            if ( self )
+                xSemaphoreGiveFromISR( self->_finishedFlag, nullptr );
+            RMT.int_clr.val |= 1 << ( 3 * channel );
+        }
+    }
+}
+
+void IRAM_ATTR SmartLed::copyRmtHalfBlock() {
+    int offset = detail::MAX_PULSES * _halfIdx;
+    _halfIdx = !_halfIdx;
+    int len = 3 - _componentPosition + 3 * ( _count - 1 );
+    len = std::min( len, detail::MAX_PULSES / 8 );
+
+    if ( !len ) {
+        for ( int i = 0; i < detail::MAX_PULSES; i++) {
+            RMTMEM.chan[ _channel].data32[i + offset ].val = 0;
+        }
+    }
+
+    int i;
+    for ( i = 0; i != len && _pixelPosition != _count; i++ ) {
+        uint8_t val = _buffer[ _pixelPosition ].getGrb( _componentPosition );
+        for ( int j = 0; j != 8; j++, val <<= 1 ) {
+            int bit = val >> 7;
+            int idx = i * 8 + offset + j;
+            RMTMEM.chan[ _channel ].data32[ idx ].val = _bitToRmt[ bit & 0x01 ].value;
+        }
+        if ( _pixelPosition == _count - 1 && _componentPosition == 2 ) {
+            RMTMEM.chan[ _channel ].data32[ i * 8 + offset + 7 ].duration1 =
+                _timing.TRS / ( detail::RMT_DURATION_NS * detail::DIVIDER );
+        }
+
+        _componentPosition++;
+        if ( _componentPosition == 3 ) {
+            _componentPosition = 0;
+            _pixelPosition++;
+        }
+    }
+
+    for ( i *= 8; i != detail::MAX_PULSES; i++ ) {
+        RMTMEM.chan[ _channel ].data32[ i + offset ].val = 0;
+    }
+}
--- a/code/components/jomjol_controlGPIO/SmartLeds.h
+++ b/code/components/jomjol_controlGPIO/SmartLeds.h
@@ -0,0 +1,530 @@
+#pragma once
+
+/*
+ * A C++ driver for the WS2812 LEDs using the RMT peripheral on the ESP32.
+ *
+ * Jan "yaqwsx" Mrázek <email@honzamrazek.cz>
+ *
+ * Based on the work by Martin F. Falatic - https://github.com/FozzTexx/ws2812-demo
+ */
+
+/*
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+ * THE SOFTWARE.
+ */
+
+#include <memory>
+#include <cassert>
+#include <cstring>
+
+#if defined ( ARDUINO )
+    extern "C" { // ...someone forgot to put in the includes...
+        #include "esp32-hal.h"
+        #include "esp_intr_alloc.h"
+        #include "esp_ipc.h"
+        #include "driver/gpio.h"
+        #include "driver/periph_ctrl.h"
+        #include "freertos/semphr.h"
+        #include "soc/rmt_struct.h"
+        #include <driver/spi_master.h>
+        #include "esp_idf_version.h"
+#if ESP_IDF_VERSION >= ESP_IDF_VERSION_VAL( 4, 0, 0 )
+        #include "soc/dport_reg.h"
+#endif
+    }
+#elif defined ( ESP_PLATFORM )
+    extern "C" { // ...someone forgot to put in the includes...
+        #include <esp_intr_alloc.h>
+        #include <esp_ipc.h>
+        #include <driver/gpio.h>
+        #include <freertos/FreeRTOS.h>
+        #include <freertos/semphr.h>
+        #include <soc/dport_reg.h>
+        #include <soc/gpio_sig_map.h>
+        #include <soc/rmt_struct.h>
+        #include <driver/spi_master.h>
+    }
+    #include <stdio.h>
+#endif
+
+#include "Color.h"
+
+namespace detail {
+
+struct TimingParams {
+    uint32_t T0H;
+    uint32_t T1H;
+    uint32_t T0L;
+    uint32_t T1L;
+    uint32_t TRS;
+};
+
+union RmtPulsePair {
+    struct {
+        int duration0:15;
+        int level0:1;
+        int duration1:15;
+        int level1:1;
+    };
+    uint32_t value;
+};
+
+static const int DIVIDER = 4; // 8 still seems to work, but timings become marginal
+static const int MAX_PULSES = 32; // A channel has a 64 "pulse" buffer - we use half per pass
+static const double RMT_DURATION_NS = 12.5; // minimum time of a single RMT duration based on clock ns
+
+} // namespace detail
+
+using LedType = detail::TimingParams;
+
+static const LedType LED_WS2812  = { 350, 700, 800, 600, 50000 };
+static const LedType LED_WS2812B = { 400, 850, 850, 400, 50100 };
+static const LedType LED_SK6812  = { 300, 600, 900, 600, 80000 };
+static const LedType LED_WS2813  = { 350, 800, 350, 350, 300000 };
+
+enum BufferType { SingleBuffer = 0, DoubleBuffer };
+
+enum IsrCore { CoreFirst = 0, CoreSecond = 1, CoreCurrent = 2};
+
+class SmartLed {
+public:
+    // The RMT interrupt must not run on the same core as WiFi interrupts, otherwise SmartLeds
+    // can't fill the RMT buffer fast enough, resulting in rendering artifacts.
+    // Usually, that means you have to set isrCore == CoreSecond.
+    //
+    // If you use anything other than CoreCurrent, the FreeRTOS scheduler MUST be already running,
+    // so you can't use it if you define SmartLed as global variable.
+    SmartLed( const LedType& type, int count, int pin, int channel = 0, BufferType doubleBuffer = SingleBuffer, IsrCore isrCore = CoreCurrent)
+        : _timing( type ),
+          _channel( channel ),
+          _count( count ),
+          _firstBuffer( new Rgb[ count ] ),
+          _secondBuffer( doubleBuffer ? new Rgb[ count ] : nullptr ),
+          _finishedFlag( xSemaphoreCreateBinary() )
+    {
+        assert( channel >= 0 && channel < 8 );
+        assert( ledForChannel( channel ) == nullptr );
+
+        xSemaphoreGive( _finishedFlag );
+
+        DPORT_SET_PERI_REG_MASK( DPORT_PERIP_CLK_EN_REG, DPORT_RMT_CLK_EN );
+        DPORT_CLEAR_PERI_REG_MASK( DPORT_PERIP_RST_EN_REG, DPORT_RMT_RST );
+
+        PIN_FUNC_SELECT( GPIO_PIN_MUX_REG[ pin ], 2 );
+        gpio_set_direction( static_cast< gpio_num_t >( pin ), GPIO_MODE_OUTPUT );
+        gpio_matrix_out( static_cast< gpio_num_t >( pin ), RMT_SIG_OUT0_IDX + _channel, 0, 0 );
+        initChannel( _channel );
+
+        RMT.tx_lim_ch[ _channel ].limit = detail::MAX_PULSES;
+        RMT.int_ena.val |= 1 << ( 24 + _channel );
+        RMT.int_ena.val |= 1 << ( 3 * _channel );
+
+        _bitToRmt[ 0 ].level0 = 1;
+        _bitToRmt[ 0 ].level1 = 0;
+        _bitToRmt[ 0 ].duration0 = _timing.T0H / ( detail::RMT_DURATION_NS * detail::DIVIDER );
+        _bitToRmt[ 0 ].duration1 = _timing.T0L / ( detail::RMT_DURATION_NS * detail::DIVIDER );
+
+        _bitToRmt[ 1 ].level0 = 1;
+        _bitToRmt[ 1 ].level1 = 0;
+        _bitToRmt[ 1 ].duration0 = _timing.T1H / ( detail::RMT_DURATION_NS * detail::DIVIDER );
+        _bitToRmt[ 1 ].duration1 = _timing.T1L / ( detail::RMT_DURATION_NS * detail::DIVIDER );
+
+        if ( !anyAlive() ) {
+            _interruptCore = isrCore;
+            if(isrCore != CoreCurrent) {
+                ESP_ERROR_CHECK(esp_ipc_call_blocking(isrCore, registerInterrupt, NULL));
+            } else {
+                registerInterrupt(NULL);
+            }
+        }
+
+        ledForChannel( channel ) = this;
+    }
+
+    ~SmartLed() {
+        ledForChannel( _channel ) = nullptr;
+        if ( !anyAlive() ) {
+            if(_interruptCore != CoreCurrent) {
+                ESP_ERROR_CHECK(esp_ipc_call_blocking(_interruptCore, unregisterInterrupt, NULL));
+            } else {
+                unregisterInterrupt(NULL);
+            }
+        }
+        vSemaphoreDelete( _finishedFlag );
+    }
+
+    Rgb& operator[]( int idx ) {
+        return _firstBuffer[ idx ];
+    }
+
+    const Rgb& operator[]( int idx ) const {
+        return _firstBuffer[ idx ];
+    }
+
+    void show() {
+        _buffer = _firstBuffer.get();
+        startTransmission();
+        swapBuffers();
+    }
+
+    bool wait( TickType_t timeout = portMAX_DELAY ) {
+        if( xSemaphoreTake( _finishedFlag, timeout ) == pdTRUE ) {
+            xSemaphoreGive( _finishedFlag );
+            return true;
+        }
+        return false;
+    }
+
+    int size() const {
+        return _count;
+    }
+
+    Rgb *begin() { return _firstBuffer.get(); }
+    const Rgb *begin() const { return _firstBuffer.get(); }
+    const Rgb *cbegin() const { return _firstBuffer.get(); }
+
+    Rgb *end() { return _firstBuffer.get() + _count; }
+    const Rgb *end() const { return _firstBuffer.get() + _count; }
+    const Rgb *cend() const { return _firstBuffer.get() + _count; }
+
+private:
+    static intr_handle_t _interruptHandle;
+    static IsrCore _interruptCore;
+
+    static void initChannel( int channel ) {
+        RMT.apb_conf.fifo_mask = 1;  //enable memory access, instead of FIFO mode.
+        RMT.apb_conf.mem_tx_wrap_en = 1; //wrap around when hitting end of buffer
+        RMT.conf_ch[ channel ].conf0.div_cnt = detail::DIVIDER;
+        RMT.conf_ch[ channel ].conf0.mem_size = 1;
+        RMT.conf_ch[ channel ].conf0.carrier_en = 0;
+        RMT.conf_ch[ channel ].conf0.carrier_out_lv = 1;
+        RMT.conf_ch[ channel ].conf0.mem_pd = 0;
+
+        RMT.conf_ch[ channel ].conf1.rx_en = 0;
+        RMT.conf_ch[ channel ].conf1.mem_owner = 0;
+        RMT.conf_ch[ channel ].conf1.tx_conti_mode = 0;    //loop back mode.
+        RMT.conf_ch[ channel ].conf1.ref_always_on = 1;    // use apb clock: 80M
+        RMT.conf_ch[ channel ].conf1.idle_out_en = 1;
+        RMT.conf_ch[ channel ].conf1.idle_out_lv = 0;
+    }
+
+    static void registerInterrupt(void *) {
+        ESP_ERROR_CHECK(esp_intr_alloc( ETS_RMT_INTR_SOURCE, 0, interruptHandler, nullptr, &_interruptHandle));
+    }
+
+    static void unregisterInterrupt(void*) {
+        esp_intr_free( _interruptHandle );
+    }
+
+    static SmartLed*& IRAM_ATTR ledForChannel( int channel );
+    static void IRAM_ATTR interruptHandler( void* );
+
+    void IRAM_ATTR copyRmtHalfBlock();
+
+    void swapBuffers() {
+        if ( _secondBuffer )
+            _firstBuffer.swap( _secondBuffer );
+    }
+
+    void startTransmission() {
+        // Invalid use of the library
+        if( xSemaphoreTake( _finishedFlag, 0 ) != pdTRUE )
+            abort();
+
+        _pixelPosition = _componentPosition = _halfIdx = 0;
+        copyRmtHalfBlock();
+        if ( _pixelPosition < _count )
+            copyRmtHalfBlock();
+
+        RMT.conf_ch[ _channel ].conf1.mem_rd_rst = 1;
+        RMT.conf_ch[ _channel ].conf1.tx_start = 1;
+    }
+
+    static bool anyAlive() {
+        for ( int i = 0; i != 8; i++ )
+            if ( ledForChannel( i ) != nullptr ) return true;
+        return false;
+    }
+
+    const LedType& _timing;
+    int _channel;
+    detail::RmtPulsePair _bitToRmt[ 2 ];
+    int _count;
+    std::unique_ptr< Rgb[] > _firstBuffer;
+    std::unique_ptr< Rgb[] > _secondBuffer;
+    Rgb *_buffer;
+
+    xSemaphoreHandle _finishedFlag;
+
+    int _pixelPosition;
+    int _componentPosition;
+    int _halfIdx;
+};
+
+class Apa102 {
+public:
+    struct ApaRgb {
+        ApaRgb( uint8_t r = 0, uint8_t g = 0, uint32_t b = 0, uint32_t v = 0xFF )
+            : v( 0xE0 | v ), b( b ), g( g ), r( r )
+        {}
+
+        ApaRgb& operator=( const Rgb& o ) {
+            r = o.r;
+            g = o.g;
+            b = o.b;
+            return *this;
+        }
+
+        ApaRgb& operator=( const Hsv& o ) {
+            *this = Rgb{ o };
+            return *this;
+        }
+
+        uint8_t v, b, g, r;
+    };
+
+    static const int FINAL_FRAME_SIZE = 4;
+    static const int TRANS_COUNT = 2 + 8;
+
+    Apa102( int count, int clkpin, int datapin, BufferType doubleBuffer = SingleBuffer )
+        : _count( count ),
+          _firstBuffer( new ApaRgb[ count ] ),
+          _secondBuffer( doubleBuffer ? new ApaRgb[ count ] : nullptr ),
+          _initFrame( 0 )
+    {
+        spi_bus_config_t buscfg;
+        memset( &buscfg, 0, sizeof( buscfg ) );
+        buscfg.mosi_io_num = datapin;
+        buscfg.miso_io_num = -1;
+        buscfg.sclk_io_num = clkpin;
+        buscfg.quadwp_io_num = -1;
+        buscfg.quadhd_io_num = -1;
+        buscfg.max_transfer_sz = 65535;
+
+        spi_device_interface_config_t devcfg;
+        memset( &devcfg, 0, sizeof( devcfg ) );
+        devcfg.clock_speed_hz = 1000000;
+        devcfg.mode = 0;
+        devcfg.spics_io_num = -1;
+        devcfg.queue_size = TRANS_COUNT;
+        devcfg.pre_cb = nullptr;
+
+        auto ret = spi_bus_initialize( HSPI_HOST, &buscfg, 1 );
+        assert( ret == ESP_OK );
+
+        ret = spi_bus_add_device( HSPI_HOST, &devcfg, &_spi );
+        assert( ret == ESP_OK );
+
+        std::fill_n( _finalFrame, FINAL_FRAME_SIZE, 0xFFFFFFFF );
+    }
+
+    ~Apa102() {
+        // ToDo
+    }
+
+    ApaRgb& operator[]( int idx ) {
+        return _firstBuffer[ idx ];
+    }
+
+    const ApaRgb& operator[]( int idx ) const {
+        return _firstBuffer[ idx ];
+    }
+
+    void show() {
+        _buffer = _firstBuffer.get();
+        startTransmission();
+        swapBuffers();
+    }
+
+    void wait() {
+        for ( int i = 0; i != _transCount; i++ ) {
+            spi_transaction_t *t;
+            spi_device_get_trans_result( _spi, &t, portMAX_DELAY );
+        }
+    }
+private:
+    void swapBuffers() {
+        if ( _secondBuffer )
+            _firstBuffer.swap( _secondBuffer );
+    }
+
+    void startTransmission() {
+        for ( int i = 0; i != TRANS_COUNT; i++ ) {
+            _transactions[ i ].cmd = 0;
+            _transactions[ i ].addr = 0;
+            _transactions[ i ].flags = 0;
+            _transactions[ i ].rxlength = 0;
+            _transactions[ i ].rx_buffer = nullptr;
+        }
+        // Init frame
+        _transactions[ 0 ].length = 32;
+        _transactions[ 0 ].tx_buffer = &_initFrame;
+        spi_device_queue_trans( _spi, _transactions + 0, portMAX_DELAY );
+        // Data
+        _transactions[ 1 ].length = 32 * _count;
+        _transactions[ 1 ].tx_buffer = _buffer;
+        spi_device_queue_trans( _spi, _transactions + 1, portMAX_DELAY );
+        _transCount = 2;
+        // End frame
+        for ( int i = 0; i != 1 + _count / 32 / FINAL_FRAME_SIZE; i++ ) {
+            _transactions[ 2 + i ].length = 32 * FINAL_FRAME_SIZE;
+            _transactions[ 2 + i ].tx_buffer = _finalFrame;
+            spi_device_queue_trans( _spi, _transactions + 2 + i, portMAX_DELAY );
+            _transCount++;
+        }
+    }
+
+    spi_device_handle_t _spi;
+    int _count;
+    std::unique_ptr< ApaRgb[] > _firstBuffer, _secondBuffer;
+    ApaRgb *_buffer;
+
+    spi_transaction_t _transactions[ TRANS_COUNT ];
+    int _transCount;
+
+    uint32_t _initFrame;
+    uint32_t _finalFrame[ FINAL_FRAME_SIZE ];
+};
+
+class LDP8806 {
+public:
+    struct LDP8806_GRB {
+
+        LDP8806_GRB( uint8_t g_7bit = 0, uint8_t r_7bit = 0, uint32_t b_7bit = 0 )
+            : g( g_7bit ), r( r_7bit ), b( b_7bit )
+        {
+        }
+
+        LDP8806_GRB& operator=( const Rgb& o ) {
+            //Convert 8->7bit colour
+            r = ( o.r * 127 / 256 ) | 0x80;
+            g = ( o.g * 127 / 256 ) | 0x80;
+            b = ( o.b * 127 / 256 ) | 0x80;
+            return *this;
+        }
+
+        LDP8806_GRB& operator=( const Hsv& o ) {
+            *this = Rgb{ o };
+            return *this;
+        }
+
+        uint8_t g, r, b;
+    };
+
+    static const int LED_FRAME_SIZE_BYTES = sizeof( LDP8806_GRB );
+    static const int LATCH_FRAME_SIZE_BYTES = 3;
+    static const int TRANS_COUNT_MAX = 20;//Arbitrary, supports up to 600 LED
+
+    LDP8806( int count, int clkpin, int datapin, BufferType doubleBuffer = SingleBuffer, uint32_t clock_speed_hz = 2000000 )
+        : _count( count ),
+          _firstBuffer( new LDP8806_GRB[ count ] ),
+          _secondBuffer( doubleBuffer ? new LDP8806_GRB[ count ] : nullptr ),
+          // one 'latch'/start-of-data mark frame for every 32 leds
+          _latchFrames( ( count + 31 ) / 32 )
+    {
+        spi_bus_config_t buscfg;
+        memset( &buscfg, 0, sizeof( buscfg ) );
+        buscfg.mosi_io_num = datapin;
+        buscfg.miso_io_num = -1;
+        buscfg.sclk_io_num = clkpin;
+        buscfg.quadwp_io_num = -1;
+        buscfg.quadhd_io_num = -1;
+        buscfg.max_transfer_sz = 65535;
+
+        spi_device_interface_config_t devcfg;
+        memset( &devcfg, 0, sizeof( devcfg ) );
+        devcfg.clock_speed_hz = clock_speed_hz;
+        devcfg.mode = 0;
+        devcfg.spics_io_num = -1;
+        devcfg.queue_size = TRANS_COUNT_MAX;
+        devcfg.pre_cb = nullptr;
+
+        auto ret = spi_bus_initialize( HSPI_HOST, &buscfg, 1 );
+        assert( ret == ESP_OK );
+
+        ret = spi_bus_add_device( HSPI_HOST, &devcfg, &_spi );
+        assert( ret == ESP_OK );
+
+        std::fill_n( _latchBuffer, LATCH_FRAME_SIZE_BYTES, 0x0 );
+    }
+
+    ~LDP8806() {
+        // noop
+    }
+
+    LDP8806_GRB& operator[]( int idx ) {
+        return _firstBuffer[ idx ];
+    }
+
+    const LDP8806_GRB& operator[]( int idx ) const {
+        return _firstBuffer[ idx ];
+    }
+
+    void show() {
+        _buffer = _firstBuffer.get();
+        startTransmission();
+        swapBuffers();
+    }
+
+    void wait() {
+        while ( _transCount-- ) {
+            spi_transaction_t *t;
+            spi_device_get_trans_result( _spi, &t, portMAX_DELAY );
+        }
+    }
+private:
+    void swapBuffers() {
+        if ( _secondBuffer )
+            _firstBuffer.swap( _secondBuffer );
+    }
+
+    void startTransmission() {
+        _transCount = 0;
+        for ( int i = 0; i != TRANS_COUNT_MAX; i++ ) {
+            _transactions[ i ].cmd = 0;
+            _transactions[ i ].addr = 0;
+            _transactions[ i ].flags = 0;
+            _transactions[ i ].rxlength = 0;
+            _transactions[ i ].rx_buffer = nullptr;
+        }
+        // LED Data
+        _transactions[ 0 ].length = ( LED_FRAME_SIZE_BYTES * 8 ) * _count;
+        _transactions[ 0 ].tx_buffer = _buffer;
+        spi_device_queue_trans( _spi, _transactions + _transCount, portMAX_DELAY );
+        _transCount++;
+
+        // 'latch'/start-of-data marker frames
+        for ( int i = 0; i < _latchFrames; i++ ) {
+            _transactions[ _transCount ].length = ( LATCH_FRAME_SIZE_BYTES * 8 );
+            _transactions[ _transCount ].tx_buffer = _latchBuffer;
+            spi_device_queue_trans( _spi, _transactions + _transCount, portMAX_DELAY );
+            _transCount++;
+        }
+    }
+
+    spi_device_handle_t _spi;
+    int _count;
+    std::unique_ptr< LDP8806_GRB[] > _firstBuffer, _secondBuffer;
+    LDP8806_GRB *_buffer;
+
+    spi_transaction_t _transactions[ TRANS_COUNT_MAX ];
+    int _transCount;
+
+    int _latchFrames;
+    uint8_t _latchBuffer[ LATCH_FRAME_SIZE_BYTES ];
+};
--- a/code/components/jomjol_controlGPIO/server_GPIO.cpp
+++ b/code/components/jomjol_controlGPIO/server_GPIO.cpp
@@ -8,6 +8,8 @@
 #include "esp_system.h"
 #include "esp_event.h"

+#include "server_tflite.h"
+
 //#define LOG_LOCAL_LEVEL ESP_LOG_DEBUG
 #include "esp_log.h"
 //#include "errno.h"
@@ -105,7 +107,8 @@ void GpioPin::init()
    //configure GPIO with the given settings
    gpio_config(&io_conf);

-    if (_interruptType != GPIO_INTR_DISABLE) {
+//    if (_interruptType != GPIO_INTR_DISABLE) {                // ohne GPIO_PIN_MODE_EXTERNAL_FLASH_WS281X, wenn das genutzt wird, dann soll auch der Handler hier nicht initialisiert werden, da das dann über SmartLED erfolgt.
+    if ((_interruptType != GPIO_INTR_DISABLE) && (_interruptType != GPIO_PIN_MODE_EXTERNAL_FLASH_WS281X)) {
        //hook isr handler for specific gpio pin
        ESP_LOGD(TAG_SERVERGPIO, "GpioPin::init add isr handler for GPIO %d\r\n", _gpio);
        gpio_isr_handler_add(_gpio, gpio_isr_handler, (void*)&_gpio);
@@ -210,12 +213,15 @@ void GpioHandler::init()
    // printf("wait before start %ldms\r\n", (long) xDelay);
    // vTaskDelay( xDelay );

+    printf("*************** Start GPIOHandler_Init *****************\n");
+
    if (gpioMap == NULL) {
        gpioMap = new std::map<gpio_num_t, GpioPin*>();
    } else {
        clear();
    }
    
+    
    ESP_LOGI(TAG_SERVERGPIO, "read GPIO config and init GPIO");
    if (!readConfig()) {
        clear();
@@ -225,6 +231,7 @@ void GpioHandler::init()
        return;
    }

+
    for(std::map<gpio_num_t, GpioPin*>::iterator it = gpioMap->begin(); it != gpioMap->end(); ++it) {
        it->second->init();
    }
@@ -291,17 +298,32 @@ bool GpioHandler::readConfig()
    std::string line = "";
    bool disabledLine = false;
    bool eof = false;
+    gpio_num_t gpioExtLED = (gpio_num_t) 0;
+    
+//    printf("readConfig - Start 1\n");
        
-    while ((!configFile.GetNextParagraph(line, disabledLine, eof) || (line.compare("[GPIO]") != 0)) && !disabledLine && !eof) {}
+    while ((!configFile.GetNextParagraph(line, disabledLine, eof) || (line.compare("[GPIO]") != 0)) && !eof) {}
    if (eof)
        return false;
-    
+
+//    printf("readConfig - Start 2 line: %s, disabbledLine: %d\n", line.c_str(), (int) disabledLine);
+
+
    _isEnabled = !disabledLine;

    if (!_isEnabled)
        return false;

-    std::string mainTopicMQTT = "";
+//    printf("readConfig - Start 3\n");
+
+//    std::string mainTopicMQTT = "";
+    std::string mainTopicMQTT = GetMQTTMainTopic();
+    if (mainTopicMQTT.length() > 0)
+    {
+        mainTopicMQTT = mainTopicMQTT + "/GPIO";
+        ESP_LOGD(TAG_SERVERGPIO, "MAINTOPICMQTT found\r\n");
+    }
+
    bool registerISR = false;
    while (configFile.getNextLine(&line, disabledLine, eof) && !configFile.isNewParagraph(line))
    {
@@ -313,8 +335,8 @@ bool GpioHandler::readConfig()
        //     std::string gpioStr = pieces_match[1];
        ESP_LOGD(TAG_SERVERGPIO, "conf param %s\r\n", toUpper(zerlegt[0]).c_str());
        if (toUpper(zerlegt[0]) == "MAINTOPICMQTT") {
-            ESP_LOGD(TAG_SERVERGPIO, "MAINTOPICMQTT found\r\n");
-            mainTopicMQTT = zerlegt[1];
+//            ESP_LOGD(TAG_SERVERGPIO, "MAINTOPICMQTT found\r\n");
+//            mainTopicMQTT = zerlegt[1];
        } else if ((zerlegt[0].rfind("IO", 0) == 0) && (zerlegt.size() >= 6))
        {
            ESP_LOGI(TAG_SERVERGPIO,"Enable GP%s in %s mode", zerlegt[0].c_str(), zerlegt[1].c_str());
@@ -335,10 +357,40 @@ bool GpioHandler::readConfig()
            GpioPin* gpioPin = new GpioPin(gpioNr, gpioName, pinMode, intType,dutyResolution, mqttTopic, httpEnabled);
            (*gpioMap)[gpioNr] = gpioPin;

+            if (pinMode == GPIO_PIN_MODE_EXTERNAL_FLASH_WS281X)
+            {
+                printf("Set WS2812 to GPIO %d\n", gpioNr);
+                gpioExtLED = gpioNr;
+            }
+
            if (intType != GPIO_INTR_DISABLE) {
                registerISR = true;
            }
        }
+        if (toUpper(zerlegt[0]) == "LEDNUMBERS")
+        {
+            LEDNumbers = stoi(zerlegt[1]);
+        }
+        if (toUpper(zerlegt[0]) == "LEDCOLOR")
+        {
+            uint8_t _r, _g, _b;
+            _r = stoi(zerlegt[1]);
+            _g = stoi(zerlegt[2]);
+            _b = stoi(zerlegt[3]);
+
+            LEDColor = Rgb{_r, _g, _b};
+        }
+        if (toUpper(zerlegt[0]) == "LEDTYPE")
+        {
+            if (zerlegt[1] == "WS2812")
+                LEDType = LED_WS2812;
+            if (zerlegt[1] == "WS2812B")
+                LEDType = LED_WS2812B;
+            if (zerlegt[1] == "SK6812")
+                LEDType = LED_SK6812;
+            if (zerlegt[1] == "WS2813")
+                LEDType = LED_WS2813;
+        }
    }

    if (registerISR) {
@@ -346,6 +398,23 @@ bool GpioHandler::readConfig()
        gpio_install_isr_service(ESP_INTR_FLAG_LOWMED | ESP_INTR_FLAG_IRAM);
    }

+    if (gpioExtLED > 0)
+    {
+    //     LogFile.WriteToFile("Startsequence 06");      // Nremove
+//        vTaskDelay( xDelay );   
+//        xDelay = 5000 / portTICK_PERIOD_MS;
+//        printf("main: sleep for : %ldms\n", (long) xDelay);
+
+//        SmartLed leds( LED_WS2812, 2, GPIO_NUM_12, 0, DoubleBuffer );
+
+
+//        leds[ 0 ] = Rgb{ 255, 0, 0 };
+//        leds[ 1 ] = Rgb{ 255, 255, 255 };
+//        leds.show();    
+//        SmartLed leds = new SmartLed(LEDType, LEDNumbers, gpioExtLED, 0, DoubleBuffer);
+//        _SmartLED = new SmartLed( LED_WS2812, 2, GPIO_NUM_12, 0, DoubleBuffer );
+    }
+
    return true;
 }

@@ -487,7 +556,47 @@ void GpioHandler::flashLightEnable(bool value)
                } else {
                    ESP_LOGE(TAG_SERVERGPIO, "Can't set flash light pin GPIO %d.  Error: %s\r\n", (int)it->first, resp_str.c_str());
                }
-            }
+            } else 
+                {
+                    if (it->second->getMode() == GPIO_PIN_MODE_EXTERNAL_FLASH_WS281X)
+                    {
+#ifdef __LEDGLOBAL
+                        if (leds_global == NULL) {
+                            ESP_LOGI(TAG_SERVERGPIO, "init SmartLed: LEDNumber=%d, GPIO=%d", LEDNumbers, (int)it->second->getGPIO());
+                            leds_global = new SmartLed( LEDType, LEDNumbers, it->second->getGPIO(), 0, DoubleBuffer );
+                        } else {
+                            // wait until we can update: https://github.com/RoboticsBrno/SmartLeds/issues/10#issuecomment-386921623
+                            leds_global->wait();
+                        }
+#else
+                        SmartLed leds( LEDType, LEDNumbers, it->second->getGPIO(), 0, DoubleBuffer );
+#endif
+  
+                        if (value)
+                        {
+                            for (int i = 0; i < LEDNumbers; ++i)
+#ifdef __LEDGLOBAL
+                                (*leds_global)[i] = LEDColor;
+#else
+                                leds[i] = LEDColor;
+#endif
+                        }
+                        else
+                        {
+                            for (int i = 0; i < LEDNumbers; ++i)
+#ifdef __LEDGLOBAL
+                                (*leds_global)[i] = Rgb{0, 0, 0};
+#else
+                                leds[i] = Rgb{0, 0, 0};
+#endif
+                        }
+#ifdef __LEDGLOBAL
+                        leds_global->show(); 
+#else
+                        leds.show(); 
+#endif 
+                    }
+                }
        }
    }
 }
--- a/code/components/jomjol_controlGPIO/server_GPIO.h
+++ b/code/components/jomjol_controlGPIO/server_GPIO.h
@@ -7,8 +7,13 @@
 #include <map>
 #include "driver/gpio.h"

+#include "SmartLeds.h"
+
 //#include "ClassControllCamera.h"

+// wenn __LEDGLOBAL definiert ist, wird eine globale Variable für die LED-Ansteuerung verwendet, ansonsten lokal und jedesmal neu
+#define __LEDGLOBAL
+
 typedef enum {
    GPIO_PIN_MODE_DISABLED              = 0x0,
    GPIO_PIN_MODE_INPUT                 = 0x1,
@@ -45,6 +50,7 @@ public:
    void gpioInterrupt(int value);
    gpio_int_type_t getInterruptType() { return _interruptType; }
    gpio_pin_mode_t getMode() { return _mode; }
+    gpio_num_t getGPIO(){return _gpio;};

 private:
    gpio_num_t _gpio;
@@ -80,6 +86,13 @@ private:
    TaskHandle_t xHandleTaskGpio = NULL;
    bool _isEnabled = false;

+    int LEDNumbers = 2;
+    Rgb LEDColor = Rgb{ 255, 255, 255 };
+    LedType LEDType = LED_WS2812;
+#ifdef __LEDGLOBAL
+    SmartLed *leds_global = NULL;
+#endif
+
    bool readConfig();
    void clear();
    
--- a/code/components/jomjol_controlcamera/ClassControllCamera.cpp
+++ b/code/components/jomjol_controlcamera/ClassControllCamera.cpp
@@ -74,7 +74,7 @@ static camera_config_t camera_config = {

    //XCLK 20MHz or 10MHz for OV2640 double FPS (Experimental)
 //    .xclk_freq_hz = 20000000,             // Orginalwert
-    .xclk_freq_hz = 5000000,               // Test, um die Bildfehler los zu werden !!!!
+    .xclk_freq_hz =    5000000,               // Test, um die Bildfehler los zu werden !!!!
    .ledc_timer = LEDC_TIMER_0,
    .ledc_channel = LEDC_CHANNEL_0,

@@ -86,6 +86,8 @@ static camera_config_t camera_config = {

    .jpeg_quality = 5, //0-63 lower number means higher quality
    .fb_count = 1       //if more than one, i2s runs in continuous mode. Use only with JPEG
+//    .grab_mode = CAMERA_GRAB_WHEN_EMPTY,
+
 };


@@ -279,13 +281,23 @@ esp_err_t CCamera::CaptureToBasisImage(CImageBasis *_Image, int delay)
        ESP_LOGE(TAGCAMERACLASS, "CaptureToBasisImage: Camera Capture Failed");
        LEDOnOff(false);
        LightOnOff(false);
-        doReboot();
+
+        LogFile.SwitchOnOff(true);
+        LogFile.WriteToFile("Camera is not working anymore - most propably hardware problem (instablility, ...). "
+                "System will reboot.");
+         doReboot();

        return ESP_FAIL;
    }

    int _size = fb->len;
    zwischenspeicher = (uint8_t*) malloc(_size);
+    if (!zwischenspeicher)
+    {
+        ESP_LOGE(TAGCAMERACLASS, "Nicht ausreichend Speicherplatz für Bild in Funktion CaptureToBasisImage()");
+        LogFile.SwitchOnOff(true);
+        LogFile.WriteToFile("Nicht ausreichend Speicherplatz für Bild in Funktion CaptureToBasisImage()");
+    }
    for (int i = 0; i < _size; ++i)
        *(zwischenspeicher + i) = *(fb->buf + i);
    esp_camera_fb_return(fb);        
@@ -499,6 +511,7 @@ void CCamera::LightOnOff(bool status)
 {
    GpioHandler* gpioHandler = gpio_handler_get();
    if ((gpioHandler != NULL) && (gpioHandler->isEnabled())) {
+        printf("Use gpioHandler flashLigh\n");
        gpioHandler->flashLightEnable(status);
    }  else {
        // Init the GPIO
--- a/code/components/jomjol_controlcamera/sensor.h
+++ b/code/components/jomjol_controlcamera/sensor.h
@@ -11,11 +11,48 @@
 #include <stdint.h>
 #include <stdbool.h>

-#define OV9650_PID     (0x96)
-#define OV7725_PID     (0x77)
-#define OV2640_PID     (0x26)
-#define OV3660_PID     (0x36)
-#define OV5640_PID     (0x56)
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+typedef enum {
+    OV9650_PID = 0x96,
+    OV7725_PID = 0x77,
+    OV2640_PID = 0x26,
+    OV3660_PID = 0x3660,
+    OV5640_PID = 0x5640,
+    OV7670_PID = 0x76,
+    NT99141_PID = 0x1410,
+    GC2145_PID = 0x2145,
+    GC032A_PID = 0x232a,
+    GC0308_PID = 0x9b,
+} camera_pid_t;
+
+typedef enum {
+    CAMERA_OV7725,
+    CAMERA_OV2640,
+    CAMERA_OV3660,
+    CAMERA_OV5640,
+    CAMERA_OV7670,
+    CAMERA_NT99141,
+    CAMERA_GC2145,
+    CAMERA_GC032A,
+    CAMERA_GC0308,
+    CAMERA_MODEL_MAX,
+    CAMERA_NONE,
+} camera_model_t;
+
+typedef enum {
+    OV2640_SCCB_ADDR   = 0x30,// 0x60 >> 1
+    OV5640_SCCB_ADDR   = 0x3C,// 0x78 >> 1
+    OV3660_SCCB_ADDR   = 0x3C,// 0x78 >> 1
+    OV7725_SCCB_ADDR   = 0x21,// 0x42 >> 1
+    OV7670_SCCB_ADDR   = 0x21,// 0x42 >> 1
+    NT99141_SCCB_ADDR  = 0x2A,// 0x54 >> 1
+    GC2145_SCCB_ADDR   = 0x3C,// 0x78 >> 1
+    GC032A_SCCB_ADDR   = 0x21,// 0x42 >> 1
+    GC0308_SCCB_ADDR   = 0x21,// 0x42 >> 1
+} camera_sccb_addr_t;

 typedef enum {
    PIXFORMAT_RGB565,    // 2BPP/RGB565
@@ -56,6 +93,15 @@ typedef enum {
    FRAMESIZE_INVALID
 } framesize_t;

+typedef struct {
+    const camera_model_t model;
+    const char *name;
+    const camera_sccb_addr_t sccb_addr;
+    const camera_pid_t pid;
+    const framesize_t max_size;
+    const bool support_jpeg;
+} camera_sensor_info_t;
+
 typedef enum {
    ASPECT_RATIO_4X3,
    ASPECT_RATIO_3X2,
@@ -99,11 +145,13 @@ typedef struct {

 // Resolution table (in sensor.c)
 extern const resolution_info_t resolution[];
+// camera sensor table (in sensor.c)
+extern const camera_sensor_info_t camera_sensor[];

 typedef struct {
    uint8_t MIDH;
    uint8_t MIDL;
-    uint8_t PID;
+    uint16_t PID;
    uint8_t VER;
 } sensor_id_t;

@@ -188,4 +236,10 @@ typedef struct _sensor {
    int  (*set_xclk)            (sensor_t *sensor, int timer, int xclk);
 } sensor_t;

+camera_sensor_info_t *esp_camera_sensor_get_info(sensor_id_t *id);
+
+#ifdef __cplusplus
+}
+#endif
+
 #endif /* __SENSOR_H__ */
--- a/code/components/jomjol_controlcamera/server_camera.cpp
+++ b/code/components/jomjol_controlcamera/server_camera.cpp
@@ -8,8 +8,8 @@

 #include "ClassLogFile.h"

-#define SCRATCH_BUFSIZE2  8192 
-char scratch2[SCRATCH_BUFSIZE2];
+// #define SCRATCH_BUFSIZE2  8192 
+// char scratch2[SCRATCH_BUFSIZE2];

 //#define DEBUG_DETAIL_ON   
 static const char *TAGPARTCAMERA = "server_camera";
--- a/code/components/jomjol_fileserver_ota/CMakeLists.txt
+++ b/code/components/jomjol_fileserver_ota/CMakeLists.txt
@@ -2,6 +2,6 @@ FILE(GLOB_RECURSE app_sources ${CMAKE_CURRENT_SOURCE_DIR}/*.*)

 idf_component_register(SRCS ${app_sources}
                    INCLUDE_DIRS "." "../../include"
-                    REQUIRES tfmicro esp_http_server app_update esp_http_client nvs_flash jomjol_tfliteclass jomjol_flowcontroll spiffs jomjol_helper jomjol_controlGPIO)
+                    REQUIRES tflite-lib esp_http_server app_update esp_http_client nvs_flash jomjol_tfliteclass jomjol_flowcontroll spiffs jomjol_helper jomjol_controlGPIO)


--- a/code/components/jomjol_fileserver_ota/server_file.cpp
+++ b/code/components/jomjol_fileserver_ota/server_file.cpp
@@ -17,7 +17,14 @@
 #include <sys/param.h>
 #include <sys/unistd.h>
 #include <sys/stat.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif
 #include <dirent.h>
+#ifdef __cplusplus
+}
+#endif

 #include "esp_err.h"
 #include "esp_log.h"
@@ -58,6 +65,52 @@ struct file_server_data {

 static const char *TAG_FILESERVER = "file_server";

+
+#include <iostream>
+#include <sys/types.h>
+#include <dirent.h>
+
+using namespace std;
+
+static esp_err_t get_tflite_file_handler(httpd_req_t *req){
+    DIR *verzeichnis;
+    struct dirent *files;
+
+    std::string _filename, _fileext, _result = "";
+    std::string _delimiter = ".";
+    size_t pos = 0;
+
+    verzeichnis=opendir("/sdcard/config");
+
+    printf("Suche TFLITE in /sdcard/config\n");
+
+    while((files = readdir(verzeichnis)))
+    {
+        _filename = files->d_name;
+        _fileext = _filename;
+        printf("File: %s\t", _filename.c_str());
+
+        while ((pos = _fileext.find(_delimiter))) {
+            _fileext.erase(0, pos + _delimiter.length());
+        }
+
+        printf(" Extension: %s\n", _fileext.c_str());
+
+        if ((_fileext == "tfl") || (_fileext == "tflite"))
+        {
+            _result = _result + _filename + "\t";
+        }
+    }
+    closedir(verzeichnis);
+
+    httpd_resp_set_hdr(req, "Access-Control-Allow-Origin", "*");
+    httpd_resp_set_type(req, "text/plain");
+    httpd_resp_sendstr_chunk(req, _result.c_str());
+    httpd_resp_sendstr_chunk(req, NULL);
+    return ESP_OK;
+}
+
+
 /* Handler to redirect incoming GET request for /index.html to /
 * This can be overridden by uploading file with same name */
 // static esp_err_t index_html_get_handler(httpd_req_t *req)
@@ -797,4 +850,15 @@ void register_server_file_uri(httpd_handle_t server, const char *base_path)
    };
    httpd_register_uri_handler(server, &file_delete);

+
+    /* URI handler for getting tflite files from server */
+/*
+    httpd_uri_t file_tflite = {
+        .uri       = "/tflite",   // Match all URIs of type /delete/path/to/file
+        .method    = HTTP_GET,
+        .handler   = get_tflite_file_handler,
+        .user_ctx  = server_data    // Pass server data as context
+    };
+    httpd_register_uri_handler(server, &file_tflite);
+*/
 }
--- a/code/components/jomjol_fileserver_ota/server_help.cpp
+++ b/code/components/jomjol_fileserver_ota/server_help.cpp
@@ -5,7 +5,14 @@
 #include <sys/param.h>
 #include <sys/unistd.h>
 #include <sys/stat.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif
 #include <dirent.h>
+#ifdef __cplusplus
+}
+#endif

 #include "esp_err.h"
 #include "esp_log.h"
@@ -111,6 +118,8 @@ esp_err_t set_content_type_from_file(httpd_req_t *req, const char *filename)
        return httpd_resp_set_type(req, "image/jpeg");
    } else if (IS_FILE_EXT(filename, ".ico")) {
        return httpd_resp_set_type(req, "image/x-icon");
+    } else if (IS_FILE_EXT(filename, ".js")) {
+        return httpd_resp_set_type(req, "text/javascript");
    }
    /* This is a limited set only */
    /* For any other type always set as plain text */
--- a/code/components/jomjol_fileserver_ota/server_ota.cpp
+++ b/code/components/jomjol_fileserver_ota/server_ota.cpp
@@ -30,6 +30,7 @@
 #include "server_file.h"
 #include "server_GPIO.h"

+
 #include "ClassLogFile.h"

 #include "Helper.h"
--- a/code/components/jomjol_flowcontroll/ClassFlow.cpp
+++ b/code/components/jomjol_flowcontroll/ClassFlow.cpp
@@ -130,11 +130,9 @@ bool ClassFlow::getNextLine(FILE* pfile, string *rt)
 	*rt = trim(*rt);
 	while ((zw[0] == ';' || zw[0] == '#' || (rt->size() == 0)) && !(zw[1] == '['))			// Kommentarzeilen (; oder #) und Leerzeilen überspringen, es sei denn es ist ein neuer auskommentierter Paragraph
 	{
+		*rt = "";
 		if (!fgets(zw, 1024, pfile))
-		{
-			*rt = "";
 			return false;
-		}
 		printf("%s", zw);		
 		*rt = zw;
 		*rt = trim(*rt);
--- a/code/components/jomjol_flowcontroll/ClassFlowAnalog.cpp
+++ b/code/components/jomjol_flowcontroll/ClassFlowAnalog.cpp
@@ -1,487 +0,0 @@
-#include "ClassFlowAnalog.h"
-
-#include <math.h>
-#include <iomanip> 
-#include <sys/types.h>
-#include <sstream>      // std::stringstream
-
-  
-// #define OHNETFLITE
-
-#ifndef OHNETFLITE
-#include "CTfLiteClass.h"
-#endif
-
-#include "ClassLogFile.h"
-
-static const char* TAG = "flow_analog";
-
-bool debugdetailanalog = false;
-
-void ClassFlowAnalog::SetInitialParameter(void)
-{
-    string cnnmodelfile = "";
-    modelxsize = 1;
-    modelysize = 1;
-    ListFlowControll = NULL;
-    previousElement = NULL;   
-    SaveAllFiles = false; 
-    disabled = false;
-    extendedResolution = false;
-}   
-
-ClassFlowAnalog::ClassFlowAnalog(std::vector<ClassFlow*>* lfc) : ClassFlowImage(lfc, TAG)
-{
-    SetInitialParameter();
-    ListFlowControll = lfc;
-
-    for (int i = 0; i < ListFlowControll->size(); ++i)
-    {
-        if (((*ListFlowControll)[i])->name().compare("ClassFlowAlignment") == 0)
-        {
-            flowpostalignment = (ClassFlowAlignment*) (*ListFlowControll)[i];
-        }
-    }
-
-}
-
-
-int ClassFlowAnalog::AnzahlROIs(int _analog = 0)
-{
-    int zw = ANALOG[_analog]->ROI.size();
-    if (extendedResolution)
-        zw++;
-    
-    return zw;
-} 
-
-
-string ClassFlowAnalog::getReadout(int _analog = 0)
-{
-    string result = "";    
-    if (ANALOG[_analog]->ROI.size() == 0)
-        return result;
-
-
-    float zahl = ANALOG[_analog]->ROI[ANALOG[_analog]->ROI.size() - 1]->result;
-    int ergebnis_nachkomma = ((int) floor(zahl * 10)) % 10;
-
-    int prev = -1;
-
-    prev = ZeigerEval(ANALOG[_analog]->ROI[ANALOG[_analog]->ROI.size() - 1]->result, prev);
-    result = std::to_string(prev);
-
-    if (extendedResolution)
-        result = result + std::to_string(ergebnis_nachkomma);
-
-    for (int i = ANALOG[_analog]->ROI.size() - 2; i >= 0; --i)
-    {
-        prev = ZeigerEval(ANALOG[_analog]->ROI[i]->result, prev);
-        result = std::to_string(prev) + result;
-    }
-
-    return result;
-}
-
-int ClassFlowAnalog::ZeigerEval(float zahl, int ziffer_vorgaenger)
-{
-    int ergebnis_nachkomma = ((int) floor(zahl * 10)) % 10;
-    int ergebnis_vorkomma = ((int) floor(zahl)) % 10;
-    int ergebnis, ergebnis_rating;
-
-    if (ziffer_vorgaenger == -1)
-        return ergebnis_vorkomma % 10;
-
-    ergebnis_rating = ergebnis_nachkomma - ziffer_vorgaenger;
-    if (ergebnis_nachkomma >= 5)
-        ergebnis_rating-=5;
-    else
-        ergebnis_rating+=5;
-    ergebnis = (int) round(zahl);
-    if (ergebnis_rating < 0)
-        ergebnis-=1;
-    if (ergebnis == -1)
-        ergebnis+=10;
-
-    ergebnis = ergebnis % 10;
-    return ergebnis;
-}
-
-bool ClassFlowAnalog::ReadParameter(FILE* pfile, string& aktparamgraph)
-{
-    std::vector<string> zerlegt;
-
-    aktparamgraph = trim(aktparamgraph);
-
-    if (aktparamgraph.size() == 0)
-        if (!this->GetNextParagraph(pfile, aktparamgraph))
-            return false;
-
-
-    if ((aktparamgraph.compare("[Analog]") != 0) && (aktparamgraph.compare(";[Analog]") != 0))       // Paragraph passt nich zu MakeImage
-        return false;
-
-    if (aktparamgraph[0] == ';')
-    {
-        disabled = true;
-        while (getNextLine(pfile, &aktparamgraph) && !isNewParagraph(aktparamgraph));
-        printf("[Analog] is disabled !!!\n");
-        return true;
-    }
-
-
-    while (this->getNextLine(pfile, &aktparamgraph) && !this->isNewParagraph(aktparamgraph))
-    {
-        zerlegt = this->ZerlegeZeile(aktparamgraph);
-        if ((zerlegt[0] == "LogImageLocation") && (zerlegt.size() > 1))
-        {
-            this->LogImageLocation = "/sdcard" + zerlegt[1];
-            this->isLogImage = true;
-        }
-        if ((toUpper(zerlegt[0]) == "LOGFILERETENTIONINDAYS") && (zerlegt.size() > 1))
-        {
-            this->logfileRetentionInDays = std::stoi(zerlegt[1]);
-        }
-        if ((zerlegt[0] == "Model") && (zerlegt.size() > 1))
-        {
-            this->cnnmodelfile = zerlegt[1];
-        }
-        if ((zerlegt[0] == "ModelInputSize") && (zerlegt.size() > 2))
-        {
-            this->modelxsize = std::stoi(zerlegt[1]);
-            this->modelysize = std::stoi(zerlegt[2]);
-        }
-        if (zerlegt.size() >= 5)
-        {
-            analog* _analog = GetANALOG(zerlegt[0], true);
-            roianalog* neuroi = _analog->ROI[_analog->ROI.size()-1];
-            neuroi->posx = std::stoi(zerlegt[1]);
-            neuroi->posy = std::stoi(zerlegt[2]);
-            neuroi->deltax = std::stoi(zerlegt[3]);
-            neuroi->deltay = std::stoi(zerlegt[4]);
-            neuroi->result = -1;
-            neuroi->image = NULL;
-            neuroi->image_org = NULL;
-//            ROI.push_back(neuroi);
-        }
-
-        if ((toUpper(zerlegt[0]) == "SAVEALLFILES") && (zerlegt.size() > 1))
-        {
-            if (toUpper(zerlegt[1]) == "TRUE")
-                SaveAllFiles = true;
-        }
-
-        if ((toUpper(zerlegt[0]) == "EXTENDEDRESOLUTION") && (zerlegt.size() > 1))
-        {
-            if (toUpper(zerlegt[1]) == "TRUE")
-                extendedResolution = true;
-        }
-    }
-
-   for (int _ana = 0; _ana < ANALOG.size(); ++_ana)
-        for (int i = 0; i < ANALOG[_ana]->ROI.size(); ++i)
-        {
-            ANALOG[_ana]->ROI[i]->image = new CImageBasis(modelxsize, modelysize, 3);
-            ANALOG[_ana]->ROI[i]->image_org = new CImageBasis(ANALOG[_ana]->ROI[i]->deltax, ANALOG[_ana]->ROI[i]->deltay, 3);
-        }
-
-    return true;
-}
-
-analog* ClassFlowAnalog::FindANALOG(string _name_number)
-{
-
-    for (int i = 0; i < ANALOG.size(); ++i)
-    {
-        if (ANALOG[i]->name == _name_number)
-            return ANALOG[i];
-    }
-
-    return NULL;
-}
-
-
-
-analog* ClassFlowAnalog::GetANALOG(string _name, bool _create = true)
-{
-    string _analog, _roi;
-    int _pospunkt = _name.find_first_of(".");
-//    printf("Name: %s, Pospunkt: %d\n", _name.c_str(), _pospunkt);
-    if (_pospunkt > -1)
-    {
-        _analog = _name.substr(0, _pospunkt);
-        _roi = _name.substr(_pospunkt+1, _name.length() - _pospunkt - 1);
-    }
-    else
-    {
-        _analog = "default";
-        _roi = _name;
-    }
-
-    analog *_ret = NULL;
-
-    for (int i = 0; i < ANALOG.size(); ++i)
-    {
-        if (ANALOG[i]->name == _analog)
-            _ret = ANALOG[i];
-    }
-
-    if (!_create)         // nicht gefunden und soll auch nicht erzeugt werden
-        return _ret;
-
-
-    if (_ret == NULL)
-    {
-        _ret = new analog;
-        _ret->name = _analog;
-        ANALOG.push_back(_ret);
-    }
-
-    roianalog* neuroi = new roianalog;
-    neuroi->name = _roi;
-    _ret->ROI.push_back(neuroi);
-
-    printf("GetANALOG - ANALOG %s - roi %s\n", _analog.c_str(), _roi.c_str());
-
-    return _ret;
-}
-
-
-
-string ClassFlowAnalog::getHTMLSingleStep(string host)
-{
-    string result, zw;
-    std::vector<HTMLInfo*> htmlinfo;
-
-    result = "<p>Found ROIs: </p> <p><img src=\"" + host + "/img_tmp/alg_roi.jpg\"></p>\n";
-    result = result + "Analog Pointers: <p> ";
-
-    htmlinfo = GetHTMLInfo();
-    for (int i = 0; i < htmlinfo.size(); ++i)
-    {
-        std::stringstream stream;
-        stream << std::fixed << std::setprecision(1) << htmlinfo[i]->val;
-        zw = stream.str();
-
-        result = result + "<img src=\"" + host + "/img_tmp/" +  htmlinfo[i]->filename + "\"> " + zw;
-        delete htmlinfo[i];
-    }
-    htmlinfo.clear();         
-
-    return result;
-}
-
-
-
-bool ClassFlowAnalog::doFlow(string time)
-{
-    if (disabled)
-      return true;
-
-    if (!doAlignAndCut(time)){
-        return false;
-    };
-
-    if (debugdetailanalog) LogFile.WriteToFile("ClassFlowAnalog::doFlow nach Alignment");
-
-    doNeuralNetwork(time);
-
-    RemoveOldLogs();
-
-    return true;
-}
-
-bool ClassFlowAnalog::doAlignAndCut(string time)
-{
-    if (disabled)
-        return true;
-
-    CAlignAndCutImage *caic = flowpostalignment->GetAlignAndCutImage();    
-
-    for (int _ana = 0; _ana < ANALOG.size(); ++_ana)
-        for (int i = 0; i < ANALOG[_ana]->ROI.size(); ++i)
-        {
-            printf("Analog %d - Align&Cut\n", i);
-            
-            caic->CutAndSave(ANALOG[_ana]->ROI[i]->posx, ANALOG[_ana]->ROI[i]->posy, ANALOG[_ana]->ROI[i]->deltax, ANALOG[_ana]->ROI[i]->deltay, ANALOG[_ana]->ROI[i]->image_org);
-            if (SaveAllFiles)
-            {
-                if (ANALOG[_ana]->name == "default")
-                    ANALOG[_ana]->ROI[i]->image_org->SaveToFile(FormatFileName("/sdcard/img_tmp/" + ANALOG[_ana]->ROI[i]->name + ".jpg"));
-                else
-                    ANALOG[_ana]->ROI[i]->image_org->SaveToFile(FormatFileName("/sdcard/img_tmp/" + ANALOG[_ana]->name + "_" + ANALOG[_ana]->ROI[i]->name + ".jpg"));
-            } 
-
-            ANALOG[_ana]->ROI[i]->image_org->Resize(modelxsize, modelysize, ANALOG[_ana]->ROI[i]->image);
-            if (SaveAllFiles)
-            {
-                if (ANALOG[_ana]->name == "default")
-                    ANALOG[_ana]->ROI[i]->image->SaveToFile(FormatFileName("/sdcard/img_tmp/" + ANALOG[_ana]->ROI[i]->name + ".bmp"));
-                else
-                    ANALOG[_ana]->ROI[i]->image->SaveToFile(FormatFileName("/sdcard/img_tmp/" + ANALOG[_ana]->name + "_" + ANALOG[_ana]->ROI[i]->name + ".bmp"));
-            } 
-        }
-
-    return true;
-} 
-
-void ClassFlowAnalog::DrawROI(CImageBasis *_zw)
-{
-    int r = 0;
-    int g = 255;
-    int b = 0;
-
-    for (int _ana = 0; _ana < ANALOG.size(); ++_ana)
-        for (int i = 0; i < ANALOG[_ana]->ROI.size(); ++i)
-        {
-            _zw->drawRect(ANALOG[_ana]->ROI[i]->posx, ANALOG[_ana]->ROI[i]->posy, ANALOG[_ana]->ROI[i]->deltax, ANALOG[_ana]->ROI[i]->deltay, r, g, b, 1);
-            _zw->drawCircle((int) (ANALOG[_ana]->ROI[i]->posx + ANALOG[_ana]->ROI[i]->deltax/2), (int)  (ANALOG[_ana]->ROI[i]->posy + ANALOG[_ana]->ROI[i]->deltay/2), (int) (ANALOG[_ana]->ROI[i]->deltax/2), r, g, b, 2);
-            _zw->drawLine((int) (ANALOG[_ana]->ROI[i]->posx + ANALOG[_ana]->ROI[i]->deltax/2), (int) ANALOG[_ana]->ROI[i]->posy, (int) (ANALOG[_ana]->ROI[i]->posx + ANALOG[_ana]->ROI[i]->deltax/2), (int) (ANALOG[_ana]->ROI[i]->posy + ANALOG[_ana]->ROI[i]->deltay), r, g, b, 2);
-            _zw->drawLine((int) ANALOG[_ana]->ROI[i]->posx, (int) (ANALOG[_ana]->ROI[i]->posy + ANALOG[_ana]->ROI[i]->deltay/2), (int) ANALOG[_ana]->ROI[i]->posx + ANALOG[_ana]->ROI[i]->deltax, (int) (ANALOG[_ana]->ROI[i]->posy + ANALOG[_ana]->ROI[i]->deltay/2), r, g, b, 2);
-        }
-} 
-
-bool ClassFlowAnalog::doNeuralNetwork(string time)
-{
-    if (disabled)
-        return true;
-
-    string logPath = CreateLogFolder(time);
-    
-    string input = "/sdcard/img_tmp/alg.jpg";
-    string ioresize = "/sdcard/img_tmp/resize.bmp";
-    string output;
-    input = FormatFileName(input);
-
-#ifndef OHNETFLITE
-    CTfLiteClass *tflite = new CTfLiteClass;  
-    string zwcnn = "/sdcard" + cnnmodelfile;
-    zwcnn = FormatFileName(zwcnn);
-    printf(zwcnn.c_str());printf("\n");
-    if (!tflite->LoadModel(zwcnn)) {
-        printf("Can't read model file /sdcard%s\n", cnnmodelfile.c_str());
-        delete tflite;
-        return false;
-    } 
-    tflite->MakeAllocate();
-#endif
-
-    for (int _ana = 0; _ana < ANALOG.size(); ++_ana)
-    {
-        for (int i = 0; i < ANALOG[_ana]->ROI.size(); ++i)
-        {
-            printf("Analog %d - TfLite\n", i);
-
-            float f1, f2;
-            f1 = 0; f2 = 0;
-
-    #ifndef OHNETFLITE
-            tflite->LoadInputImageBasis(ANALOG[_ana]->ROI[i]->image);        
-            tflite->Invoke();
-            if (debugdetailanalog) LogFile.WriteToFile("Nach Invoke");
-
-
-            f1 = tflite->GetOutputValue(0);
-            f2 = tflite->GetOutputValue(1);
-    #endif
-
-            float result = fmod(atan2(f1, f2) / (M_PI * 2) + 2, 1);
-    //        printf("Result sin, cos, ziffer: %f, %f, %f\n", f1, f2, result);  
-            ANALOG[_ana]->ROI[i]->result = result * 10;
-
-            printf("Result Analog%i: %f\n", i, ANALOG[_ana]->ROI[i]->result); 
-
-            if (isLogImage)
-            {
-                LogImage(logPath, ANALOG[_ana]->ROI[i]->name, &ANALOG[_ana]->ROI[i]->result, NULL, time, ANALOG[_ana]->ROI[i]->image_org);
-            }
-        }
-    }
-
-#ifndef OHNETFLITE
-        delete tflite;
-#endif    
-
-    return true;
-}
-
-
-std::vector<HTMLInfo*> ClassFlowAnalog::GetHTMLInfo()
-{
-    std::vector<HTMLInfo*> result;
-
-    for (int _ana = 0; _ana < ANALOG.size(); ++_ana)
-        for (int i = 0; i < ANALOG[_ana]->ROI.size(); ++i)
-        {
-                if (ANALOG[_ana]->name == "default")
-                    ANALOG[_ana]->ROI[i]->image->SaveToFile(FormatFileName("/sdcard/img_tmp/" + ANALOG[_ana]->ROI[i]->name + ".bmp"));
-                else
-                    ANALOG[_ana]->ROI[i]->image->SaveToFile(FormatFileName("/sdcard/img_tmp/" + ANALOG[_ana]->name + "_" + ANALOG[_ana]->ROI[i]->name + ".bmp"));
-
-
-            HTMLInfo *zw = new HTMLInfo;
-            if (ANALOG[_ana]->name == "default")
-            {
-                zw->filename = ANALOG[_ana]->ROI[i]->name + ".bmp";
-                zw->filename_org = ANALOG[_ana]->ROI[i]->name + ".jpg";
-            }
-            else
-            {
-                zw->filename = ANALOG[_ana]->name + "_" + ANALOG[_ana]->ROI[i]->name + ".bmp";
-                zw->filename_org = ANALOG[_ana]->name + "_" + ANALOG[_ana]->ROI[i]->name + ".jpg";
-            }
-
-            zw->val = ANALOG[_ana]->ROI[i]->result;
-            zw->image = ANALOG[_ana]->ROI[i]->image;
-            zw->image_org = ANALOG[_ana]->ROI[i]->image_org;
-
-            result.push_back(zw);
-        }
-
-    return result;
-}
-
-
-
-int ClassFlowAnalog::getAnzahlANALOG()
-{
-    return ANALOG.size();
-}
-
-string ClassFlowAnalog::getNameANALOG(int _analog)
-{
-    if (_analog < ANALOG.size())
-        return ANALOG[_analog]->name;
-
-    return "ANALOG DOES NOT EXIST";
-}
-
-analog* ClassFlowAnalog::GetANALOG(int _analog)
-{
-    if (_analog < ANALOG.size())
-        return ANALOG[_analog];
-
-    return NULL;
-}
-
-
-
-void ClassFlowAnalog::UpdateNameNumbers(std::vector<std::string> *_name_numbers)
-{
-    for (int _dig = 0; _dig < ANALOG.size(); _dig++)
-    {
-        std::string _name = ANALOG[_dig]->name;
-        bool found = false;
-        for (int i = 0; i < (*_name_numbers).size(); ++i)
-        {
-            if ((*_name_numbers)[i] == _name)
-                found = true;
-        }
-        if (!found)
-            (*_name_numbers).push_back(_name);
-    }
-}
-
-
-
-
--- a/code/components/jomjol_flowcontroll/ClassFlowAnalog.h
+++ b/code/components/jomjol_flowcontroll/ClassFlowAnalog.h
@@ -1,65 +0,0 @@
-#pragma once
-#include "ClassFlowImage.h"
-#include "ClassFlowAlignment.h"
-// #include "CTfLiteClass.h"
-
-struct roianalog {
-    int posx, posy, deltax, deltay;
-    float result;
-    CImageBasis *image, *image_org;
-    string name;
-};
-
-struct analog {
-    string name;
-    std::vector<roianalog*> ROI;
-};
-
-
-class ClassFlowAnalog :
-    public ClassFlowImage
-{
-protected:
-//    std::vector<roianalog*> ROI;
-    std::vector<analog*> ANALOG;
-
-    string cnnmodelfile;
-    int modelxsize, modelysize;
-    int ZeigerEval(float zahl, int ziffer_vorgaenger);
-    bool SaveAllFiles;    
-
-
-    ClassFlowAlignment* flowpostalignment;
-
-	void SetInitialParameter(void);   
-
-
-public:
-    bool extendedResolution;
-
-    ClassFlowAnalog(std::vector<ClassFlow*>* lfc);
-
-    bool ReadParameter(FILE* pfile, string& aktparamgraph);
-    bool doFlow(string time);
-    string getHTMLSingleStep(string host);
-    string getReadout(int _analog);   
-
-    void DrawROI(CImageBasis *_zw); 
-
-    bool doNeuralNetwork(string time); 
-    bool doAlignAndCut(string time);
-   	std::vector<HTMLInfo*> GetHTMLInfo();   
-    int AnzahlROIs(int _analog);
-
-    int getAnzahlANALOG();
-    analog* GetANALOG(int _analog);
-    analog* GetANALOG(string _name, bool _create);
-    analog* FindANALOG(string _name_number);    
-    string getNameANALOG(int _analog);     
-
-    void UpdateNameNumbers(std::vector<std::string> *_name_numbers);
-
-
-    string name(){return "ClassFlowAnalog";}; 
-};
-
--- a/code/components/jomjol_flowcontroll/ClassFlowCNNGeneral.cpp
+++ b/code/components/jomjol_flowcontroll/ClassFlowCNNGeneral.cpp
@@ -0,0 +1,665 @@
+#include "ClassFlowCNNGeneral.h"
+
+#include <math.h>
+#include <iomanip> 
+#include <sys/types.h>
+#include <sstream>      // std::stringstream
+
+#include "CTfLiteClass.h"
+#include "ClassLogFile.h"
+
+static const char* TAG = "flow_analog";
+
+bool debugdetailgeneral = false;
+
+ClassFlowCNNGeneral::ClassFlowCNNGeneral(ClassFlowAlignment *_flowalign, t_CNNType _cnntype) : ClassFlowImage(NULL, TAG)
+{
+    string cnnmodelfile = "";
+    modelxsize = 1;
+    modelysize = 1;
+    ListFlowControll = NULL;
+    previousElement = NULL;   
+    SaveAllFiles = false; 
+    disabled = false;
+//    extendedResolution = false;
+    isLogImageSelect = false;
+    CNNType = AutoDetect;
+    CNNType = _cnntype;
+    flowpostalignment = _flowalign;
+}
+
+/*
+int ClassFlowCNNGeneral::AnzahlROIs(int _analog = 0)
+{
+    int zw = GENERAL[_analog]->ROI.size();
+    if (extendedResolution && (CNNType != Digital)) zw++;   // da letzte Ziffer inkl Nachhkomma, es sei denn, das Nachkomma gibt es nicht (Digital)
+    return zw;
+} 
+*/
+
+string ClassFlowCNNGeneral::getReadout(int _analog = 0, bool _extendedResolution = false)
+{
+    string result = "";    
+    if (GENERAL[_analog]->ROI.size() == 0)
+        return result;
+
+    if (CNNType == Analogue)
+    {
+        float zahl = GENERAL[_analog]->ROI[GENERAL[_analog]->ROI.size() - 1]->result_float;
+        int ergebnis_nachkomma = ((int) floor(zahl * 10) + 10) % 10;
+
+        int prev = -1;
+
+        prev = ZeigerEval(GENERAL[_analog]->ROI[GENERAL[_analog]->ROI.size() - 1]->result_float, prev);
+        result = std::to_string(prev);
+
+        if (_extendedResolution && (CNNType != Digital))
+            result = result + std::to_string(ergebnis_nachkomma);
+
+        for (int i = GENERAL[_analog]->ROI.size() - 2; i >= 0; --i)
+        {
+            prev = ZeigerEval(GENERAL[_analog]->ROI[i]->result_float, prev);
+            result = std::to_string(prev) + result;
+        }
+        return result;
+    }
+
+    if (CNNType == Digital)
+    {
+        for (int i = 0; i < GENERAL[_analog]->ROI.size(); ++i)
+        {
+            if (GENERAL[_analog]->ROI[i]->result_klasse >= 10)
+                result = result + "N";
+            else
+                result = result + std::to_string(GENERAL[_analog]->ROI[i]->result_klasse);
+        }
+        return result;
+    }
+
+    if (CNNType == DigitalHyprid)
+    {
+//        int ergebnis_nachkomma = -1;
+        int zif_akt = -1;
+
+        float zahl = GENERAL[_analog]->ROI[GENERAL[_analog]->ROI.size() - 1]->result_float;
+        if (zahl >= 0)       // NaN?
+        {
+            if (_extendedResolution)
+            {
+                int ergebnis_nachkomma = ((int) floor(zahl * 10)) % 10;
+                int ergebnis_vorkomma = ((int) floor(zahl)) % 10;
+
+                result = std::to_string(ergebnis_vorkomma) + std::to_string(ergebnis_nachkomma);
+                zif_akt = ergebnis_vorkomma;
+            }
+            else
+            {
+                zif_akt = ZeigerEvalHybrid(GENERAL[_analog]->ROI[GENERAL[_analog]->ROI.size() - 1]->result_float, -1, -1);
+                result = std::to_string(zif_akt);
+            }
+        }
+        else
+        {
+            result = "N";
+            if (_extendedResolution && (CNNType != Digital))
+                result = "NN";
+        }
+
+        for (int i = GENERAL[_analog]->ROI.size() - 2; i >= 0; --i)
+        {
+            if (GENERAL[_analog]->ROI[i]->result_float >= 0)
+            {
+                zif_akt = ZeigerEvalHybrid(GENERAL[_analog]->ROI[i]->result_float, GENERAL[_analog]->ROI[i+1]->result_float, zif_akt);
+                result = std::to_string(zif_akt) + result;
+            }
+            else
+            {
+                zif_akt = -1;
+                result = "N" + result;
+            }
+        }
+        return result;
+    }
+
+    return result;
+}
+
+int ClassFlowCNNGeneral::ZeigerEvalHybrid(float zahl, float zahl_vorgaenger, int eval_vorgaenger)
+{
+    int ergebnis_nachkomma = ((int) floor(zahl * 10)) % 10;
+//    int ergebnis_vorkomma = ((int) floor(zahl)) % 10;
+
+    if (zahl_vorgaenger < 0)                // keine Vorzahl vorhanden !!! --> Runde die Zahl
+    {
+        if ((ergebnis_nachkomma <= 2) || (ergebnis_nachkomma >= 8))     // Band um die Ziffer --> Runden, da Ziffer im Rahmen Ungenauigkeit erreicht
+            return ((int) round(zahl) + 10) % 10;
+        else
+            return ((int) trunc(zahl) + 10) % 10;
+    }
+
+    if (zahl_vorgaenger > 9.2)              // Ziffernwechsel beginnt
+    {
+        if (eval_vorgaenger == 0)           // Wechsel hat schon stattgefunden
+        {
+            return ((int) round(zahl) + 10) % 10;      // Annahme, dass die neue Zahl schon in der Nähe des Ziels ist
+        }
+        else
+        {
+            if (zahl_vorgaenger <= 9.5)     // Wechsel startet gerade, aber beginnt erst
+            {
+                if ((ergebnis_nachkomma <= 2) || (ergebnis_nachkomma >= 8))     // Band um die Ziffer --> Runden, da Ziffer im Rahmen Ungenauigkeit erreicht
+                    return ((int) round(zahl) + 10) % 10;
+                else
+                    return ((int) trunc(zahl) + 10) % 10;
+            }
+            else
+            {
+                return ((int) trunc(zahl) + 10) % 10;   // Wechsel schon weiter fortgeschritten, d.h. über 2 als Nachkomma
+            }
+        }
+    }
+
+    if ((ergebnis_nachkomma <= 2) || (ergebnis_nachkomma >= 8))     // Band um die Ziffer --> Runden, da Ziffer im Rahmen Ungenauigkeit erreicht
+        return ((int) round(zahl) + 10) % 10;
+
+    return ((int) trunc(zahl) + 10) % 10;
+}
+
+int ClassFlowCNNGeneral::ZeigerEval(float zahl, int ziffer_vorgaenger)
+{
+    int ergebnis_nachkomma = ((int) floor(zahl * 10) + 10) % 10;
+    int ergebnis_vorkomma = ((int) floor(zahl) + 10) % 10;
+    int ergebnis, ergebnis_rating;
+
+    if (ziffer_vorgaenger == -1)
+        return ergebnis_vorkomma % 10;
+
+    ergebnis_rating = ergebnis_nachkomma - ziffer_vorgaenger;
+    if (ergebnis_nachkomma >= 5)
+        ergebnis_rating-=5;
+    else
+        ergebnis_rating+=5;
+    ergebnis = (int) round(zahl);
+    if (ergebnis_rating < 0)
+        ergebnis-=1;
+    if (ergebnis == -1)
+        ergebnis+=10;
+
+    ergebnis = (ergebnis + 10) % 10;
+    return ergebnis;
+}
+
+bool ClassFlowCNNGeneral::ReadParameter(FILE* pfile, string& aktparamgraph)
+{
+    std::vector<string> zerlegt;
+
+    aktparamgraph = trim(aktparamgraph);
+
+    if (aktparamgraph.size() == 0)
+        if (!this->GetNextParagraph(pfile, aktparamgraph))
+            return false;
+
+
+    if ((toUpper(aktparamgraph) != "[ANALOG]") && (toUpper(aktparamgraph) != ";[ANALOG]") 
+        && (toUpper(aktparamgraph) != "[DIGIT]") && (toUpper(aktparamgraph) != ";[DIGIT]")
+        && (toUpper(aktparamgraph) != "[DIGITS]") && (toUpper(aktparamgraph) != ";[DIGITS]")
+        )       // Paragraph passt nicht
+        return false;
+
+
+/*
+    if ((aktparamgraph.compare("[Analog]") != 0) && (aktparamgraph.compare(";[Analog]") != 0) 
+        && (aktparamgraph.compare("[Digit]") != 0) && (aktparamgraph.compare(";[Digit]")))       // Paragraph passt nicht
+        return false;
+*/
+
+    if (aktparamgraph[0] == ';')
+    {
+        disabled = true;
+        while (getNextLine(pfile, &aktparamgraph) && !isNewParagraph(aktparamgraph));
+        printf("[Analog/Digit] is disabled !!!\n");
+        return true;
+    }
+
+
+    while (this->getNextLine(pfile, &aktparamgraph) && !this->isNewParagraph(aktparamgraph))
+    {
+        zerlegt = this->ZerlegeZeile(aktparamgraph);
+        if ((zerlegt[0] == "LogImageLocation") && (zerlegt.size() > 1))
+        {
+            this->LogImageLocation = "/sdcard" + zerlegt[1];
+            this->isLogImage = true;
+        }
+        if ((zerlegt[0] == "LogImageSelect") && (zerlegt.size() > 1))
+        {
+            LogImageSelect = zerlegt[1];
+            isLogImageSelect = true;            
+        }
+
+        if ((toUpper(zerlegt[0]) == "LOGFILERETENTIONINDAYS") && (zerlegt.size() > 1))
+        {
+            this->logfileRetentionInDays = std::stoi(zerlegt[1]);
+        }
+        if ((toUpper(zerlegt[0]) == "MODELTYPE") && (zerlegt.size() > 1))
+        {
+            if (toUpper(zerlegt[1]) == "DIGITHYPRID")
+                CNNType = DigitalHyprid;
+        }
+
+        if ((zerlegt[0] == "Model") && (zerlegt.size() > 1))
+        {
+            this->cnnmodelfile = zerlegt[1];
+        }
+        if ((zerlegt[0] == "ModelInputSize") && (zerlegt.size() > 2))
+        {
+            this->modelxsize = std::stoi(zerlegt[1]);
+            this->modelysize = std::stoi(zerlegt[2]);
+        }
+        if (zerlegt.size() >= 5)
+        {
+            general* _analog = GetGENERAL(zerlegt[0], true);
+            roi* neuroi = _analog->ROI[_analog->ROI.size()-1];
+            neuroi->posx = std::stoi(zerlegt[1]);
+            neuroi->posy = std::stoi(zerlegt[2]);
+            neuroi->deltax = std::stoi(zerlegt[3]);
+            neuroi->deltay = std::stoi(zerlegt[4]);
+            neuroi->result_float = -1;
+            neuroi->image = NULL;
+            neuroi->image_org = NULL;
+        }
+
+        if ((toUpper(zerlegt[0]) == "SAVEALLFILES") && (zerlegt.size() > 1))
+        {
+            if (toUpper(zerlegt[1]) == "TRUE")
+                SaveAllFiles = true;
+        }
+
+/*
+        if ((toUpper(zerlegt[0]) == "EXTENDEDRESOLUTION") && (zerlegt.size() > 1))
+        {
+            if (toUpper(zerlegt[1]) == "TRUE")
+                extendedResolution = true;
+        }
+*/
+    }
+
+
+   for (int _ana = 0; _ana < GENERAL.size(); ++_ana)
+        for (int i = 0; i < GENERAL[_ana]->ROI.size(); ++i)
+        {
+            GENERAL[_ana]->ROI[i]->image = new CImageBasis(modelxsize, modelysize, 3);
+            GENERAL[_ana]->ROI[i]->image_org = new CImageBasis(GENERAL[_ana]->ROI[i]->deltax, GENERAL[_ana]->ROI[i]->deltay, 3);
+        }
+
+    return true;
+}
+
+general* ClassFlowCNNGeneral::FindGENERAL(string _name_number)
+{
+    for (int i = 0; i < GENERAL.size(); ++i)
+        if (GENERAL[i]->name == _name_number)
+            return GENERAL[i];
+    return NULL;
+}
+
+
+
+general* ClassFlowCNNGeneral::GetGENERAL(string _name, bool _create = true)
+{
+    string _analog, _roi;
+    int _pospunkt = _name.find_first_of(".");
+
+    if (_pospunkt > -1)
+    {
+        _analog = _name.substr(0, _pospunkt);
+        _roi = _name.substr(_pospunkt+1, _name.length() - _pospunkt - 1);
+    }
+    else
+    {
+        _analog = "default";
+        _roi = _name;
+    }
+
+    general *_ret = NULL;
+
+    for (int i = 0; i < GENERAL.size(); ++i)
+        if (GENERAL[i]->name == _analog)
+            _ret = GENERAL[i];
+
+    if (!_create)         // nicht gefunden und soll auch nicht erzeugt werden
+        return _ret;
+
+    if (_ret == NULL)
+    {
+        _ret = new general;
+        _ret->name = _analog;
+        GENERAL.push_back(_ret);
+    }
+
+    roi* neuroi = new roi;
+    neuroi->name = _roi;
+    _ret->ROI.push_back(neuroi);
+
+    printf("GetGENERAL - GENERAL %s - roi %s\n", _analog.c_str(), _roi.c_str());
+
+    return _ret;
+}
+
+
+
+string ClassFlowCNNGeneral::getHTMLSingleStep(string host)
+{
+    string result, zw;
+    std::vector<HTMLInfo*> htmlinfo;
+
+    result = "<p>Found ROIs: </p> <p><img src=\"" + host + "/img_tmp/alg_roi.jpg\"></p>\n";
+    result = result + "Analog Pointers: <p> ";
+
+    htmlinfo = GetHTMLInfo();
+    for (int i = 0; i < htmlinfo.size(); ++i)
+    {
+        std::stringstream stream;
+        stream << std::fixed << std::setprecision(1) << htmlinfo[i]->val;
+        zw = stream.str();
+
+        result = result + "<img src=\"" + host + "/img_tmp/" +  htmlinfo[i]->filename + "\"> " + zw;
+        delete htmlinfo[i];
+    }
+    htmlinfo.clear();         
+
+    return result;
+}
+
+
+
+bool ClassFlowCNNGeneral::doFlow(string time)
+{
+    if (disabled)
+      return true;
+
+    if (!doAlignAndCut(time)){
+        return false;
+    };
+
+    if (debugdetailgeneral) LogFile.WriteToFile("ClassFlowCNNGeneral::doFlow nach Alignment");
+
+    doNeuralNetwork(time);
+
+    RemoveOldLogs();
+    return true;
+}
+
+bool ClassFlowCNNGeneral::doAlignAndCut(string time)
+{
+    if (disabled)
+        return true;
+
+    CAlignAndCutImage *caic = flowpostalignment->GetAlignAndCutImage();    
+
+    for (int _ana = 0; _ana < GENERAL.size(); ++_ana)
+        for (int i = 0; i < GENERAL[_ana]->ROI.size(); ++i)
+        {
+            printf("General %d - Align&Cut\n", i);
+            
+            caic->CutAndSave(GENERAL[_ana]->ROI[i]->posx, GENERAL[_ana]->ROI[i]->posy, GENERAL[_ana]->ROI[i]->deltax, GENERAL[_ana]->ROI[i]->deltay, GENERAL[_ana]->ROI[i]->image_org);
+            if (SaveAllFiles)
+            {
+                if (GENERAL[_ana]->name == "default")
+                    GENERAL[_ana]->ROI[i]->image_org->SaveToFile(FormatFileName("/sdcard/img_tmp/" + GENERAL[_ana]->ROI[i]->name + ".jpg"));
+                else
+                    GENERAL[_ana]->ROI[i]->image_org->SaveToFile(FormatFileName("/sdcard/img_tmp/" + GENERAL[_ana]->name + "_" + GENERAL[_ana]->ROI[i]->name + ".jpg"));
+            } 
+
+            GENERAL[_ana]->ROI[i]->image_org->Resize(modelxsize, modelysize, GENERAL[_ana]->ROI[i]->image);
+            if (SaveAllFiles)
+            {
+                if (GENERAL[_ana]->name == "default")
+                    GENERAL[_ana]->ROI[i]->image->SaveToFile(FormatFileName("/sdcard/img_tmp/" + GENERAL[_ana]->ROI[i]->name + ".bmp"));
+                else
+                    GENERAL[_ana]->ROI[i]->image->SaveToFile(FormatFileName("/sdcard/img_tmp/" + GENERAL[_ana]->name + "_" + GENERAL[_ana]->ROI[i]->name + ".bmp"));
+            } 
+        }
+
+    return true;
+} 
+
+void ClassFlowCNNGeneral::DrawROI(CImageBasis *_zw)
+{
+    if (CNNType == Analogue)
+    {
+        int r = 0;
+        int g = 255;
+        int b = 0;
+
+        for (int _ana = 0; _ana < GENERAL.size(); ++_ana)
+            for (int i = 0; i < GENERAL[_ana]->ROI.size(); ++i)
+            {
+                _zw->drawRect(GENERAL[_ana]->ROI[i]->posx, GENERAL[_ana]->ROI[i]->posy, GENERAL[_ana]->ROI[i]->deltax, GENERAL[_ana]->ROI[i]->deltay, r, g, b, 1);
+                _zw->drawCircle((int) (GENERAL[_ana]->ROI[i]->posx + GENERAL[_ana]->ROI[i]->deltax/2), (int)  (GENERAL[_ana]->ROI[i]->posy + GENERAL[_ana]->ROI[i]->deltay/2), (int) (GENERAL[_ana]->ROI[i]->deltax/2), r, g, b, 2);
+                _zw->drawLine((int) (GENERAL[_ana]->ROI[i]->posx + GENERAL[_ana]->ROI[i]->deltax/2), (int) GENERAL[_ana]->ROI[i]->posy, (int) (GENERAL[_ana]->ROI[i]->posx + GENERAL[_ana]->ROI[i]->deltax/2), (int) (GENERAL[_ana]->ROI[i]->posy + GENERAL[_ana]->ROI[i]->deltay), r, g, b, 2);
+                _zw->drawLine((int) GENERAL[_ana]->ROI[i]->posx, (int) (GENERAL[_ana]->ROI[i]->posy + GENERAL[_ana]->ROI[i]->deltay/2), (int) GENERAL[_ana]->ROI[i]->posx + GENERAL[_ana]->ROI[i]->deltax, (int) (GENERAL[_ana]->ROI[i]->posy + GENERAL[_ana]->ROI[i]->deltay/2), r, g, b, 2);
+            }
+    }
+    else
+    {
+        for (int _dig = 0; _dig < GENERAL.size(); ++_dig)
+            for (int i = 0; i < GENERAL[_dig]->ROI.size(); ++i)
+                _zw->drawRect(GENERAL[_dig]->ROI[i]->posx, GENERAL[_dig]->ROI[i]->posy, GENERAL[_dig]->ROI[i]->deltax, GENERAL[_dig]->ROI[i]->deltay, 0, 0, (255 - _dig*100), 2);
+    }
+} 
+
+bool ClassFlowCNNGeneral::doNeuralNetwork(string time)
+{
+    if (disabled)
+        return true;
+
+    string logPath = CreateLogFolder(time);
+
+    CTfLiteClass *tflite = new CTfLiteClass;  
+    string zwcnn = "/sdcard" + cnnmodelfile;
+    zwcnn = FormatFileName(zwcnn);
+    printf(zwcnn.c_str());printf("\n");
+    if (!tflite->LoadModel(zwcnn)) {
+        printf("Can't read model file /sdcard%s\n", cnnmodelfile.c_str());
+        LogFile.WriteToFile("Cannot load model");
+
+        delete tflite;
+        return false;
+    } 
+    tflite->MakeAllocate();
+
+    if (CNNType == AutoDetect)
+    {
+        int _anzoutputdimensions = tflite->GetAnzOutPut();
+        switch (_anzoutputdimensions) 
+        {
+            case 2:
+                CNNType = Analogue;
+                printf("TFlite-Type set to Analogue\n");
+                break;
+            case 11:
+                CNNType = Digital;
+                printf("TFlite-Type set to Digital\n");
+                break;
+            case 22:
+                CNNType = DigitalHyprid;
+                printf("TFlite-Type set to DigitalHyprid\n");
+                break;
+            default:
+                printf("ERROR ERROR ERROR - tflite passt nicht zur Firmware - ERROR ERROR ERROR\n");
+        }
+//        flowpostprocessing->UpdateNachkommaDecimalShift();
+    }
+
+    for (int _ana = 0; _ana < GENERAL.size(); ++_ana)
+    {
+        for (int i = 0; i < GENERAL[_ana]->ROI.size(); ++i)
+        {
+            printf("General %d - TfLite\n", i);
+
+            switch (CNNType) {
+                case Analogue:
+                    {
+                        float f1, f2;
+                        f1 = 0; f2 = 0;
+
+                        tflite->LoadInputImageBasis(GENERAL[_ana]->ROI[i]->image);        
+                        tflite->Invoke();
+                        if (debugdetailgeneral) LogFile.WriteToFile("Nach Invoke");
+
+                        f1 = tflite->GetOutputValue(0);
+                        f2 = tflite->GetOutputValue(1);
+                        float result = fmod(atan2(f1, f2) / (M_PI * 2) + 2, 1);
+                        GENERAL[_ana]->ROI[i]->result_float = result * 10;
+                        printf("Result General(Analog)%i: %f\n", i, GENERAL[_ana]->ROI[i]->result_float); 
+                        if (isLogImage)
+                            LogImage(logPath, GENERAL[_ana]->ROI[i]->name, &GENERAL[_ana]->ROI[i]->result_float, NULL, time, GENERAL[_ana]->ROI[i]->image_org);
+                    } break;
+                case Digital:
+                    {
+                        GENERAL[_ana]->ROI[i]->result_klasse = 0;
+                        GENERAL[_ana]->ROI[i]->result_klasse = tflite->GetClassFromImageBasis(GENERAL[_ana]->ROI[i]->image);
+                        printf("Result General(Digit)%i: %d\n", i, GENERAL[_ana]->ROI[i]->result_klasse);
+
+                        if (isLogImage)
+                        {
+                            if (isLogImageSelect)
+                            {
+                                if (LogImageSelect.find(GENERAL[_ana]->ROI[i]->name) != std::string::npos)
+                                    LogImage(logPath, GENERAL[_ana]->ROI[i]->name, NULL, &GENERAL[_ana]->ROI[i]->result_klasse, time, GENERAL[_ana]->ROI[i]->image_org);
+                            }
+                            else
+                            {
+                                LogImage(logPath, GENERAL[_ana]->ROI[i]->name, NULL, &GENERAL[_ana]->ROI[i]->result_klasse, time, GENERAL[_ana]->ROI[i]->image_org);
+                            }
+                        }
+                    } break;
+                case DigitalHyprid:
+                    {
+                        int _num, _nachkomma;
+
+                        tflite->LoadInputImageBasis(GENERAL[_ana]->ROI[i]->image);        
+                        tflite->Invoke();
+                        if (debugdetailgeneral) LogFile.WriteToFile("Nach Invoke");
+
+                        _num = tflite->GetOutClassification(0, 10);
+                        _nachkomma = tflite->GetOutClassification(11, 21);
+
+
+                        string _zwres = "Nach Invoke - Nummer: " + to_string(_num) + " Nachkomma: " + to_string(_nachkomma);
+                        if (debugdetailgeneral) LogFile.WriteToFile(_zwres);
+
+                        if ((_num == 10) || (_nachkomma == 10))                      // NaN detektiert
+                            GENERAL[_ana]->ROI[i]->result_float = -1;
+                        else
+                            GENERAL[_ana]->ROI[i]->result_float = fmod((double) _num + (((double)_nachkomma)-5)/10 + (double) 10, 10);
+
+                        printf("Result General(DigitalHyprid)%i: %f\n", i, GENERAL[_ana]->ROI[i]->result_float); 
+                        _zwres = "Result General(DigitalHyprid)" + to_string(i) + ": " + to_string(GENERAL[_ana]->ROI[i]->result_float);
+                        if (debugdetailgeneral) LogFile.WriteToFile(_zwres);
+
+                        if (isLogImage)
+                            LogImage(logPath, GENERAL[_ana]->ROI[i]->name, &GENERAL[_ana]->ROI[i]->result_float, NULL, time, GENERAL[_ana]->ROI[i]->image_org);
+                    } break;
+                default:
+                    break;
+            }
+        }
+    }
+
+    delete tflite;
+
+    return true;
+}
+
+bool ClassFlowCNNGeneral::isExtendedResolution(int _number)
+{
+//    if (extendedResolution && !(CNNType == Digital))
+    if (!(CNNType == Digital))
+        return true;
+
+    return false;
+}
+
+
+
+std::vector<HTMLInfo*> ClassFlowCNNGeneral::GetHTMLInfo()
+{
+    std::vector<HTMLInfo*> result;
+
+    for (int _ana = 0; _ana < GENERAL.size(); ++_ana)
+        for (int i = 0; i < GENERAL[_ana]->ROI.size(); ++i)
+        {
+                if (GENERAL[_ana]->name == "default")
+                    GENERAL[_ana]->ROI[i]->image->SaveToFile(FormatFileName("/sdcard/img_tmp/" + GENERAL[_ana]->ROI[i]->name + ".bmp"));
+                else
+                    GENERAL[_ana]->ROI[i]->image->SaveToFile(FormatFileName("/sdcard/img_tmp/" + GENERAL[_ana]->name + "_" + GENERAL[_ana]->ROI[i]->name + ".bmp"));
+
+
+            HTMLInfo *zw = new HTMLInfo;
+            if (GENERAL[_ana]->name == "default")
+            {
+                zw->filename = GENERAL[_ana]->ROI[i]->name + ".bmp";
+                zw->filename_org = GENERAL[_ana]->ROI[i]->name + ".jpg";
+            }
+            else
+            {
+                zw->filename = GENERAL[_ana]->name + "_" + GENERAL[_ana]->ROI[i]->name + ".bmp";
+                zw->filename_org = GENERAL[_ana]->name + "_" + GENERAL[_ana]->ROI[i]->name + ".jpg";
+            }
+
+            if (CNNType == Digital)
+                zw->val = GENERAL[_ana]->ROI[i]->result_klasse;
+            else
+                zw->val = GENERAL[_ana]->ROI[i]->result_float;
+            zw->image = GENERAL[_ana]->ROI[i]->image;
+            zw->image_org = GENERAL[_ana]->ROI[i]->image_org;
+
+//            printf("Push %s\n", zw->filename.c_str());
+
+            result.push_back(zw);
+        }
+
+//    printf("größe: %d\n", result.size());
+
+    return result;
+}
+
+int ClassFlowCNNGeneral::getAnzahlGENERAL()
+{
+    return GENERAL.size();
+}
+
+string ClassFlowCNNGeneral::getNameGENERAL(int _analog)
+{
+    if (_analog < GENERAL.size())
+        return GENERAL[_analog]->name;
+
+    return "GENERAL DOES NOT EXIST";
+}
+
+general* ClassFlowCNNGeneral::GetGENERAL(int _analog)
+{
+    if (_analog < GENERAL.size())
+        return GENERAL[_analog];
+
+    return NULL;
+}
+
+
+
+void ClassFlowCNNGeneral::UpdateNameNumbers(std::vector<std::string> *_name_numbers)
+{
+    for (int _dig = 0; _dig < GENERAL.size(); _dig++)
+    {
+        std::string _name = GENERAL[_dig]->name;
+        bool found = false;
+        for (int i = 0; i < (*_name_numbers).size(); ++i)
+        {
+            if ((*_name_numbers)[i] == _name)
+                found = true;
+        }
+        if (!found)
+            (*_name_numbers).push_back(_name);
+    }
+}
--- a/code/components/jomjol_flowcontroll/ClassFlowCNNGeneral.h
+++ b/code/components/jomjol_flowcontroll/ClassFlowCNNGeneral.h
@@ -0,0 +1,72 @@
+#ifndef __CLASSCNNGENERAL__
+#define __CLASSCNNGENERAL__
+
+#include"ClassFlowDefineTypes.h"
+#include "ClassFlowAlignment.h"
+// #include "ClassFlowPostProcessing.h"
+
+
+enum t_CNNType {
+    AutoDetect,
+    Analogue,
+    Digital,
+    DigitalHyprid,
+    None
+ };
+
+class ClassFlowCNNGeneral :
+    public ClassFlowImage
+{
+protected:
+    t_CNNType CNNType;
+    std::vector<general*> GENERAL;
+
+    string cnnmodelfile;
+    int modelxsize, modelysize;
+    bool isLogImageSelect;
+    string LogImageSelect;
+    ClassFlowAlignment* flowpostalignment;
+//    ClassFlowPostProcessing *flowpostprocessing = NULL;
+    bool SaveAllFiles;   
+//    bool extendedResolution;
+
+    int ZeigerEval(float zahl, int ziffer_vorgaenger);
+    int ZeigerEvalHybrid(float zahl, float zahl_vorgaenger, int eval_vorgaenger);
+
+
+    bool doNeuralNetwork(string time); 
+    bool doAlignAndCut(string time);
+
+public:
+    ClassFlowCNNGeneral(ClassFlowAlignment *_flowalign, t_CNNType _cnntype = AutoDetect);
+
+    bool ReadParameter(FILE* pfile, string& aktparamgraph);
+    bool doFlow(string time);
+
+    string getHTMLSingleStep(string host);
+    string getReadout(int _analog, bool _extendedResolution);   
+
+    void DrawROI(CImageBasis *_zw); 
+
+   	std::vector<HTMLInfo*> GetHTMLInfo();   
+
+//    int AnzahlROIs(int _analog);
+    int getAnzahlGENERAL();
+    general* GetGENERAL(int _analog);
+    general* GetGENERAL(string _name, bool _create);
+    general* FindGENERAL(string _name_number);    
+    string getNameGENERAL(int _analog);    
+
+    bool isExtendedResolution(int _number = 0);
+
+//    void setPostprocessing(ClassFlowPostProcessing *_fpp){flowpostprocessing = _fpp;}; 
+
+    void UpdateNameNumbers(std::vector<std::string> *_name_numbers);
+
+    t_CNNType getCNNType(){return CNNType;};
+
+    string name(){return "ClassFlowCNNGeneral";}; 
+};
+
+#endif
+
--- a/code/components/jomjol_flowcontroll/ClassFlowControll.cpp
+++ b/code/components/jomjol_flowcontroll/ClassFlowControll.cpp
@@ -6,12 +6,23 @@
 #include "freertos/task.h"

 #include <sys/stat.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif
 #include <dirent.h>
+#ifdef __cplusplus
+}
+#endif
+
 #include "ClassLogFile.h"
 #include "time_sntp.h"
 #include "Helper.h"
 #include "server_ota.h"

+
+//#include "CImg.h"
+
 #include "server_help.h"

 //#define DEBUG_DETAIL_ON  
@@ -32,10 +43,10 @@ std::string ClassFlowControll::doSingleStep(std::string _stepname, std::string _
    if ((_stepname.compare(0, 7, "[Digits") == 0) || (_stepname.compare(0, 8, ";[Digits") == 0)) {
 //    if ((_stepname.compare("[Digits]") == 0) || (_stepname.compare(";[Digits]") == 0)){
 //        printf("Digits!!!\n");
-        _classname = "ClassFlowDigit";
+        _classname = "ClassFlowCNNGeneral";
    }
    if ((_stepname.compare("[Analog]") == 0) || (_stepname.compare(";[Analog]") == 0)){
-        _classname = "ClassFlowAnalog";
+        _classname = "ClassFlowCNNGeneral";
    }
    if ((_stepname.compare("[MQTT]") == 0) || (_stepname.compare(";[MQTT]") == 0)){
        _classname = "ClassFlowMQTT";
@@ -51,11 +62,33 @@ std::string ClassFlowControll::doSingleStep(std::string _stepname, std::string _
    return result;
 }

-std::vector<HTMLInfo*> ClassFlowControll::GetAllDigital()
+
+std::string ClassFlowControll::TranslateAktstatus(std::string _input)
 {
-    for (int i = 0; i < FlowControll.size(); ++i)
-        if (FlowControll[i]->name().compare("ClassFlowDigit") == 0)
-            return ((ClassFlowDigit*) (FlowControll[i]))->GetHTMLInfo();
+    if (_input.compare("ClassFlowMakeImage") == 0)
+        return ("Take Image");
+    if (_input.compare("ClassFlowAlignment") == 0)
+        return ("Aligning");
+    //if (_input.compare("ClassFlowAnalog") == 0)
+    //    return ("Analog ROIs");
+    if (_input.compare("ClassFlowCNNGeneral") == 0)
+        return ("Digitalization of ROIs");
+    if (_input.compare("ClassFlowMQTT") == 0)
+        return ("Sending MQTT");
+    if (_input.compare("ClassFlowPostProcessing") == 0)
+        return ("Processing");
+
+    return "Unkown Status";
+}
+
+
+std::vector<HTMLInfo*> ClassFlowControll::GetAllDigital() 
+{
+    if (flowdigit)
+    {
+        printf("ClassFlowControll::GetAllDigital - flowdigit != NULL\n");
+        return flowdigit->GetHTMLInfo();
+    }

    std::vector<HTMLInfo*> empty;
    return empty;
@@ -63,14 +96,43 @@ std::vector<HTMLInfo*> ClassFlowControll::GetAllDigital()

 std::vector<HTMLInfo*> ClassFlowControll::GetAllAnalog()
 {
-    for (int i = 0; i < FlowControll.size(); ++i)
-        if (FlowControll[i]->name().compare("ClassFlowAnalog") == 0)
-            return ((ClassFlowAnalog*) (FlowControll[i]))->GetHTMLInfo();
+    if (flowanalog)
+        return flowanalog->GetHTMLInfo();

    std::vector<HTMLInfo*> empty;
    return empty;
 }

+t_CNNType ClassFlowControll::GetTypeDigital()
+{
+    if (flowdigit)
+        return flowdigit->getCNNType();
+
+    return t_CNNType::None;
+}
+
+t_CNNType ClassFlowControll::GetTypeAnalog()
+{
+    if (flowanalog)
+        return flowanalog->getCNNType();
+
+    return t_CNNType::None;
+}
+
+
+
+
+string ClassFlowControll::GetMQTTMainTopic()
+{
+    for (int i = 0; i < FlowControll.size(); ++i)
+        if (FlowControll[i]->name().compare("ClassFlowMQTT") == 0)
+            return ((ClassFlowMQTT*) (FlowControll[i]))->GetMQTTMainTopic();
+
+
+    return "";
+}
+
+

 void ClassFlowControll::SetInitialParameter(void)
 {
@@ -82,7 +144,7 @@ void ClassFlowControll::SetInitialParameter(void)
    flowpostprocessing = NULL;
    disabled = false;
    aktRunNr = 0;
-    aktstatus = "Startup";
+    aktstatus = "Booting ...";

 }

@@ -110,20 +172,20 @@ ClassFlow* ClassFlowControll::CreateClassFlow(std::string _type)
    }
    if (toUpper(_type).compare("[ANALOG]") == 0)
    {
-        cfc = new ClassFlowAnalog(&FlowControll);
-        flowanalog = (ClassFlowAnalog*) cfc;
+        cfc = new ClassFlowCNNGeneral(flowalignment);
+        flowanalog = (ClassFlowCNNGeneral*) cfc;
    }
    if (toUpper(_type).compare(0, 7, "[DIGITS") == 0)
    {
-        cfc = new ClassFlowDigit(&FlowControll);
-        flowdigit = (ClassFlowDigit*) cfc;
+        cfc = new ClassFlowCNNGeneral(flowalignment);
+        flowdigit = (ClassFlowCNNGeneral*) cfc;
    }
    if (toUpper(_type).compare("[MQTT]") == 0)
        cfc = new ClassFlowMQTT(&FlowControll);
        
    if (toUpper(_type).compare("[POSTPROCESSING]") == 0)
    {
-        cfc = new ClassFlowPostProcessing(&FlowControll); 
+        cfc = new ClassFlowPostProcessing(&FlowControll, flowanalog, flowdigit); 
        flowpostprocessing = (ClassFlowPostProcessing*) cfc;
    }

@@ -168,14 +230,17 @@ void ClassFlowControll::InitFlow(std::string config)
        cfc = CreateClassFlow(line);
        if (cfc)
        {
-            printf("Start ReadParameter\n");
+            printf("Start ReadParameter (%s)\n", line.c_str());
            cfc->ReadParameter(pFile, line);
        }
        else
        {
-            fgets(zw, 1024, pFile);
-            printf("%s", zw);
-            line = std::string(zw);
+            line = "";
+            if (fgets(zw, 1024, pFile) && !feof(pFile))
+                {
+                    printf("Read: %s", zw);
+                    line = std::string(zw);
+                }
        }
    }

@@ -183,8 +248,8 @@ void ClassFlowControll::InitFlow(std::string config)

 }

-std::string ClassFlowControll::getActStatus(){
-    return aktstatus;
+std::string* ClassFlowControll::getActStatus(){
+    return &aktstatus;
 }

 void ClassFlowControll::doFlowMakeImageOnly(string time){
@@ -193,9 +258,9 @@ void ClassFlowControll::doFlowMakeImageOnly(string time){
    for (int i = 0; i < FlowControll.size(); ++i)
    {
        if (FlowControll[i]->name() == "ClassFlowMakeImage") {
-            zw_time = gettimestring("%Y%m%d-%H%M%S");
-            aktstatus = zw_time + ": " + FlowControll[i]->name();
-            string zw = "FlowControll.doFlowMakeImageOnly - " + FlowControll[i]->name();
+//            zw_time = gettimestring("%Y%m%d-%H%M%S");
+            zw_time = gettimestring("%H:%M:%S");
+            aktstatus = TranslateAktstatus(FlowControll[i]->name()) + " (" + zw_time + ")";
            FlowControll[i]->doFlow(time);
        }
    }
@@ -215,8 +280,11 @@ bool ClassFlowControll::doFlow(string time)

    for (int i = 0; i < FlowControll.size(); ++i)
    {
-        zw_time = gettimestring("%Y%m%d-%H%M%S");
-        aktstatus = zw_time + ": " + FlowControll[i]->name();
+        zw_time = gettimestring("%H:%M:%S");
+        aktstatus = TranslateAktstatus(FlowControll[i]->name()) + " (" + zw_time + ")";
+
+//        zw_time = gettimestring("%Y%m%d-%H%M%S");
+//        aktstatus = zw_time + ": " + FlowControll[i]->name();
        
       
        string zw = "FlowControll.doFlow - " + FlowControll[i]->name();
@@ -225,7 +293,7 @@ bool ClassFlowControll::doFlow(string time)
        if (!FlowControll[i]->doFlow(time)){
            repeat++;
            LogFile.WriteToFile("Fehler im vorheriger Schritt - wird zum " + to_string(repeat) + ". Mal wiederholt");
-            i = -1;    // vorheriger Schritt muss wiederholt werden (vermutlich Bilder aufnehmen)
+            if (i) i -= 1;    // vorheriger Schritt muss wiederholt werden (vermutlich Bilder aufnehmen)
            result = false;
            if (repeat > 5) {
                LogFile.WriteToFile("Wiederholung 5x nicht erfolgreich --> reboot");
@@ -243,53 +311,49 @@ bool ClassFlowControll::doFlow(string time)
 #endif

    }
-    zw_time = gettimestring("%Y%m%d-%H%M%S");    
-    aktstatus = zw_time + ": Flow is done";
+    zw_time = gettimestring("%H:%M:%S");
+    aktstatus = "Flow finished (" + zw_time + ")";
    return result;
 }

-void ClassFlowControll::UpdateAktStatus(std::string _flow)
-{
-    aktstatus = gettimestring("%Y%m%d-%H%M%S");
-    aktstatus = aktstatus + "\t" + std::to_string(aktRunNr) + "\t";
-    
-    if (_flow == "ClassFlowMakeImage")
-        aktstatus = aktstatus + "Taking Raw Image";
-    else
-        if (_flow == "ClassFlowAlignment")
-            aktstatus = aktstatus + "Aligning Image";
-
-
-}
-

 string ClassFlowControll::getReadoutAll(int _type)
 {
-    std::vector<NumberPost*> numbers = flowpostprocessing->GetNumbers();
    std::string out = "";
-
-    for (int i = 0; i < numbers.size(); ++i)
+    if (flowpostprocessing)
    {
-        out = out + numbers[i]->name + "\t";
-        switch (_type) {
-            case READOUT_TYPE_VALUE:
-                out = out + numbers[i]->ReturnValue;
-                break;
-            case READOUT_TYPE_PREVALUE:
-                out = out + numbers[i]->ReturnPreValue;
-                break;
-            case READOUT_TYPE_RAWVALUE:
-                out = out + numbers[i]->ReturnRawValue;
-                break;
-            case READOUT_TYPE_ERROR:
-                out = out + numbers[i]->ErrorMessageText;
-                break;
-        }
-        if (i < numbers.size()-1)
-            out = out + "\r\n";
-    }
+        std::vector<NumberPost*> *numbers = flowpostprocessing->GetNumbers();

-//    printf("OUT: %s", out.c_str());
+        for (int i = 0; i < (*numbers).size(); ++i)
+        {
+            out = out + (*numbers)[i]->name + "\t";
+            switch (_type) {
+                case READOUT_TYPE_VALUE:
+                    out = out + (*numbers)[i]->ReturnValueNoError;
+                    break;
+                case READOUT_TYPE_PREVALUE:
+                    if (flowpostprocessing->PreValueUse)
+                    {
+                        if ((*numbers)[i]->PreValueOkay)
+                            out = out + (*numbers)[i]->ReturnPreValue;
+                        else
+                            out = out + "PreValue too old";                
+                    }
+                    else
+                        out = out + "PreValue deactivated";
+                    break;
+                case READOUT_TYPE_RAWVALUE:
+                    out = out + (*numbers)[i]->ReturnRawValue;
+                    break;
+                case READOUT_TYPE_ERROR:
+                    out = out + (*numbers)[i]->ErrorMessageText;
+                    break;
+            }
+            if (i < (*numbers).size()-1)
+                out = out + "\r\n";
+        }
+    //    printf("OUT: %s", out.c_str());
+    }

    return out;
 }	
@@ -328,7 +392,7 @@ string ClassFlowControll::GetPrevalue(std::string _number)
    return std::string();    
 }

-std::string ClassFlowControll::UpdatePrevalue(std::string _newvalue, std::string _numbers)
+std::string ClassFlowControll::UpdatePrevalue(std::string _newvalue, std::string _numbers, bool _extern)
 {
    float zw;
    char* p;
@@ -350,7 +414,7 @@ std::string ClassFlowControll::UpdatePrevalue(std::string _newvalue, std::string

    if (flowpostprocessing)
    {
-        flowpostprocessing->SetPreValue(zw, _numbers);
+        flowpostprocessing->SetPreValue(zw, _numbers, _extern);
        return _newvalue;    
    }

@@ -442,6 +506,7 @@ bool ClassFlowControll::ReadParameter(FILE* pfile, string& aktparamgraph)
    return true;
 }

+
 int ClassFlowControll::CleanTempFolder() {
    const char* folderPath = "/sdcard/img_tmp";
    
@@ -497,53 +562,59 @@ esp_err_t ClassFlowControll::GetJPGStream(std::string _fn, httpd_req_t *req)
    {
        _send = flowalignment->ImageBasis;  
    }
-
-
-
-    if (_fn == "alg_roi.jpg")
+    else
    {
-        CImageBasis* _imgzw = new CImageBasis(flowalignment->ImageBasis);
-        flowalignment->DrawRef(_imgzw);
-        if (flowdigit) flowdigit->DrawROI(_imgzw);
-        if (flowanalog) flowanalog->DrawROI(_imgzw);
-        _send = _imgzw;
-        Dodelete = true;
-    }
+        if (_fn == "alg_roi.jpg")
+        {
+            CImageBasis* _imgzw = new CImageBasis(flowalignment->ImageBasis);
+            flowalignment->DrawRef(_imgzw);
+            if (flowdigit) flowdigit->DrawROI(_imgzw);
+            if (flowanalog) flowanalog->DrawROI(_imgzw);
+            _send = _imgzw;
+            Dodelete = true;
+        }
+        else
+        {
+            std::vector<HTMLInfo*> htmlinfo;
+            htmlinfo = GetAllDigital();
+            for (int i = 0; i < htmlinfo.size(); ++i)
+            {
+                if (_fn == htmlinfo[i]->filename)
+                {
+                    if (htmlinfo[i]->image)
+                        _send = htmlinfo[i]->image;
+                }
+                if (_fn == htmlinfo[i]->filename_org)
+                {
+                    if (htmlinfo[i]->image_org)
+                        _send = htmlinfo[i]->image_org;        
+                }
+                delete htmlinfo[i];
+            }
+            htmlinfo.clear();

-    std::vector<HTMLInfo*> htmlinfo;
-    htmlinfo = GetAllDigital();
-    for (int i = 0; i < htmlinfo.size(); ++i)
-    {
-        if (_fn == htmlinfo[i]->filename)
-        {
-            if (htmlinfo[i]->image)
-                _send = htmlinfo[i]->image;
-        }
-        if (_fn == htmlinfo[i]->filename_org)
-        {
-            if (htmlinfo[i]->image_org)
-                _send = htmlinfo[i]->image_org;        
-        }
-        delete htmlinfo[i];
-    }
-    htmlinfo.clear();
+            if (!_send)
+            {
+                htmlinfo = GetAllAnalog();
+                for (int i = 0; i < htmlinfo.size(); ++i)
+                {
+                    if (_fn == htmlinfo[i]->filename)
+                    {
+                        if (htmlinfo[i]->image)
+                            _send = htmlinfo[i]->image;
+                    }
+                    if (_fn == htmlinfo[i]->filename_org)
+                    {
+                        if (htmlinfo[i]->image_org)
+                            _send = htmlinfo[i]->image_org;        
+                    }
+                    delete htmlinfo[i];
+                }
+                htmlinfo.clear();

-    htmlinfo = GetAllAnalog();
-    for (int i = 0; i < htmlinfo.size(); ++i)
-    {
-        if (_fn == htmlinfo[i]->filename)
-        {
-            if (htmlinfo[i]->image)
-                _send = htmlinfo[i]->image;
+            }
        }
-        if (_fn == htmlinfo[i]->filename_org)
-        {
-            if (htmlinfo[i]->image_org)
-                _send = htmlinfo[i]->image_org;        
-        }
-        delete htmlinfo[i];
    }
-    htmlinfo.clear();

    if (_send)
    {
@@ -561,4 +632,37 @@ esp_err_t ClassFlowControll::GetJPGStream(std::string _fn, httpd_req_t *req)
    }

    return result;
-}
+}
+
+
+string ClassFlowControll::getJSON()
+{
+    std::vector<NumberPost*>* NUMBERS = flowpostprocessing->GetNumbers();
+
+    std::string json="{\n";
+
+    for (int i = 0; i < (*NUMBERS).size(); ++i)
+    {
+        json += "\"" + (*NUMBERS)[i]->name + "\":\n";
+        json += "  {\n";
+        if ((*NUMBERS)[i]->ReturnValueNoError.length() > 0)
+            json += "    \"value\": "      + (*NUMBERS)[i]->ReturnValueNoError          + ",\n";
+        else
+            json += "    \"value\": \"\",\n";
+        json += "    \"raw\": \""        + (*NUMBERS)[i]->ReturnRawValue              + "\",\n";
+        json += "    \"error\": \""     + (*NUMBERS)[i]->ErrorMessageText             + "\",\n";
+        if ((*NUMBERS)[i]->ReturnRateValue.length() > 0)
+            json += "    \"rate\": "      + (*NUMBERS)[i]->ReturnRateValue                + ",\n";
+        else
+            json += "    \"rate\": \"\",\n";
+
+        json += "    \"timestamp\": \"" + (*NUMBERS)[i]->timeStamp                    + "\"\n";
+        if ((i+1) < (*NUMBERS).size())
+            json += "  },\n";
+        else
+            json += "  }\n";
+    }
+    json += "}";
+
+    return json;
+}
--- a/code/components/jomjol_flowcontroll/ClassFlowControll.h
+++ b/code/components/jomjol_flowcontroll/ClassFlowControll.h
@@ -1,14 +1,15 @@
-#pragma once
+#ifndef __FLOWCONTROLL__
+#define __FLOWCONTROLL__

 #include <string>

 #include "ClassFlow.h"
 #include "ClassFlowMakeImage.h"
 #include "ClassFlowAlignment.h"
-#include "ClassFlowDigit.h"
-#include "ClassFlowAnalog.h"
+#include "ClassFlowCNNGeneral.h"
 #include "ClassFlowPostProcessing.h"
 #include "ClassFlowMQTT.h"
+#include "ClassFlowCNNGeneral.h"


 #define READOUT_TYPE_VALUE 0
@@ -24,8 +25,9 @@ protected:
 	std::vector<ClassFlow*> FlowControll;
 	ClassFlowPostProcessing* flowpostprocessing;
 	ClassFlowAlignment* flowalignment;	
-	ClassFlowAnalog* flowanalog;
-	ClassFlowDigit* flowdigit;
+	ClassFlowCNNGeneral* flowanalog;
+	ClassFlowCNNGeneral* flowdigit;
+//	ClassFlowDigit* flowdigit;
 	ClassFlowMakeImage* flowmakeimage;
 	ClassFlow* CreateClassFlow(std::string _type);

@@ -36,8 +38,6 @@ protected:
 	std::string aktstatus;
 	int aktRunNr;

-	void UpdateAktStatus(std::string _flow);
-
 public:
 	void InitFlow(std::string config);
 	bool doFlow(string time);
@@ -45,9 +45,14 @@ public:
 	bool getStatusSetupModus(){return SetupModeActive;};
 	string getReadout(bool _rawvalue, bool _noerror);
 	string getReadoutAll(int _type);	
-	string UpdatePrevalue(std::string _newvalue, std::string _numbers);
+	string UpdatePrevalue(std::string _newvalue, std::string _numbers, bool _extern);
 	string GetPrevalue(std::string _number = "");	
 	bool ReadParameter(FILE* pfile, string& aktparamgraph);	
+	string getJSON();
+
+	string TranslateAktstatus(std::string _input);
+
+	string GetMQTTMainTopic();

 	esp_err_t GetJPGStream(std::string _fn, httpd_req_t *req);
 	esp_err_t SendRawJPG(httpd_req_t *req);
@@ -56,14 +61,19 @@ public:

 	bool isAutoStart(long &_intervall);

-	std::string getActStatus();
+	std::string* getActStatus();

 	std::vector<HTMLInfo*> GetAllDigital();
 	std::vector<HTMLInfo*> GetAllAnalog();	

+	t_CNNType GetTypeDigital();
+	t_CNNType GetTypeAnalog();
+
 	int CleanTempFolder();

 	string name(){return "ClassFlowControll";};
 };

+#endif
+

--- a/code/components/jomjol_flowcontroll/ClassFlowDefineTypes.h
+++ b/code/components/jomjol_flowcontroll/ClassFlowDefineTypes.h
@@ -0,0 +1,53 @@
+#ifndef __CLASSFLOWIMAGE_CLASS__
+#define __CLASSFLOWIMAGE_CLASS__
+
+#include "ClassFlowImage.h"
+
+struct roi {
+    int posx, posy, deltax, deltay;
+    float result_float;
+    int result_klasse;
+    string name;
+    CImageBasis *image, *image_org;
+};
+
+struct general {
+    string name;
+    std::vector<roi*> ROI;
+};
+
+
+struct NumberPost {
+    float MaxRateValue;
+    bool useMaxRateValue;
+    bool ErrorMessage;
+    bool PreValueOkay;
+    bool AllowNegativeRates;
+    bool checkDigitIncreaseConsistency;
+    time_t lastvalue;
+    string timeStamp;
+    float FlowRateAct;          // m3 / min
+    float PreValue;             // letzter Wert, der gut ausgelesen wurde
+    float Value;                // letzer ausgelesener Wert, inkl. Korrekturen
+    string ReturnRateValue;      // RückgabewertRate
+    string ReturnRawValue;      // Rohwert (mit N & führenden 0)    
+    string ReturnValue;         // korrigierter Rückgabewert, ggf. mit Fehlermeldung
+    string ReturnPreValue;  // korrigierter Rückgabewert ohne Fehlermeldung
+    string ReturnValueNoError;
+    string ErrorMessageText;        // Fehlermeldung bei Consistency Check
+    int AnzahlAnalog;
+    int AnzahlDigital;
+    int DecimalShift;
+    int DecimalShiftInitial;
+    int Nachkomma;
+
+    bool isExtendedResolution;
+
+    general *digit_roi;
+    general *analog_roi;
+
+    string name;
+};
+
+#endif
+
--- a/code/components/jomjol_flowcontroll/ClassFlowDigit.cpp
+++ b/code/components/jomjol_flowcontroll/ClassFlowDigit.cpp
@@ -1,420 +0,0 @@
-#include "ClassFlowDigit.h"
-
-
-//#include "CFindTemplate.h"
-//#include "CTfLiteClass.h"
-
-// #define OHNETFLITE
-
-#ifndef OHNETFLITE
-#include "CTfLiteClass.h"
-#endif
-
-// #include "bitmap_image.hpp"
-
-#include "ClassLogFile.h"
-
-static const char* TAG = "flow_digital";
-
-
-void ClassFlowDigit::SetInitialParameter(void)
-{
-    string cnnmodelfile = "";
-    modelxsize = 1;
-    modelysize = 1;
-    ListFlowControll = NULL;
-    previousElement = NULL;    
-    SaveAllFiles = false;
-    disabled = false;
-    DecimalShift = 0;
-    DecimalShiftEnabled = false;
-}    
-
-ClassFlowDigit::ClassFlowDigit() : ClassFlowImage(TAG)
-{
-    SetInitialParameter();
-}
-
-ClassFlowDigit::ClassFlowDigit(std::vector<ClassFlow*>* lfc) : ClassFlowImage(lfc, TAG)
-{
-    SetInitialParameter();
-    ListFlowControll = lfc;
-
-    for (int i = 0; i < ListFlowControll->size(); ++i)
-    {
-        if (((*ListFlowControll)[i])->name().compare("ClassFlowAlignment") == 0)
-        {
-            flowpostalignment = (ClassFlowAlignment*) (*ListFlowControll)[i];
-        }
-    }
-}
-
-ClassFlowDigit::ClassFlowDigit(std::vector<ClassFlow*>* lfc, ClassFlow *_prev) : ClassFlowImage(lfc, _prev, TAG)
-{
-    SetInitialParameter();
-    ListFlowControll = lfc;
-    previousElement = _prev;
-
-    for (int i = 0; i < ListFlowControll->size(); ++i)
-    {
-        if (((*ListFlowControll)[i])->name().compare("ClassFlowAlignment") == 0)
-        {
-            flowpostalignment = (ClassFlowAlignment*) (*ListFlowControll)[i];
-        }
-    }    
-}
-
-string ClassFlowDigit::getReadout(int _digit = 0)
-{
-    string rst = "";
-
-    for (int i = 0; i < DIGIT[_digit]->ROI.size(); ++i)
-    {
-        if (DIGIT[_digit]->ROI[i]->resultklasse == 10)
-            rst = rst + "N";
-        else
-            rst = rst + std::to_string(DIGIT[_digit]->ROI[i]->resultklasse);
-    }
-
-    return rst;
-}
-
-bool ClassFlowDigit::ReadParameter(FILE* pfile, string& aktparamgraph)
-{
-    std::vector<string> zerlegt;
-
-    aktparamgraph = trim(aktparamgraph);
-
-    if (aktparamgraph.size() == 0)
-        if (!this->GetNextParagraph(pfile, aktparamgraph)) 
-            return false;
-
-    printf("aktparamgraph: %s\n", aktparamgraph.c_str());
-
-    if ((aktparamgraph.compare(0, 7, "[Digits") != 0) && (aktparamgraph.compare(0, 8, ";[Digits") != 0))       // Paragraph passt nich zu MakeImage
-        return false;
-
-    int _pospkt = aktparamgraph.find_first_of(".");
-    int _posklammerzu = aktparamgraph.find_first_of("]");
-    if (_pospkt > -1)
-        NameDigit = aktparamgraph.substr(_pospkt+1, _posklammerzu - _pospkt-1);
-    else
-        NameDigit = "";
-    printf("Name Digit: %s\n", NameDigit.c_str());
-
-    if (aktparamgraph[0] == ';')
-    {
-        disabled = true;
-        while (getNextLine(pfile, &aktparamgraph) && !isNewParagraph(aktparamgraph));
-        printf("[Digits] is disabled !!!\n");
-        return true;
-    }
-
-
-    while (getNextLine(pfile, &aktparamgraph) && !isNewParagraph(aktparamgraph))
-    {
-        zerlegt = this->ZerlegeZeile(aktparamgraph);
-        if ((zerlegt[0] == "LogImageLocation") && (zerlegt.size() > 1))
-        {
-            LogImageLocation = "/sdcard" + zerlegt[1];
-            isLogImage = true;            
-        }
-        if ((zerlegt[0] == "Model") && (zerlegt.size() > 1))
-        {
-            cnnmodelfile = zerlegt[1];
-        }
-        if ((zerlegt[0] == "ModelInputSize") && (zerlegt.size() > 2))
-        {
-            modelxsize = std::stoi(zerlegt[1]);
-            modelysize = std::stoi(zerlegt[2]);
-        }
-        if (zerlegt.size() >= 5)
-        {
-            digit* _digit = GetDIGIT(zerlegt[0], true);
-            roi* neuroi = _digit->ROI[_digit->ROI.size()-1];
-            neuroi->posx = std::stoi(zerlegt[1]);
-            neuroi->posy = std::stoi(zerlegt[2]);
-            neuroi->deltax = std::stoi(zerlegt[3]);
-            neuroi->deltay = std::stoi(zerlegt[4]);
-            neuroi->resultklasse = -1;
-            neuroi->image = NULL;
-            neuroi->image_org = NULL;            
-        }
-
-        if ((toUpper(zerlegt[0]) == "SAVEALLFILES") && (zerlegt.size() > 1))
-        {
-            if (toUpper(zerlegt[1]) == "TRUE")
-                SaveAllFiles = true;
-        }
-
-    }
-
-   for (int _dig = 0; _dig < DIGIT.size(); ++_dig)
-        for (int i = 0; i < DIGIT[_dig]->ROI.size(); ++i)
-        {
-            DIGIT[_dig]->ROI[i]->image = new CImageBasis(modelxsize, modelysize, 3);
-            DIGIT[_dig]->ROI[i]->image_org = new CImageBasis(DIGIT[_dig]->ROI[i]->deltax, DIGIT[_dig]->ROI[i]->deltay, 3);
-        }
-
-    return true;
-}
-
-digit* ClassFlowDigit::FindDIGIT(string _name_number)
-{
-    for (int i = 0; i < DIGIT.size(); ++i)
-    {
-        if (DIGIT[i]->name == _name_number)
-            return DIGIT[i];
-    }
-
-    return NULL;
-}
-
-
-digit* ClassFlowDigit::GetDIGIT(string _name, bool _create = true)
-{
-    string _digit, _roi;
-    int _pospunkt = _name.find_first_of(".");
-//    printf("Name: %s, Pospunkt: %d\n", _name.c_str(), _pospunkt);
-    if (_pospunkt > -1)
-    {
-        _digit = _name.substr(0, _pospunkt);
-        _roi = _name.substr(_pospunkt+1, _name.length() - _pospunkt - 1);
-    }
-    else
-    {
-        _digit = "default";
-        _roi = _name;
-    }
-
-    digit *_ret = NULL;
-
-    for (int i = 0; i < DIGIT.size(); ++i)
-    {
-        if (DIGIT[i]->name == _digit)
-            _ret = DIGIT[i];
-    }
-
-    if (!_create)         // nicht gefunden und soll auch nicht erzeugt werden, ggf. geht eine NULL zurück
-        return _ret;
-
-    if (_ret == NULL)
-    {
-        _ret = new digit;
-        _ret->name = _digit;
-        DIGIT.push_back(_ret);
-    }
-
-    roi* neuroi = new roi;
-    neuroi->name = _roi;
-    _ret->ROI.push_back(neuroi);
-
-    printf("GetDIGIT - digit %s - roi %s\n", _digit.c_str(), _roi.c_str());
-
-    return _ret;
-}
-
-
-
-string ClassFlowDigit::getHTMLSingleStep(string host)
-{
-    string result, zw;
-    std::vector<HTMLInfo*> htmlinfo;
-
-    result = "<p>Found ROIs: </p> <p><img src=\"" + host + "/img_tmp/alg_roi.jpg\"></p>\n";
-    result = result + "Digital Counter: <p> ";
-
-    htmlinfo = GetHTMLInfo();
-    for (int i = 0; i < htmlinfo.size(); ++i)
-    {
-        if (htmlinfo[i]->val == 10)
-            zw = "NaN";
-        else
-        {
-            zw = to_string((int) htmlinfo[i]->val);
-        }
-        result = result + "<img src=\"" + host + "/img_tmp/" +  htmlinfo[i]->filename + "\"> " + zw;
-        delete htmlinfo[i];
-    }
-    htmlinfo.clear();    
-
-    return result;
-}
-
-
-bool ClassFlowDigit::doFlow(string time)
-{
-    if (disabled)
-        return true;
-        
-    if (!doAlignAndCut(time)){
-        return false;
-    };
-
-    doNeuralNetwork(time);
-
-    RemoveOldLogs();
-
-    return true;
-}
-
-bool ClassFlowDigit::doAlignAndCut(string time)
-{
-    if (disabled)
-        return true;
-
-    CAlignAndCutImage *caic = flowpostalignment->GetAlignAndCutImage();
-
-    for (int _dig = 0; _dig < DIGIT.size(); ++_dig)
-    {
-        printf("DIGIT[_dig]->ROI.size() %d\n", DIGIT[_dig]->ROI.size());
-        for (int i = 0; i < DIGIT[_dig]->ROI.size(); ++i)
-        {
-            printf("DigitalDigit %d - Align&Cut\n", i);
-            
-            caic->CutAndSave(DIGIT[_dig]->ROI[i]->posx, DIGIT[_dig]->ROI[i]->posy, DIGIT[_dig]->ROI[i]->deltax, DIGIT[_dig]->ROI[i]->deltay, DIGIT[_dig]->ROI[i]->image_org);
-            if (SaveAllFiles)
-            {
-                if (DIGIT[_dig]->name == "default")
-                    DIGIT[_dig]->ROI[i]->image_org->SaveToFile(FormatFileName("/sdcard/img_tmp/" + DIGIT[_dig]->ROI[i]->name + ".jpg"));
-                else
-                    DIGIT[_dig]->ROI[i]->image_org->SaveToFile(FormatFileName("/sdcard/img_tmp/" + DIGIT[_dig]->name + "_" + DIGIT[_dig]->ROI[i]->name + ".jpg"));
-            } 
-
-            DIGIT[_dig]->ROI[i]->image_org->Resize(modelxsize, modelysize, DIGIT[_dig]->ROI[i]->image);
-            if (SaveAllFiles)
-            {
-                if (DIGIT[_dig]->name == "default")
-                    DIGIT[_dig]->ROI[i]->image->SaveToFile(FormatFileName("/sdcard/img_tmp/" + DIGIT[_dig]->ROI[i]->name + ".bmp"));
-                else
-                    DIGIT[_dig]->ROI[i]->image->SaveToFile(FormatFileName("/sdcard/img_tmp/" + DIGIT[_dig]->name + "_" + DIGIT[_dig]->ROI[i]->name + ".bmp"));
-            } 
-        }
-    }
-    return true;
-} 
-
-bool ClassFlowDigit::doNeuralNetwork(string time)
-{
-    if (disabled)
-        return true;
-            
-    string logPath = CreateLogFolder(time);
-
-#ifndef OHNETFLITE
-    CTfLiteClass *tflite = new CTfLiteClass;  
-    string zwcnn =  FormatFileName("/sdcard" + cnnmodelfile);
-    printf(zwcnn.c_str());printf("\n");
-    if (!tflite->LoadModel(zwcnn)) {
-        printf("Can't read model file /sdcard%s\n", cnnmodelfile.c_str());
-        delete tflite;
-        return false;
-    } 
-
-    tflite->MakeAllocate();
-#endif
-
-    for (int _dig = 0; _dig < DIGIT.size(); ++_dig)
-        for (int i = 0; i < DIGIT[_dig]->ROI.size(); ++i)
-        {
-            printf("DigitalDigit %d - TfLite\n", i);
-
-            DIGIT[_dig]->ROI[i]->resultklasse = 0;
-    #ifndef OHNETFLITE
-            DIGIT[_dig]->ROI[i]->resultklasse = tflite->GetClassFromImageBasis(DIGIT[_dig]->ROI[i]->image);
-
-    #endif
-            printf("Result Digit%i: %d\n", i, DIGIT[_dig]->ROI[i]->resultklasse);
-
-            if (isLogImage)
-            {
-                LogImage(logPath, DIGIT[_dig]->ROI[i]->name, NULL, &DIGIT[_dig]->ROI[i]->resultklasse, time, DIGIT[_dig]->ROI[i]->image_org);
-            }
-        }
-#ifndef OHNETFLITE
-        delete tflite;
-#endif
-    return true;
-}
-
-void ClassFlowDigit::DrawROI(CImageBasis *_zw)
-{
-    for (int _dig = 0; _dig < DIGIT.size(); ++_dig)
-        for (int i = 0; i < DIGIT[_dig]->ROI.size(); ++i)
-            _zw->drawRect(DIGIT[_dig]->ROI[i]->posx, DIGIT[_dig]->ROI[i]->posy, DIGIT[_dig]->ROI[i]->deltax, DIGIT[_dig]->ROI[i]->deltay, 0, 0, (255 - _dig*100), 2);
-}     
-
-std::vector<HTMLInfo*> ClassFlowDigit::GetHTMLInfo()
-{
-    std::vector<HTMLInfo*> result;
-
-    for (int _dig = 0; _dig < DIGIT.size(); ++_dig)
-        for (int i = 0; i < DIGIT[_dig]->ROI.size(); ++i)
-        {
-                if (DIGIT[_dig]->name == "default")
-                    DIGIT[_dig]->ROI[i]->image->SaveToFile(FormatFileName("/sdcard/img_tmp/" + DIGIT[_dig]->ROI[i]->name + ".bmp"));
-                else
-                    DIGIT[_dig]->ROI[i]->image->SaveToFile(FormatFileName("/sdcard/img_tmp/" + DIGIT[_dig]->name + "_" + DIGIT[_dig]->ROI[i]->name + ".bmp"));
-
-
-            HTMLInfo *zw = new HTMLInfo;
-            if (DIGIT[_dig]->name == "default")
-            {
-                zw->filename = DIGIT[_dig]->ROI[i]->name + ".bmp";
-                zw->filename_org = DIGIT[_dig]->ROI[i]->name + ".jpg";
-            }
-            else
-            {
-                zw->filename = DIGIT[_dig]->name + "_" + DIGIT[_dig]->ROI[i]->name + ".bmp";
-                zw->filename_org = DIGIT[_dig]->name + "_" + DIGIT[_dig]->ROI[i]->name + ".jpg";
-            }
-
-            zw->val = DIGIT[_dig]->ROI[i]->resultklasse;
-            zw->image = DIGIT[_dig]->ROI[i]->image;
-            zw->image_org = DIGIT[_dig]->ROI[i]->image_org;
-            result.push_back(zw);
-        }
-
-    return result;
-}
-
-int ClassFlowDigit::getAnzahlDIGIT()
-{
-    return DIGIT.size();
-}
-
-string ClassFlowDigit::getNameDIGIT(int _digit)
-{
-    if (_digit < DIGIT.size())
-        return DIGIT[_digit]->name;
-
-    return "DIGIT DOES NOT EXIST";
-}
-
-digit* ClassFlowDigit::GetDIGIT(int _digit)
-{
-    if (_digit < DIGIT.size())
-        return DIGIT[_digit];
-
-    return NULL;
-}
-
-void ClassFlowDigit::UpdateNameNumbers(std::vector<std::string> *_name_numbers)
-{
-    for (int _dig = 0; _dig < DIGIT.size(); _dig++)
-    {
-        std::string _name = DIGIT[_dig]->name;
-        bool found = false;
-        for (int i = 0; i < (*_name_numbers).size(); ++i)
-        {
-            if ((*_name_numbers)[i] == _name)
-                found = true;
-        }
-        if (!found)
-            (*_name_numbers).push_back(_name);
-    }
-}
-
-
-
-
--- a/code/components/jomjol_flowcontroll/ClassFlowDigit.h
+++ b/code/components/jomjol_flowcontroll/ClassFlowDigit.h
@@ -1,68 +0,0 @@
-#pragma once
-#include "ClassFlowImage.h"
-#include "ClassFlowAlignment.h"
-#include "Helper.h"
-
-#include <string>
-
-
-
-struct roi {
-    int posx, posy, deltax, deltay;
-    int resultklasse;
-    string name;
-    CImageBasis *image, *image_org;
-    roi* next;
-};
-
-struct digit {
-    string name;
-    std::vector<roi*> ROI;
-};
-
-class ClassFlowDigit :
-    public ClassFlowImage
-{
-protected:
-//    std::vector<roi*> ROI;
-    std::vector<digit*> DIGIT;
-    string cnnmodelfile;
-    int modelxsize, modelysize;
-    bool SaveAllFiles;
-    string NameDigit;
-    int DecimalShift;
-    bool DecimalShiftEnabled;
-
-
-    ClassFlowAlignment* flowpostalignment;
- 
-    bool doNeuralNetwork(string time); 
-    bool doAlignAndCut(string time); 
-
-
-	void SetInitialParameter(void);    
-
-public:
-    ClassFlowDigit();
-    ClassFlowDigit(std::vector<ClassFlow*>* lfc);
-    ClassFlowDigit(std::vector<ClassFlow*>* lfc, ClassFlow *_prev);
-    bool ReadParameter(FILE* pfile, string& aktparamgraph);
-    bool doFlow(string time);
-    string getHTMLSingleStep(string host); 
-    string getReadout(int _digit);
-   	std::vector<HTMLInfo*> GetHTMLInfo();
-
-    int getAnzahlDIGIT();
-    digit* GetDIGIT(int _digit);
-    digit* GetDIGIT(string _name, bool _create);
-    digit* FindDIGIT(string _name_number);
-
-    string getNameDIGIT(int _digit);
-
-    void UpdateNameNumbers(std::vector<std::string> *_name_numbers);
-
-    void DrawROI(CImageBasis *_zw);        
-
-    string name(){return "ClassFlowDigit";};
-};
-
--- a/code/components/jomjol_flowcontroll/ClassFlowImage.cpp
+++ b/code/components/jomjol_flowcontroll/ClassFlowImage.cpp
@@ -2,7 +2,15 @@
 #include <string>
 #include <string.h>
 #include <sys/stat.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif
 #include <dirent.h>
+#ifdef __cplusplus
+}
+#endif
+
 #include "time_sntp.h"
 #include "ClassLogFile.h"
 #include "CImageBasis.h"
@@ -48,9 +56,14 @@ void ClassFlowImage::LogImage(string logPath, string name, float *resultFloat, i
 	if (!isLogImage)
 		return;
 	
+    
 	char buf[10];
+
 	if (resultFloat != NULL) {
-		sprintf(buf, "%.1f_", *resultFloat);
+        if (*resultFloat < 0)
+            sprintf(buf, "N.N_");
+        else
+            sprintf(buf, "%.1f_", *resultFloat);
 	} else if (resultInt != NULL) {
 		sprintf(buf, "%d_", *resultInt);
 	} else {
--- a/code/components/jomjol_flowcontroll/ClassFlowMQTT.cpp
+++ b/code/components/jomjol_flowcontroll/ClassFlowMQTT.cpp
@@ -122,6 +122,12 @@ bool ClassFlowMQTT::ReadParameter(FILE* pfile, string& aktparamgraph)
 }


+string ClassFlowMQTT::GetMQTTMainTopic()
+{
+    return maintopic;
+}
+
+
 bool ClassFlowMQTT::doFlow(string zwtime)
 {
    if (!MQTTenable)
@@ -129,6 +135,7 @@ bool ClassFlowMQTT::doFlow(string zwtime)

    std::string result;
    std::string resulterror = "";
+    std::string resultraw = "";
    std::string resultrate = "";
    std::string resulttimestamp = "";
    string zw = "";
@@ -148,37 +155,56 @@ bool ClassFlowMQTT::doFlow(string zwtime)

    if (flowpostprocessing)
    {
-        std::vector<NumberPost*> NUMBERS = flowpostprocessing->GetNumbers();
+        std::vector<NumberPost*>* NUMBERS = flowpostprocessing->GetNumbers();

-        for (int i = 0; i < NUMBERS.size(); ++i)
+        for (int i = 0; i < (*NUMBERS).size(); ++i)
        {
-            result =  NUMBERS[i]->ReturnValueNoError;
-            resulterror = NUMBERS[i]->ErrorMessageText;
-            resultrate = std::to_string(NUMBERS[i]->FlowRateAct);
-            resulttimestamp = NUMBERS[i]->timeStamp;
+            result =  (*NUMBERS)[i]->ReturnValueNoError;
+            resultraw =  (*NUMBERS)[i]->ReturnRawValue;
+            resulterror = (*NUMBERS)[i]->ErrorMessageText;
+            resultrate = (*NUMBERS)[i]->ReturnRateValue;
+            resulttimestamp = (*NUMBERS)[i]->timeStamp;

-            namenumber = NUMBERS[i]->name;
+            namenumber = (*NUMBERS)[i]->name;
            if (namenumber == "default")
                namenumber = maintopic + "/";
            else
                namenumber = maintopic + "/" + namenumber + "/";

-            zw = namenumber + "value";    
-            MQTTPublish(zw, result);
+            zw = namenumber + "value"; 
+            if (result.length() > 0)   
+                MQTTPublish(zw, result);

-            zw = namenumber + "error";    
-            MQTTPublish(zw, resulterror, 1);
+            zw = namenumber + "error"; 
+            if (resulterror.length() > 0)  
+                MQTTPublish(zw, resulterror, 1);

-            zw = namenumber + "rate";    
-            MQTTPublish(zw, resultrate);
+            zw = namenumber + "rate"; 
+            if (resultrate.length() > 0)   
+                MQTTPublish(zw, resultrate);
+
+            zw = namenumber + "raw"; 
+            if (resultraw.length() > 0)   
+                MQTTPublish(zw, resultraw);

            zw = namenumber + "timestamp";
-            MQTTPublish(zw, resulttimestamp);
+            if (resulttimestamp.length() > 0)
+                MQTTPublish(zw, resulttimestamp);


-            std::string json="{\"value\":"+result;
-            json += ",\"error\":\""+resulterror;
-            json += "\",\"rate\":"+resultrate;
+            std::string json = "";
+            
+            if (result.length() > 0)
+                json += "{\"value\":"+result;
+            else
+                json += "{\"value\":\"\"";
+
+            json += ",\"raw\":\""+resultraw;
+            json += "\",\"error\":\""+resulterror;
+            if (resultrate.length() > 0)
+                json += "\",\"rate\":"+resultrate;
+            else
+                json += "\",\"rate\":\"\"";
            json += ",\"timestamp\":\""+resulttimestamp+"\"}";

            zw = namenumber + "json";
--- a/code/components/jomjol_flowcontroll/ClassFlowMQTT.h
+++ b/code/components/jomjol_flowcontroll/ClassFlowMQTT.h
@@ -23,6 +23,8 @@ public:
    ClassFlowMQTT(std::vector<ClassFlow*>* lfc);
    ClassFlowMQTT(std::vector<ClassFlow*>* lfc, ClassFlow *_prev);

+    string GetMQTTMainTopic();
+
    bool ReadParameter(FILE* pfile, string& aktparamgraph);
    bool doFlow(string time);
    string name(){return "ClassFlowMQTT";};
--- a/code/components/jomjol_flowcontroll/ClassFlowPostProcessing.cpp
+++ b/code/components/jomjol_flowcontroll/ClassFlowPostProcessing.cpp
@@ -1,5 +1,4 @@
 #include "ClassFlowPostProcessing.h"
-
 #include "Helper.h"
 #include "ClassFlowMakeImage.h"
 #include "ClassLogFile.h"
@@ -28,21 +27,27 @@ string ClassFlowPostProcessing::GetPreValue(std::string _number)
        if (NUMBERS[i]->name == _number)
            index = i;

-//    result = RundeOutput(NUMBERS[index]->PreValue, -NUMBERS[index]->DecimalShift);
    result = RundeOutput(NUMBERS[index]->PreValue, NUMBERS[index]->Nachkomma);

-//    if (NUMBERS[index]->digit_roi && NUMBERS[index]->analog_roi)
-//        result = RundeOutput(NUMBERS[index]->PreValue, NUMBERS[index]->AnzahlAnalog - NUMBERS[index]->DecimalShift);
-
    return result;
 }

-void ClassFlowPostProcessing::SetPreValue(float zw, string _numbers)
+void ClassFlowPostProcessing::SetPreValue(float zw, string _numbers, bool _extern)
 {
+    printf("SetPrevalue: %f, %s\n", zw, _numbers.c_str());
    for (int j = 0; j < NUMBERS.size(); ++j)
    {
+//        printf("Number %d, %s\n", j, NUMBERS[j]->name.c_str());
        if (NUMBERS[j]->name == _numbers)
+        {
            NUMBERS[j]->PreValue = zw;
+            if (_extern)
+            {
+                time(&(NUMBERS[j]->lastvalue));
+                localtime(&(NUMBERS[j]->lastvalue));
+            }
+//            printf("Found %d! - set to %f\n", j,  NUMBERS[j]->PreValue);
+        }
    }
    UpdatePreValueINI = true;
    SavePreValue();
@@ -84,7 +89,7 @@ bool ClassFlowPostProcessing::LoadPreValue(void)
                if (NUMBERS[j]->name == name)
                {
                    NUMBERS[j]->PreValue = stof(zwvalue.c_str());
-                    NUMBERS[j]->ReturnPreValue = RundeOutput(NUMBERS[j]->PreValue, NUMBERS[j]->Nachkomma);
+                    NUMBERS[j]->ReturnPreValue = RundeOutput(NUMBERS[j]->PreValue, NUMBERS[j]->Nachkomma + 1);      // SIcherheitshalber 1 Stelle mehr, da ggf. Exgtended Resolution an ist (wird erst beim ersten Durchlauf gesetzt)

                    time_t tStart;
                    int yy, month, dd, hh, mm, ss;
@@ -112,15 +117,17 @@ bool ClassFlowPostProcessing::LoadPreValue(void)
                    else
                    {
                        NUMBERS[j]->PreValueOkay = true;
+/*
                        NUMBERS[j]->Value = NUMBERS[j]->PreValue;
                        NUMBERS[j]->ReturnValue = to_string(NUMBERS[j]->Value);
                        NUMBERS[j]->ReturnValueNoError = NUMBERS[j]->ReturnValue; 

                        if (NUMBERS[j]->digit_roi || NUMBERS[j]->analog_roi)
                        {
-                            NUMBERS[j]->ReturnValue = RundeOutput(NUMBERS[j]->Value, NUMBERS[j]->AnzahlAnalog - NUMBERS[j]->DecimalShift);
+                            NUMBERS[j]->ReturnValue = RundeOutput(NUMBERS[j]->Value, NUMBERS[j]->Nachkomma + 1);  // SIcherheitshalber 1 Stelle mehr, da ggf. Exgtended Resolution an ist (wird erst beim ersten Durchlauf gesetzt)
                            NUMBERS[j]->ReturnValueNoError = NUMBERS[j]->ReturnValue;
                        }
+*/
                    }

                }
@@ -180,7 +187,7 @@ bool ClassFlowPostProcessing::LoadPreValue(void)

        if (NUMBERS[0]->digit_roi || NUMBERS[0]->analog_roi)
        {
-            NUMBERS[0]->ReturnValue = RundeOutput(NUMBERS[0]->Value, NUMBERS[0]->AnzahlAnalog - NUMBERS[0]->DecimalShift);
+            NUMBERS[0]->ReturnValue = RundeOutput(NUMBERS[0]->Value, NUMBERS[0]->Nachkomma);
            NUMBERS[0]->ReturnValueNoError = NUMBERS[0]->ReturnValue;
        }

@@ -207,8 +214,9 @@ void ClassFlowPostProcessing::SavePreValue()
        struct tm* timeinfo = localtime(&NUMBERS[j]->lastvalue);
        strftime(buffer, 80, PREVALUE_TIME_FORMAT_OUTPUT, timeinfo);
        NUMBERS[j]->timeStamp = std::string(buffer);
+//        printf("SaverPreValue %d, Value: %f, Nachkomma %d\n", j, NUMBERS[j]->PreValue, NUMBERS[j]->Nachkomma);

-        _zw = NUMBERS[j]->name + "\t" + NUMBERS[j]->timeStamp + "\t" + RundeOutput(NUMBERS[j]->Value, NUMBERS[j]->Nachkomma) + "\n";
+        _zw = NUMBERS[j]->name + "\t" + NUMBERS[j]->timeStamp + "\t" + RundeOutput(NUMBERS[j]->PreValue, NUMBERS[j]->Nachkomma) + "\n";
        printf("Write PreValue Zeile: %s\n", _zw.c_str());

        fputs(_zw.c_str(), pFile);
@@ -220,21 +228,19 @@ void ClassFlowPostProcessing::SavePreValue()
 }


-ClassFlowPostProcessing::ClassFlowPostProcessing(std::vector<ClassFlow*>* lfc)
+ClassFlowPostProcessing::ClassFlowPostProcessing(std::vector<ClassFlow*>* lfc, ClassFlowCNNGeneral *_analog, ClassFlowCNNGeneral *_digit)
 {
-//    FlowRateAct = 0;
    PreValueUse = false;
    PreValueAgeStartup = 30;
    ErrorMessage = false;
    ListFlowControll = NULL;
-//    PreValueOkay = false;
-//    DecimalShift = 0;    
-//    ErrorMessageText = "";
-//    timeStamp = "";
    FilePreValue = FormatFileName("/sdcard/config/prevalue.ini");
    ListFlowControll = lfc;
    flowMakeImage = NULL;
    UpdatePreValueINI = false;
+    IgnoreLeadingNaN = false;
+    flowAnalog = _analog;
+    flowDigit = _digit;

    for (int i = 0; i < ListFlowControll->size(); ++i)
    {
@@ -245,6 +251,36 @@ ClassFlowPostProcessing::ClassFlowPostProcessing(std::vector<ClassFlow*>* lfc)
    }
 }

+void ClassFlowPostProcessing::handleDecimalExtendedResolution(string _decsep, string _value)
+{
+    string _digit, _decpos;
+    int _pospunkt = _decsep.find_first_of(".");
+//    printf("Name: %s, Pospunkt: %d\n", _decsep.c_str(), _pospunkt);
+    if (_pospunkt > -1)
+        _digit = _decsep.substr(0, _pospunkt);
+    else
+        _digit = "default";
+
+    for (int j = 0; j < NUMBERS.size(); ++j)
+    {
+        bool _zwdc = false;
+
+        if (toUpper(_value) == "TRUE")
+            _zwdc = true;
+     
+        if (_digit == "default")                        // erstmal auf default setzen (falls sonst nichts gesetzt)
+        {
+            NUMBERS[j]->isExtendedResolution = _zwdc;
+        }
+
+        if (NUMBERS[j]->name == _digit)
+        {
+            NUMBERS[j]->isExtendedResolution = _zwdc;
+        }
+    }
+}
+
+
 void ClassFlowPostProcessing::handleDecimalSeparator(string _decsep, string _value)
 {
    string _digit, _decpos;
@@ -259,20 +295,26 @@ void ClassFlowPostProcessing::handleDecimalSeparator(string _decsep, string _val
    {
        int _zwdc = 0;

-        try
+//        try
        {
            _zwdc = stoi(_value);
        }
-        catch(const std::exception& e)
+/*        catch(const std::exception& e)
        {
            printf("ERROR - Decimalshift is not a number: %s\n", _value.c_str());
        }
-        
+*/        
        if (_digit == "default")                        // erstmal auf default setzen (falls sonst nichts gesetzt)
+        {
            NUMBERS[j]->DecimalShift = _zwdc;
+            NUMBERS[j]->DecimalShiftInitial = _zwdc;
+        }

        if (NUMBERS[j]->name == _digit)
+        {
            NUMBERS[j]->DecimalShift = _zwdc;
+            NUMBERS[j]->DecimalShiftInitial = _zwdc;
+        }

        NUMBERS[j]->Nachkomma = NUMBERS[j]->AnzahlAnalog - NUMBERS[j]->DecimalShift;
    }
@@ -292,15 +334,15 @@ void ClassFlowPostProcessing::handleMaxRateValue(string _decsep, string _value)
    {
        float _zwdc = 1;

-        try
+//        try
        {
            _zwdc = stof(_value);
        }
-        catch(const std::exception& e)
+/*        catch(const std::exception& e)
        {
            printf("ERROR - MaxRateValue is not a number: %s\n", _value.c_str());
        }
-
+*/

        if (_digit == "default")                        // erstmal auf default setzen (falls sonst nichts gesetzt)
        {
@@ -340,6 +382,11 @@ bool ClassFlowPostProcessing::ReadParameter(FILE* pfile, string& aktparamgraph)
        zerlegt = this->ZerlegeZeile(aktparamgraph);
        std::string _param = GetParameterName(zerlegt[0]);

+        if ((toUpper(_param) == "EXTENDEDRESOLUTION") && (zerlegt.size() > 1))
+        {
+            handleDecimalExtendedResolution(zerlegt[0], zerlegt[1]);
+        }
+
        if ((toUpper(_param) == "DECIMALSHIFT") && (zerlegt.size() > 1))
        {
            handleDecimalSeparator(zerlegt[0], zerlegt[1]);
@@ -373,6 +420,13 @@ bool ClassFlowPostProcessing::ReadParameter(FILE* pfile, string& aktparamgraph)
            if (toUpper(zerlegt[1]) == "TRUE")
                ErrorMessage = true;
        }
+        if ((toUpper(_param) == "IGNORELEADINGNAN") && (zerlegt.size() > 1))
+        {
+            if (toUpper(zerlegt[1]) == "TRUE")
+                IgnoreLeadingNaN = true;
+        }
+
+        
        if ((toUpper(_param) == "PREVALUEAGESTARTUP") && (zerlegt.size() > 1))
        {
            PreValueAgeStartup = std::stoi(zerlegt[1]);
@@ -388,33 +442,20 @@ bool ClassFlowPostProcessing::ReadParameter(FILE* pfile, string& aktparamgraph)

 void ClassFlowPostProcessing::InitNUMBERS()
 {
-//    ClassFlowDigit* _cdigit = NULL;
-//    ClassFlowAnalog* _canalog = NULL;
    int anzDIGIT = 0;
    int anzANALOG = 0;
    std::vector<std::string> name_numbers;

-    flowAnalog = NULL;
-    flowDigit = NULL;
-
-    for (int i = 0; i < ListFlowControll->size(); ++i)
-    {
-        if (((*ListFlowControll)[i])->name().compare("ClassFlowDigit") == 0)
-        {
-            flowDigit = (ClassFlowDigit*) (*ListFlowControll)[i];
-            anzDIGIT = flowDigit->getAnzahlDIGIT();
-        }
-        if (((*ListFlowControll)[i])->name().compare("ClassFlowAnalog") == 0)
-        {
-            flowAnalog = (ClassFlowAnalog*)(*ListFlowControll)[i];
-            anzANALOG = flowAnalog->getAnzahlANALOG();
-        }
-    }
-
    if (flowDigit)
+    {
+        anzDIGIT = flowDigit->getAnzahlGENERAL();
        flowDigit->UpdateNameNumbers(&name_numbers);
+    }
    if (flowAnalog)
+    {
+        anzANALOG = flowAnalog->getAnzahlGENERAL();
        flowAnalog->UpdateNameNumbers(&name_numbers);
+    }

    printf("Anzahl NUMBERS: %d - DIGITS: %d, ANALOG: %d\n", name_numbers.size(), anzDIGIT, anzANALOG);

@@ -426,7 +467,7 @@ void ClassFlowPostProcessing::InitNUMBERS()
        
        _number->digit_roi = NULL;
        if (flowDigit)
-            _number->digit_roi = flowDigit->FindDIGIT(name_numbers[_num]);
+            _number->digit_roi = flowDigit->FindGENERAL(name_numbers[_num]);
        
        if (_number->digit_roi)
            _number->AnzahlDigital = _number->digit_roi->ROI.size();
@@ -435,7 +476,7 @@ void ClassFlowPostProcessing::InitNUMBERS()

        _number->analog_roi = NULL;
        if (flowAnalog)
-            _number->analog_roi = flowAnalog->FindANALOG(name_numbers[_num]);
+            _number->analog_roi = flowAnalog->FindGENERAL(name_numbers[_num]);


        if (_number->analog_roi)
@@ -453,9 +494,10 @@ void ClassFlowPostProcessing::InitNUMBERS()
        _number->MaxRateValue = 0.1;
        _number->useMaxRateValue = false;
        _number->checkDigitIncreaseConsistency = false;
-        _number->PreValueOkay = false;
-        _number->useMaxRateValue = false;
        _number->DecimalShift = 0;
+        _number->DecimalShiftInitial = 0;
+        _number->isExtendedResolution = false;
+

        _number->FlowRateAct = 0;          // m3 / min
        _number->PreValue = 0;             // letzter Wert, der gut ausgelesen wurde
@@ -526,7 +568,7 @@ bool ClassFlowPostProcessing::doFlow(string zwtime)
    time_t imagetime = 0;
    string rohwert;

-//    ErrorMessageText = "";
+    // Update Nachkomma, da sich beim Wechsel von CNNType Auto --> xyz auch die Nachkommastellen ändern können:

    imagetime = flowMakeImage->getTimeImageTaken();
    if (imagetime == 0)
@@ -545,14 +587,31 @@ bool ClassFlowPostProcessing::doFlow(string zwtime)
        NUMBERS[j]->ReturnRawValue = "";
        NUMBERS[j]->ErrorMessageText = "";

+        UpdateNachkommaDecimalShift();
+
        if (NUMBERS[j]->digit_roi)
-            NUMBERS[j]->ReturnRawValue = flowDigit->getReadout(j);
+        {
+            if (NUMBERS[j]->analog_roi) 
+                NUMBERS[j]->ReturnRawValue = flowDigit->getReadout(j, false);
+            else
+                NUMBERS[j]->ReturnRawValue = flowDigit->getReadout(j, NUMBERS[j]->isExtendedResolution);        // Extended Resolution nur falls es keine analogen Ziffern gibt
+        }
        if (NUMBERS[j]->digit_roi && NUMBERS[j]->analog_roi)
            NUMBERS[j]->ReturnRawValue = NUMBERS[j]->ReturnRawValue + ".";
-        if (NUMBERS[j]->analog_roi)
-            NUMBERS[j]->ReturnRawValue = NUMBERS[j]->ReturnRawValue + flowAnalog->getReadout(j); 

-        NUMBERS[j]->ReturnRawValue = ShiftDecimal(NUMBERS[j]->ReturnRawValue, NUMBERS[j]->DecimalShift);   
+        if (NUMBERS[j]->analog_roi)
+            NUMBERS[j]->ReturnRawValue = NUMBERS[j]->ReturnRawValue + flowAnalog->getReadout(j, NUMBERS[j]->isExtendedResolution); 
+
+        NUMBERS[j]->ReturnRawValue = ShiftDecimal(NUMBERS[j]->ReturnRawValue, NUMBERS[j]->DecimalShift);  
+
+
+        if (IgnoreLeadingNaN)               
+        {
+            while ((NUMBERS[j]->ReturnRawValue.length() > 1) && (NUMBERS[j]->ReturnRawValue[0] == 'N'))
+            {
+                NUMBERS[j]->ReturnRawValue.erase(0, 1);
+            }
+        } 

        rohwert = NUMBERS[j]->ReturnRawValue;

@@ -590,16 +649,21 @@ bool ClassFlowPostProcessing::doFlow(string zwtime)
                NUMBERS[j]->Value = checkDigitConsistency(NUMBERS[j]->Value, NUMBERS[j]->DecimalShift, NUMBERS[j]->analog_roi != NULL, NUMBERS[j]->PreValue);
            }

-            zwvalue = RundeOutput(NUMBERS[j]->Value, NUMBERS[j]->AnzahlAnalog - NUMBERS[j]->DecimalShift);
+            zwvalue = RundeOutput(NUMBERS[j]->Value, NUMBERS[j]->Nachkomma);

            if ((!NUMBERS[j]->AllowNegativeRates) && (NUMBERS[j]->Value < NUMBERS[j]->PreValue))
            {
                NUMBERS[j]->ErrorMessageText = NUMBERS[j]->ErrorMessageText + "Neg. Rate - Read: " + zwvalue + " - Raw: " + NUMBERS[j]->ReturnRawValue + " - Pre: " + RundeOutput(NUMBERS[j]->PreValue, NUMBERS[j]->Nachkomma) + " "; 
                NUMBERS[j]->Value = NUMBERS[j]->PreValue;
-                zwvalue = RundeOutput(NUMBERS[j]->Value, NUMBERS[j]->AnzahlAnalog - NUMBERS[j]->DecimalShift);
+                zwvalue = RundeOutput(NUMBERS[j]->Value, NUMBERS[j]->Nachkomma);
            }

-            if (NUMBERS[j]->useMaxRateValue && (abs(NUMBERS[j]->Value - NUMBERS[j]->PreValue) > NUMBERS[j]->MaxRateValue))
+            double difference = difftime(imagetime, NUMBERS[j]->lastvalue);      // in Sekunden
+            difference /= 60;                                                    // in Minuten
+            NUMBERS[j]->FlowRateAct = (NUMBERS[j]->Value - NUMBERS[j]->PreValue) / difference;
+            NUMBERS[j]->ReturnRateValue = std::to_string(NUMBERS[j]->FlowRateAct);
+            
+            if (NUMBERS[j]->useMaxRateValue && (abs(NUMBERS[j]->FlowRateAct) > NUMBERS[j]->MaxRateValue))
            {
                NUMBERS[j]->ErrorMessageText = NUMBERS[j]->ErrorMessageText + "Rate too high - Read: " + RundeOutput(NUMBERS[j]->Value, NUMBERS[j]->Nachkomma) + " - Pre: " + RundeOutput(NUMBERS[j]->PreValue, NUMBERS[j]->Nachkomma);
                NUMBERS[j]->Value = NUMBERS[j]->PreValue;
@@ -611,26 +675,76 @@ bool ClassFlowPostProcessing::doFlow(string zwtime)
            if (NUMBERS[j]->ErrorMessage && (NUMBERS[j]->ErrorMessageText.length() > 0))
                NUMBERS[j]->ReturnValue = NUMBERS[j]->ReturnValue + "\t" + NUMBERS[j]->ErrorMessageText;

-
-            double difference = difftime(imagetime, NUMBERS[j]->lastvalue);      // in Sekunden
-            difference /= 60;                                          // in Minuten
-            NUMBERS[j]->FlowRateAct = (NUMBERS[j]->Value - NUMBERS[j]->PreValue) / difference;
-            NUMBERS[j]->lastvalue = imagetime;
-
            if (NUMBERS[j]->ErrorMessageText.length() == 0)
            {
+                NUMBERS[j]->lastvalue = imagetime;
                NUMBERS[j]->PreValue = NUMBERS[j]->Value;
+
+                NUMBERS[j]->ReturnValueNoError = NUMBERS[j]->ReturnValue;
                NUMBERS[j]->ReturnPreValue = RundeOutput(NUMBERS[j]->PreValue, NUMBERS[j]->Nachkomma);
                NUMBERS[j]->ErrorMessageText = "no error";
                UpdatePreValueINI = true;
            }
+            else
+            {
+                NUMBERS[j]->ReturnRateValue = "";
+                NUMBERS[j]->ReturnValue = "";
+                NUMBERS[j]->ReturnValueNoError = "";
+                NUMBERS[j]->timeStamp = "";
+                
+            }
        }
+        string _zw = "PostProcessing - Raw: " + NUMBERS[j]->ReturnRawValue + " Value: " + NUMBERS[j]->ReturnValue + " Error: " + NUMBERS[j]->ErrorMessageText;
+        LogFile.WriteToFile(_zw);
    }

    SavePreValue();
    return true;
 }

+
+void ClassFlowPostProcessing::UpdateNachkommaDecimalShift()
+{
+    for (int j = 0; j < NUMBERS.size(); ++j)
+    {
+        if (NUMBERS[j]->digit_roi && !NUMBERS[j]->analog_roi)            // es gibt nur digitale ziffern
+        {
+//            printf("Nurdigital\n");
+            NUMBERS[j]->DecimalShift = NUMBERS[j]->DecimalShiftInitial;
+
+            if (NUMBERS[j]->isExtendedResolution && flowDigit->isExtendedResolution())  // extended resolution ist an und soll auch bei dieser Ziffer verwendet werden
+                NUMBERS[j]->DecimalShift = NUMBERS[j]->DecimalShift-1;
+
+            NUMBERS[j]->Nachkomma = -NUMBERS[j]->DecimalShift;
+        }
+
+        if (!NUMBERS[j]->digit_roi && NUMBERS[j]->analog_roi)            // es gibt nur analoge ziffern
+        {
+//            printf("Nur analog\n");
+            NUMBERS[j]->DecimalShift = NUMBERS[j]->DecimalShiftInitial;
+            if (NUMBERS[j]->isExtendedResolution && flowAnalog->isExtendedResolution())  // extended resolution ist an und soll auch bei dieser Ziffer verwendet werden
+                NUMBERS[j]->DecimalShift = NUMBERS[j]->DecimalShift-1;
+
+            NUMBERS[j]->Nachkomma = -NUMBERS[j]->DecimalShift;
+        }
+
+        if (NUMBERS[j]->digit_roi && NUMBERS[j]->analog_roi)            // digital + analog
+        {
+//            printf("Nur digital + analog\n");
+
+            NUMBERS[j]->DecimalShift = NUMBERS[j]->DecimalShiftInitial;
+            NUMBERS[j]->Nachkomma = NUMBERS[j]->analog_roi->ROI.size() - NUMBERS[j]->DecimalShift;
+
+            if (NUMBERS[j]->isExtendedResolution && flowAnalog->isExtendedResolution())  // extended resolution ist an und soll auch bei dieser Ziffer verwendet werden
+                NUMBERS[j]->Nachkomma = NUMBERS[j]->Nachkomma+1;
+
+        }
+
+        printf("UpdateNachkommaDecShift NUMBER%i: Nachkomma %i, DecShift %i\n", j, NUMBERS[j]->Nachkomma,NUMBERS[j]->DecimalShift);
+    }
+}
+
+
 string ClassFlowPostProcessing::getReadout(int _number)
 {
    return NUMBERS[_number]->ReturnValue;
@@ -717,14 +831,14 @@ float ClassFlowPostProcessing::checkDigitConsistency(float input, int _decilamsh
    while (pot <= pot_max)
    {
        zw = input / pow(10, pot-1);
-        aktdigit_before = ((int) zw) % 10;
+        aktdigit_before = ((int) zw + 10) % 10;
        zw = _preValue / pow(10, pot-1);
-        olddigit_before = ((int) zw) % 10;
+        olddigit_before = ((int) zw + 10) % 10;

        zw = input / pow(10, pot);
-        aktdigit = ((int) zw) % 10;
+        aktdigit = ((int) zw + 10) % 10;
        zw = _preValue / pow(10, pot);
-        olddigit = ((int) zw) % 10;
+        olddigit = ((int) zw + 10) % 10;

        no_nulldurchgang = (olddigit_before <= aktdigit_before);

--- a/code/components/jomjol_flowcontroll/ClassFlowPostProcessing.h
+++ b/code/components/jomjol_flowcontroll/ClassFlowPostProcessing.h
@@ -1,49 +1,13 @@
-#pragma once
+#ifndef __FLOWPOSTPROCESSING__
+#define __FLOWPOSTPROCESSING__
+
 #include "ClassFlow.h"
 #include "ClassFlowMakeImage.h"
-#include "ClassFlowAnalog.h"
-#include "ClassFlowDigit.h"
-
+#include "ClassFlowCNNGeneral.h"
+#include "ClassFlowDefineTypes.h"

 #include <string>

-
-struct NumberPost {
-//    int PreValueAgeStartup; 
-    float MaxRateValue;
-    bool useMaxRateValue;
-    bool ErrorMessage;
-    bool PreValueOkay;
-    bool AllowNegativeRates;
-    bool checkDigitIncreaseConsistency;
-    time_t lastvalue;
-    string timeStamp;
-    float FlowRateAct;          // m3 / min
-    float PreValue;             // letzter Wert, der gut ausgelesen wurde
-    float Value;                // letzer ausgelesener Wert, inkl. Korrekturen
-    string ReturnRawValue;      // Rohwert (mit N & führenden 0)    
-    string ReturnValue;         // korrigierter Rückgabewert, ggf. mit Fehlermeldung
-    string ReturnPreValue;  // korrigierter Rückgabewert ohne Fehlermeldung
-    string ReturnValueNoError;
-    string ErrorMessageText;        // Fehlermeldung bei Consistency Check
-    int AnzahlAnalog;
-    int AnzahlDigital;
-    int DecimalShift;
-    int Nachkomma;
-//    ClassFlowAnalog* ANALOG;
-//    ClassFlowDigit* DIGIT;
-
-    digit *digit_roi;
-    analog *analog_roi;
-
-
-
-    string name;
-};
-
-
-
-
 class ClassFlowPostProcessing :
    public ClassFlow
 {
@@ -51,13 +15,13 @@ protected:
    std::vector<NumberPost*> NUMBERS;
    bool UpdatePreValueINI;

-    bool PreValueUse;
    int PreValueAgeStartup; 
    bool ErrorMessage;
+    bool IgnoreLeadingNaN;          // SPEZIALFALL für User Gustl


-    ClassFlowAnalog* flowAnalog;
-    ClassFlowDigit* flowDigit;    
+    ClassFlowCNNGeneral* flowAnalog;
+    ClassFlowCNNGeneral* flowDigit;    


    string FilePreValue;
@@ -74,10 +38,14 @@ protected:
    void InitNUMBERS();
    void handleDecimalSeparator(string _decsep, string _value);
    void handleMaxRateValue(string _decsep, string _value);
+    void handleDecimalExtendedResolution(string _decsep, string _value);    
+


 public:
-    ClassFlowPostProcessing(std::vector<ClassFlow*>* lfc);
+    bool PreValueUse;
+
+    ClassFlowPostProcessing(std::vector<ClassFlow*>* lfc, ClassFlowCNNGeneral *_analog, ClassFlowCNNGeneral *_digit);
    bool ReadParameter(FILE* pfile, string& aktparamgraph);
    bool doFlow(string time);
    string getReadout(int _number);
@@ -87,9 +55,14 @@ public:
    string getReadoutTimeStamp(int _number = 0);
    void SavePreValue();
    string GetPreValue(std::string _number = "");
-    void SetPreValue(float zw, string _numbers);
-    std::vector<NumberPost*> GetNumbers(){return NUMBERS;};
+    void SetPreValue(float zw, string _numbers, bool _extern = false);
+
+    void UpdateNachkommaDecimalShift();
+
+    std::vector<NumberPost*>* GetNumbers(){return &NUMBERS;};

    string name(){return "ClassFlowPostProcessing";};
 };

+
+#endif
--- a/code/components/jomjol_helper/CMakeLists.txt
+++ b/code/components/jomjol_helper/CMakeLists.txt
@@ -2,6 +2,6 @@ FILE(GLOB_RECURSE app_sources ${CMAKE_CURRENT_SOURCE_DIR}/*.*)

 idf_component_register(SRCS ${app_sources}
                    INCLUDE_DIRS "."
-                    REQUIRES tfmicro jomjol_logfile)
+                    REQUIRES tflite-lib jomjol_logfile)


--- a/code/components/jomjol_helper/Helper.cpp
+++ b/code/components/jomjol_helper/Helper.cpp
@@ -6,7 +6,15 @@
 #include "Helper.h"
 #include <sys/types.h>
 #include <sys/stat.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif
 #include <dirent.h>
+#ifdef __cplusplus
+}
+#endif
+
 #include <string.h>
 #include <esp_log.h>

@@ -80,20 +88,23 @@ void memCopyGen(uint8_t* _source, uint8_t* _target, int _size)

 FILE* OpenFileAndWait(const char* nm, const char* _mode, int _waitsec)
 {
-	printf("open config file %s in mode %s\n", nm, _mode);
+	printf("open file %s in mode %s\n", nm, _mode);
 	FILE *pfile = fopen(nm, _mode);

+/*
 	if (pfile == NULL)
 	{
 		TickType_t xDelay;
 		xDelay = _waitsec * 1000 / portTICK_PERIOD_MS;
-		std::string zw = "File is locked: " + std::string(nm) + " - wait for " + std::to_string(_waitsec);
+		std::string zw = "File is locked: " + std::string(nm) + " - wait for " + std::to_string(_waitsec) + " seconds";
 	    printf(zw.c_str());
 		printf("\n");
 		LogFile.WriteToFile(zw);      
 		vTaskDelay( xDelay );
 		pfile = fopen(nm, _mode);
 	}
+*/
+
 	return pfile;
 }

--- a/code/components/jomjol_image_proc/CImageBasis.cpp
+++ b/code/components/jomjol_image_proc/CImageBasis.cpp
@@ -1,6 +1,7 @@
 #include "CImageBasis.h"
 #include "Helper.h"
 #include "ClassLogFile.h"
+#include "server_ota.h"

 #include <esp_log.h>

@@ -337,6 +338,18 @@ void CImageBasis::LoadFromMemory(stbi_uc *_buffer, int len)
    rgb_image = stbi_load_from_memory(_buffer, len, &width, &height, &channels, 3);
    bpp = channels;
    printf("Image loaded from memory: %d, %d, %d\n", width, height, channels);
+    if ((width * height * channels) == 0)
+    {
+        ESP_LOGE(TAG, "Image with size 0 loaded --> reboot to be done! "
+            "Check that your camera module is working and connected properly.");
+
+        LogFile.SwitchOnOff(true);
+        LogFile.WriteToFile("Image with size 0 loaded --> reboot to be done! "
+                "Check that your camera module is working and connected properly.");
+
+        doReboot();
+
+    }
    RGBImageRelease();
 }

--- a/code/components/jomjol_image_proc/CMakeLists.txt
+++ b/code/components/jomjol_image_proc/CMakeLists.txt
@@ -2,6 +2,6 @@ FILE(GLOB_RECURSE app_sources ${CMAKE_CURRENT_SOURCE_DIR}/*.*)

 idf_component_register(SRCS ${app_sources}
                    INCLUDE_DIRS "."
-                    REQUIRES jomjol_helper jomjol_logfile esp_http_server)
+                    REQUIRES jomjol_helper jomjol_logfile esp_http_server jomjol_fileserver_ota) 


--- a/code/components/jomjol_logfile/ClassLogFile.cpp
+++ b/code/components/jomjol_logfile/ClassLogFile.cpp
@@ -3,7 +3,15 @@
 #include <string.h>
 #include <sys/types.h>
 #include <sys/stat.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif
 #include <dirent.h>
+#ifdef __cplusplus
+}
+#endif
+
 #include "Helper.h"

 static const char *TAG = "log";
--- a/code/components/jomjol_mqtt/CMakeLists.txt
+++ b/code/components/jomjol_mqtt/CMakeLists.txt
@@ -2,6 +2,6 @@ FILE(GLOB_RECURSE app_sources ${CMAKE_CURRENT_SOURCE_DIR}/*.*)

 idf_component_register(SRCS ${app_sources}
                    INCLUDE_DIRS "."
-                    REQUIRES tfmicro mqtt jomjol_logfile)
+                    REQUIRES tflite-lib mqtt jomjol_logfile)


--- a/code/components/jomjol_tfliteclass/CTfLiteClass.cpp
+++ b/code/components/jomjol_tfliteclass/CTfLiteClass.cpp
@@ -17,6 +17,7 @@ float CTfLiteClass::GetOutputValue(int nr)
    return output2->data.f[nr];
 }

+
 int CTfLiteClass::GetClassFromImageBasis(CImageBasis *rs)
 {
    if (!LoadInputImageBasis(rs))
@@ -27,19 +28,36 @@ int CTfLiteClass::GetClassFromImageBasis(CImageBasis *rs)
    return GetOutClassification();
 }

-int CTfLiteClass::GetOutClassification()
+
+int CTfLiteClass::GetOutClassification(int _von, int _bis)
 {
  TfLiteTensor* output2 = interpreter->output(0);

-  float zw_max = 0;
+  float zw_max;
  float zw;
-  int zw_class = -1;
+  int zw_class;

  if (output2 == NULL)
    return -1;

  int numeroutput = output2->dims->data[1];
-  for (int i = 0; i < numeroutput; ++i)
+  //printf("\n number output neurons: %d\n\n", numeroutput);
+
+  if (_bis == -1)
+    _bis = numeroutput -1;
+
+  if (_von == -1)
+    _von = 0;
+
+  if (_bis >= numeroutput)
+  {
+    printf("ANZAHL OUTPUT NEURONS passt nicht zu geforderter Classifizierung!");
+    return -1;
+  }
+
+  zw_max = output2->data.f[_von];
+  zw_class = _von;
+  for (int i = _von + 1; i <= _bis; ++i)
  {
    zw = output2->data.f[i];
    if (zw > zw_max)
@@ -48,7 +66,7 @@ int CTfLiteClass::GetOutClassification()
        zw_class = i;
    }
  }
-  return zw_class;
+  return (zw_class - _von);
 }

 void CTfLiteClass::GetInputDimension(bool silent = false)
@@ -70,18 +88,18 @@ void CTfLiteClass::GetInputDimension(bool silent = false)
 }


-void CTfLiteClass::GetOutPut()
+int CTfLiteClass::GetAnzOutPut(bool silent)
 {
  TfLiteTensor* output2 = this->interpreter->output(0);

  int numdim = output2->dims->size;
-  printf("NumDimension: %d\n", numdim);  
+  if (!silent) printf("NumDimension: %d\n", numdim);  

  int sizeofdim;
  for (int j = 0; j < numdim; ++j)
  {
    sizeofdim = output2->dims->data[j];
-    printf("SizeOfDimension %d: %d\n", j, sizeofdim);  
+    if (!silent) printf("SizeOfDimension %d: %d\n", j, sizeofdim);  
  }


@@ -92,8 +110,9 @@ void CTfLiteClass::GetOutPut()
  for (int i = 0; i < numeroutput; ++i)
  {
   fo = output2->data.f[i];
-    printf("Result %d: %f\n", i, fo);  
+    if (!silent) printf("Result %d: %f\n", i, fo);  
  }
+  return numeroutput;
 }

 void CTfLiteClass::Invoke()
@@ -106,7 +125,7 @@ void CTfLiteClass::Invoke()

 bool CTfLiteClass::LoadInputImageBasis(CImageBasis *rs)
 {
-    std::string zw = "ClassFlowAnalog::doNeuralNetwork nach LoadInputResizeImage: ";
+    std::string zw = "ClassFlowCNNGeneral::doNeuralNetwork nach LoadInputResizeImage: ";

    unsigned int w = rs->width;
    unsigned int h = rs->height;
@@ -149,6 +168,8 @@ void CTfLiteClass::MakeAllocate()
    TfLiteStatus allocate_status = this->interpreter->AllocateTensors();
    if (allocate_status != kTfLiteOk) {
        TF_LITE_REPORT_ERROR(error_reporter, "AllocateTensors() failed");
+        LogFile.WriteToFile("AllocateTensors() failed");
+
    this->GetInputDimension();   
    return;
  }
@@ -215,14 +236,13 @@ bool CTfLiteClass::LoadModel(std::string _fn){
    this->error_reporter = new tflite::MicroErrorReporter;
 #endif

-    unsigned char *rd;
-    rd = ReadFileToCharArray(_fn.c_str());
+    modelload = ReadFileToCharArray(_fn.c_str());

-    if (rd == NULL) 
+    if (modelload == NULL) 
      return false;

-    this->model = tflite::GetModel(rd);
-    free(rd);
+    model = tflite::GetModel(modelload);
+//    free(rd);
    TFLITE_MINIMAL_CHECK(model != nullptr); 
    
    return true;
@@ -236,7 +256,7 @@ CTfLiteClass::CTfLiteClass()
    this->interpreter = nullptr;
    this->input = nullptr;
    this->output = nullptr;  
-    this->kTensorArenaSize = 200 * 1024;   /// laut testfile: 108000 - bisher 600
+    this->kTensorArenaSize = 800 * 1024;   /// laut testfile: 108000 - bisher 600;; 2021-09-11: 200 * 1024
    this->tensor_arena = new uint8_t[kTensorArenaSize]; 
 }

@@ -245,6 +265,8 @@ CTfLiteClass::~CTfLiteClass()
  delete this->tensor_arena;
  delete this->interpreter;
  delete this->error_reporter;
+  if (modelload)
+    free(modelload);
 }        


--- a/code/components/jomjol_tfliteclass/CTfLiteClass.h
+++ b/code/components/jomjol_tfliteclass/CTfLiteClass.h
@@ -46,6 +46,9 @@ class CTfLiteClass
        int kTensorArenaSize;
        uint8_t *tensor_arena;

+        unsigned char *modelload = NULL;
+
+
        float* input;
        int input_i;
        int im_height, im_width, im_channel;
@@ -61,9 +64,13 @@ class CTfLiteClass
        void GetInputTensorSize();
        bool LoadInputImageBasis(CImageBasis *rs);
        void Invoke();
-        void GetOutPut();
-        int GetOutClassification();
+        int GetAnzOutPut(bool silent = true);        
+//        void GetOutPut();
+//        int GetOutClassification();
+        int GetOutClassification(int _von = -1, int _bis = -1);
+
        int GetClassFromImageBasis(CImageBasis *rs);
+        std::string GetStatusFlow();

        float GetOutputValue(int nr);
        void GetInputDimension(bool silent);
--- a/code/components/jomjol_tfliteclass/server_tflite.cpp
+++ b/code/components/jomjol_tfliteclass/server_tflite.cpp
@@ -28,9 +28,6 @@ ClassFlowControll tfliteflow;
 TaskHandle_t xHandleblink_task_doFlow = NULL;
 TaskHandle_t xHandletask_autodoFlow = NULL;

-
-
-
 bool flowisrunning = false;

 long auto_intervall = 0;
@@ -192,6 +189,36 @@ esp_err_t handler_doflow(httpd_req_t *req)
 };


+esp_err_t handler_json(httpd_req_t *req)
+{
+#ifdef DEBUG_DETAIL_ON       
+    LogFile.WriteHeapInfo("handler_json - Start");    
+#endif
+
+
+    printf("handler_JSON uri:\n"); printf(req->uri); printf("\n");
+
+    char _query[100];
+    char _size[10];
+
+    httpd_resp_set_hdr(req, "Access-Control-Allow-Origin", "*");
+    httpd_resp_set_type(req, "application/json");
+
+    std::string zw = tfliteflow.getJSON();
+    if (zw.length() > 0)
+        httpd_resp_sendstr_chunk(req, zw.c_str()); 
+
+    string query = std::string(_query);
+
+    /* Respond with an empty chunk to signal HTTP response completion */
+    httpd_resp_sendstr_chunk(req, NULL);   
+
+#ifdef DEBUG_DETAIL_ON       
+    LogFile.WriteHeapInfo("handler_JSON - Done");   
+#endif
+    return ESP_OK;
+};
+


 esp_err_t handler_wasserzaehler(httpd_req_t *req)
@@ -283,37 +310,48 @@ esp_err_t handler_wasserzaehler(httpd_req_t *req)
        txt = txt + "Digital Counter: <p> ";
        httpd_resp_sendstr_chunk(req, txt.c_str()); 
        
-        std::vector<HTMLInfo*> htmlinfo;
-        htmlinfo = tfliteflow.GetAllDigital();
-        for (int i = 0; i < htmlinfo.size(); ++i)
+        std::vector<HTMLInfo*> htmlinfodig;
+        htmlinfodig = tfliteflow.GetAllDigital();  
+        for (int i = 0; i < htmlinfodig.size(); ++i)
        {
-            if (htmlinfo[i]->val == 10)
-                zw = "NaN";
+            if (tfliteflow.GetTypeDigital() == Digital)
+            {
+                if (htmlinfodig[i]->val == 10)
+                    zw = "NaN";
+                else
+                    zw = to_string((int) htmlinfodig[i]->val);
+
+                txt = "<img src=\"/img_tmp/" +  htmlinfodig[i]->filename + "\"> " + zw;
+            }
            else
            {
-                zw = to_string((int) htmlinfo[i]->val);
+                std::stringstream stream;
+                stream << std::fixed << std::setprecision(1) << htmlinfodig[i]->val;
+                zw = stream.str();
+
+                txt = "<img src=\"/img_tmp/" +  htmlinfodig[i]->filename + "\"> " + zw;
            }
-            txt = "<img src=\"/img_tmp/" +  htmlinfo[i]->filename + "\"> " + zw;
            httpd_resp_sendstr_chunk(req, txt.c_str()); 
-            delete htmlinfo[i];
+            delete htmlinfodig[i];
        }
-        htmlinfo.clear();
+        htmlinfodig.clear();
      
        txt = " <p> Analog Meter: <p> ";
        httpd_resp_sendstr_chunk(req, txt.c_str()); 
        
-        htmlinfo = tfliteflow.GetAllAnalog();
-        for (int i = 0; i < htmlinfo.size(); ++i)
+        std::vector<HTMLInfo*> htmlinfoana;
+        htmlinfoana = tfliteflow.GetAllAnalog();
+        for (int i = 0; i < htmlinfoana.size(); ++i)
        {
            std::stringstream stream;
-            stream << std::fixed << std::setprecision(1) << htmlinfo[i]->val;
+            stream << std::fixed << std::setprecision(1) << htmlinfoana[i]->val;
            zw = stream.str();

-            txt = "<img src=\"/img_tmp/" +  htmlinfo[i]->filename + "\"> " + zw;
+            txt = "<img src=\"/img_tmp/" +  htmlinfoana[i]->filename + "\"> " + zw;
            httpd_resp_sendstr_chunk(req, txt.c_str()); 
-            delete htmlinfo[i];
+            delete htmlinfoana[i];
        }
-        htmlinfo.clear();   
+        htmlinfoana.clear();   

    }   

@@ -493,31 +531,7 @@ esp_err_t handler_editflow(httpd_req_t *req)
 //        string zwzw = "Do " + _task + " start\n"; printf(zwzw.c_str());
        std::string zw = tfliteflow.doSingleStep("[Alignment]", _host);
        httpd_resp_sendstr_chunk(req, zw.c_str()); 
-    }  
-    if (_task.compare("test_analog") == 0)
-    {
-        std::string _host = "";
-        if (httpd_query_key_value(_query, "host", _valuechar, 30) == ESP_OK) {
-            _host = std::string(_valuechar);
-        }
-//        printf("Parameter host: "); printf(_host.c_str()); printf("\n"); 
-//        string zwzw = "Do " + _task + " start\n"; printf(zwzw.c_str());
-        std::string zw = tfliteflow.doSingleStep("[Analog]", _host);
-        httpd_resp_sendstr_chunk(req, zw.c_str()); 
-    }  
-    if (_task.compare("test_digits") == 0)
-    {
-        std::string _host = "";
-        if (httpd_query_key_value(_query, "host", _valuechar, 30) == ESP_OK) {
-            _host = std::string(_valuechar);
-        }
-//        printf("Parameter host: "); printf(_host.c_str()); printf("\n"); 
-
-//        string zwzw = "Do " + _task + " start\n"; printf(zwzw.c_str());
-        std::string zw = tfliteflow.doSingleStep("[Digits]", _host);
-        httpd_resp_sendstr_chunk(req, zw.c_str()); 
-    } 
-
+    }

    /* Respond with an empty chunk to signal HTTP response completion */
    httpd_resp_sendstr_chunk(req, NULL);   
@@ -530,6 +544,34 @@ esp_err_t handler_editflow(httpd_req_t *req)
 };


+esp_err_t handler_statusflow(httpd_req_t *req)
+{
+#ifdef DEBUG_DETAIL_ON       
+    LogFile.WriteHeapInfo("handler_prevalue - Start");       
+#endif
+
+    const char* resp_str;
+
+#ifdef DEBUG_DETAIL_ON       
+    printf("handler_prevalue:\n"); printf(req->uri); printf("\n");
+#endif
+
+    string* zw = tfliteflow.getActStatus();
+    resp_str = zw->c_str();
+
+    httpd_resp_set_hdr(req, "Access-Control-Allow-Origin", "*");
+    httpd_resp_send(req, resp_str, strlen(resp_str));   
+    /* Respond with an empty chunk to signal HTTP response completion */
+    httpd_resp_send_chunk(req, NULL, 0);      
+
+#ifdef DEBUG_DETAIL_ON       
+    LogFile.WriteHeapInfo("handler_prevalue - Start");       
+#endif
+
+    return ESP_OK;
+};
+
+
 esp_err_t handler_prevalue(httpd_req_t *req)
 {
 #ifdef DEBUG_DETAIL_ON       
@@ -569,7 +611,7 @@ esp_err_t handler_prevalue(httpd_req_t *req)
    }
    else
    {
-        zw = "SetPrevalue to " + tfliteflow.UpdatePrevalue(_size, _numbers);
+        zw = "SetPrevalue to " + tfliteflow.UpdatePrevalue(_size, _numbers, true);
    }
    
    resp_str = zw.c_str();
@@ -652,7 +694,28 @@ void task_autodoFlow(void *pvParameter)

 void TFliteDoAutoStart()
 {
-    xTaskCreate(&task_autodoFlow, "task_autodoFlow", configMINIMAL_STACK_SIZE * 64, NULL, tskIDLE_PRIORITY+1, &xHandletask_autodoFlow);
+    BaseType_t xReturned;
+
+    int _i = configMINIMAL_STACK_SIZE;
+
+    printf("task_autodoFlow configMINIMAL_STACK_SIZE: %d\n", _i);
+    printf("getESPHeapInfo: %s\n", getESPHeapInfo().c_str());
+
+    xReturned = xTaskCreate(&task_autodoFlow, "task_autodoFlow", configMINIMAL_STACK_SIZE * 60, NULL, tskIDLE_PRIORITY+1, &xHandletask_autodoFlow);
+    if( xReturned != pdPASS )
+    {
+
+       //Memory: 64 --> 48 --> 35 --> 25
+       printf("ERROR task_autodoFlow konnte nicht erzeugt werden !!\r\n");
+    }
+    printf("getESPHeapInfo: %s\n", getESPHeapInfo().c_str());
+
+
+}
+
+std::string GetMQTTMainTopic()
+{
+    return tfliteflow.GetMQTTMainTopic();
 }


@@ -679,6 +742,10 @@ void register_server_tflite_uri(httpd_handle_t server)
    camuri.user_ctx  = (void*) "Light Off"; 
    httpd_register_uri_handler(server, &camuri);  

+    camuri.uri       = "/statusflow.html";
+    camuri.handler   = handler_statusflow;
+    camuri.user_ctx  = (void*) "Light Off"; 
+    httpd_register_uri_handler(server, &camuri);  
    
    camuri.uri       = "/editflow.html";
    camuri.handler   = handler_editflow;
@@ -689,4 +756,10 @@ void register_server_tflite_uri(httpd_handle_t server)
    camuri.handler   = handler_wasserzaehler;
    camuri.user_ctx  = (void*) "Wasserzaehler"; 
    httpd_register_uri_handler(server, &camuri);  
+
+    camuri.uri       = "/json";
+    camuri.handler   = handler_json;
+    camuri.user_ctx  = (void*) "JSON"; 
+    httpd_register_uri_handler(server, &camuri);     
+
 }
--- a/code/components/jomjol_tfliteclass/server_tflite.h
+++ b/code/components/jomjol_tfliteclass/server_tflite.h
@@ -1,4 +1,5 @@
 #include <esp_log.h>
+#include <string>

 #include <esp_http_server.h>
 #include "CImageBasis.h"
@@ -13,6 +14,8 @@ void TFliteDoAutoStart();

 bool isSetupModusActive();

+std::string GetMQTTMainTopic();
+
 esp_err_t GetJPG(std::string _filename, httpd_req_t *req);

 esp_err_t GetRawJPG(httpd_req_t *req);
--- a/code/components/jomjol_time_sntp/CMakeLists.txt
+++ b/code/components/jomjol_time_sntp/CMakeLists.txt
@@ -2,6 +2,6 @@ FILE(GLOB_RECURSE app_sources ${CMAKE_CURRENT_SOURCE_DIR}/*.*)

 idf_component_register(SRCS ${app_sources}
                    INCLUDE_DIRS "."
-                    REQUIRES tfmicro jomjol_logfile)
+                    REQUIRES tflite-lib jomjol_logfile)


--- a/code/components/jomjol_wlan/connect_wlan.cpp
+++ b/code/components/jomjol_wlan/connect_wlan.cpp
@@ -50,14 +50,14 @@ std::string std_hostname = "watermeter";
 std::string ipadress = "";
 std::string ssid = "";

-std::string getIPAddress()
+std::string* getIPAddress()
 {
-    return ipadress;
+    return &ipadress;
 }

-std::string getSSID()
+std::string* getSSID()
 {
-    return ssid;
+    return &ssid;
 }


@@ -115,14 +115,10 @@ static void event_handler(void* arg, esp_event_base_t event_base,
        LEDBlinkTask(200, 1, true);
        esp_wifi_connect();
    } else if (event_base == WIFI_EVENT && event_id == WIFI_EVENT_STA_DISCONNECTED) {
-        if (s_retry_num < EXAMPLE_ESP_MAXIMUM_RETRY) {
-//            LEDBlinkTask(200, 1, true);
+//        if (s_retry_num < EXAMPLE_ESP_MAXIMUM_RETRY){ 
            esp_wifi_connect();
            s_retry_num++;
            ESP_LOGI(TAG, "retry to connect to the AP");
-        } else {
-            xEventGroupSetBits(s_wifi_event_group, WIFI_FAIL_BIT);
-        }
        ESP_LOGI(TAG,"connect to the AP fail");
    } else if (event_base == IP_EVENT && event_id == IP_EVENT_STA_GOT_IP) {
        ip_event_got_ip_t* event = (ip_event_got_ip_t*) event_data;
@@ -188,32 +184,6 @@ void wifi_init_sta(const char *_ssid, const char *_password, const char *_hostna
        ip_addr_set_ip4_u32(&dns_info.ip, ip.addr);
        ESP_ERROR_CHECK(esp_netif_set_dns_info(my_sta, ESP_NETIF_DNS_MAIN, &dns_info));
    }
-/////////////////////////////////////////////////////////////////
-
-
-//    esp_netif_create_default_wifi_sta();
-
-//    wifi_init_config_t cfg = WIFI_INIT_CONFIG_DEFAULT();
-//    ESP_ERROR_CHECK(esp_wifi_init(&cfg));
-
-
-
-/* 
-////////////////////////////// esp-idf 4.2 //////////////////////////
-    esp_event_handler_instance_t instance_any_id;
-    esp_event_handler_instance_t instance_got_ip;
-    ESP_ERROR_CHECK(esp_event_handler_instance_register(WIFI_EVENT,
-                                                        ESP_EVENT_ANY_ID,
-                                                        &event_handler,
-                                                        NULL,
-                                                        &instance_any_id));
-    ESP_ERROR_CHECK(esp_event_handler_instance_register(IP_EVENT,
-                                                        IP_EVENT_STA_GOT_IP,
-                                                        &event_handler,
-                                                        NULL,
-                                                        &instance_got_ip));
-////////////////////////// ENDE esp-idf 4.2 ///////////////////////////
-*/

    ESP_ERROR_CHECK(esp_event_handler_register(WIFI_EVENT, ESP_EVENT_ANY_ID, &event_handler, NULL));
    ESP_ERROR_CHECK(esp_event_handler_register(IP_EVENT, IP_EVENT_STA_GOT_IP, &event_handler, NULL));
@@ -257,27 +227,6 @@ void wifi_init_sta(const char *_ssid, const char *_password, const char *_hostna
    } else {
        ESP_LOGE(TAG, "UNEXPECTED EVENT");
    }
-
-    /* The event will not be processed after unregister */
-/* 
-////////////////////////////// esp-idf 4.2 //////////////////////////
-    ESP_ERROR_CHECK(esp_event_handler_instance_unregister(IP_EVENT, IP_EVENT_STA_GOT_IP, instance_got_ip));
-    ESP_ERROR_CHECK(esp_event_handler_instance_unregister(WIFI_EVENT, ESP_EVENT_ANY_ID, instance_any_id));
-////////////////////////// ENDE esp-idf 4.2 ///////////////////////////
-*/
-
-/* Deaktiveren, damit bei einen Verbindungsabbruch neu aufgebaut wird
-    ESP_ERROR_CHECK(esp_event_handler_unregister(IP_EVENT, IP_EVENT_STA_GOT_IP, &event_handler));
-    ESP_ERROR_CHECK(esp_event_handler_unregister(WIFI_EVENT, ESP_EVENT_ANY_ID, &event_handler));
-    vEventGroupDelete(s_wifi_event_group);
-*/ 
-
-/*
-    while (BlinkIsRunning)
-    {
-        vTaskDelay(100 / portTICK_PERIOD_MS);
-    }
-*/
 }


--- a/code/components/jomjol_wlan/connect_wlan.h
+++ b/code/components/jomjol_wlan/connect_wlan.h
@@ -7,8 +7,8 @@ void wifi_init_sta(const char *_ssid, const char *_password, const char *_hostna
 void wifi_init_sta(const char *_ssid, const char *_password, const char *_hostname);
 void wifi_init_sta(const char *_ssid, const char *_password);

-std::string getIPAddress();
-std::string getSSID();
+std::string* getIPAddress();
+std::string* getSSID();

 extern std::string hostname;
 extern std::string std_hostname;
--- a/code/components/jomjol_wlan/read_wlanini.cpp
+++ b/code/components/jomjol_wlan/read_wlanini.cpp
@@ -12,7 +12,7 @@
 #include <string.h>


-std::vector<string> ZerlegeZeile(std::string input, std::string _delimiter = "")
+std::vector<string> ZerlegeZeileWLAN(std::string input, std::string _delimiter = "")
 {
 	std::vector<string> Output;
 	std::string delimiter = " =,";
@@ -23,13 +23,13 @@ std::vector<string> ZerlegeZeile(std::string input, std::string _delimiter = "")
 	input = trim(input, delimiter);
 	size_t pos = findDelimiterPos(input, delimiter);
 	std::string token;
-	while (pos != std::string::npos) {
+    if (pos != std::string::npos)           // Zerlegt nur bis ersten Gleichheitszeichen !!! Sonderfall für WLAN.ini
+    {
 		token = input.substr(0, pos);
 		token = trim(token, delimiter);
 		Output.push_back(token);
 		input.erase(0, pos + 1);
 		input = trim(input, delimiter);
-		pos = findDelimiterPos(input, delimiter);
 	}
 	Output.push_back(input);

@@ -67,10 +67,8 @@ void LoadWlanFromFile(std::string fn, char *&_ssid, char *&_password, char *&_ho
    while ((line.size() > 0) || !(feof(pFile)))
    {
 //        printf("%s", line.c_str());
-        zerlegt = ZerlegeZeile(line, "=");
+        zerlegt = ZerlegeZeileWLAN(line, "=");
        zerlegt[0] = trim(zerlegt[0], " ");
-        for (int i = 2; i < zerlegt.size(); ++i)
-            zerlegt[1] = zerlegt[1] + "=" + zerlegt[i];

        if ((zerlegt.size() > 1) && (toUpper(zerlegt[0]) == "HOSTNAME")){
            hostname = trim(zerlegt[1]);
@@ -212,7 +210,7 @@ bool ChangeHostName(std::string fn, std::string _newhostname)
    while ((line.size() > 0) || !(feof(pFile)))
    {
        printf("%s", line.c_str());
-        zerlegt = ZerlegeZeile(line, "=");
+        zerlegt = ZerlegeZeileWLAN(line, "=");
        zerlegt[0] = trim(zerlegt[0], " ");

        if ((zerlegt.size() > 1) && (toUpper(zerlegt[0]) == "HOSTNAME")){
--- a/code/components/tflite-lib/CMakeLists.txt
+++ b/code/components/tflite-lib/CMakeLists.txt
@@ -0,0 +1,50 @@
+cmake_minimum_required(VERSION 3.5)
+
+set(tflite_dir "${CMAKE_CURRENT_SOURCE_DIR}/tensorflow/lite")
+set(tfmicro_dir "${tflite_dir}/micro")
+set(tfmicro_frontend_dir "${tflite_dir}/experimental/microfrontend/lib")
+set(tfmicro_kernels_dir "${tfmicro_dir}/kernels")
+
+file(GLOB srcs_micro
+          "${tfmicro_dir}/*.cc"
+          "${tfmicro_dir}/*.c")
+
+file(GLOB src_micro_frontend
+          "${tfmicro_frontend_dir}/*.c"
+          "${tfmicro_frontend_dir}/*.cc")
+file(GLOB srcs_kernels
+          "${tfmicro_kernels_dir}/*.c"
+          "${tfmicro_kernels_dir}/*.cc")
+
+set(lib_srcs
+          "${srcs_micro}"
+          "${srcs_kernels}"
+          "${src_micro_frontend}"
+          "${tflite_dir}/kernels/kernel_util.cc"
+          "${tflite_dir}/micro/memory_planner/greedy_memory_planner.cc"
+          "${tflite_dir}/micro/memory_planner/linear_memory_planner.cc"
+          "${tflite_dir}/c/common.c"
+          "${tflite_dir}/core/api/error_reporter.cc"
+          "${tflite_dir}/core/api/flatbuffer_conversions.cc"
+          "${tflite_dir}/core/api/op_resolver.cc"
+          "${tflite_dir}/core/api/tensor_utils.cc"
+          "${tflite_dir}/kernels/internal/quantization_util.cc"
+          "${tflite_dir}/schema/schema_utils.cc")
+
+idf_component_register(
+            SRCS "${lib_srcs}"
+            INCLUDE_DIRS "." "third_party/gemmlowp"
+                         "third_party/flatbuffers/include"
+                         "third_party/ruy"
+                         "third_party/kissfft")
+
+# Reduce the level of paranoia to be able to compile TF sources
+target_compile_options(${COMPONENT_LIB} PRIVATE
+  -Wno-maybe-uninitialized
+  -Wno-missing-field-initializers
+  -Wno-type-limits)
+
+target_compile_options(${COMPONENT_LIB} PRIVATE -fno-unwind-tables -ffunction-sections -fdata-sections -fmessage-length=0 -DTF_LITE_STATIC_MEMORY -DTF_LITE_DISABLE_X86_NEON -O3 -Wsign-compare -Wdouble-promotion -Wshadow -Wunused-variable -Wmissing-field-initializers -Wunused-function -Wswitch -Wvla -Wall -Wextra -Wstrict-aliasing -Wno-unused-parameter -DESP -DESP_NN -Wno-nonnull -Wno-nonnull -Wno-nonnull)
+target_compile_options(${COMPONENT_LIB} PRIVATE $<$<COMPILE_LANGUAGE:CXX>: -std=c++11 -fno-rtti -fno-exceptions -fno-threadsafe-statics -fno-unwind-tables -ffunction-sections -fdata-sections -fmessage-length=0 -DTF_LITE_STATIC_MEMORY -DTF_LITE_DISABLE_X86_NEON -O3 -Werror -Wsign-compare -Wdouble-promotion -Wshadow -Wunused-variable -Wmissing-field-initializers -Wunused-function -Wswitch -Wvla -Wall -Wextra -Wstrict-aliasing -Wno-unused-parameter -DESP -DESP_NN -Wno-return-type -Wno-strict-aliasing -std=gnu++14 -Wno-return-type -Wno-strict-aliasing -std=gnu++14 -Wno-return-type -Wno-strict-aliasing -std=gnu++14 >)
+target_compile_options(${COMPONENT_LIB} INTERFACE $<$<IN_LIST:-DTF_LITE_STATIC_MEMORY,$<TARGET_PROPERTY:${COMPONENT_LIB},COMPILE_OPTIONS>>:-DTF_LITE_STATIC_MEMORY>)
+target_link_libraries(${COMPONENT_LIB} PRIVATE -lm)
--- a/code/components/tflite-lib/tensorflow/lite/c/builtin_op_data.h
+++ b/code/components/tflite-lib/tensorflow/lite/c/builtin_op_data.h
@@ -63,7 +63,6 @@ typedef struct {
 } TfLiteMirrorPaddingParams;

 // Possible fused activation functions.
-// TODO(aselle): rename to TfLiteActivation
 typedef enum {
  kTfLiteActNone = 0,
  kTfLiteActRelu,
@@ -98,6 +97,8 @@ typedef struct {
  TfLiteFusedActivation activation;
 } TfLiteConv3DParams;

+typedef TfLiteConv3DParams TfLiteConv3DTransposeParams;
+
 typedef struct {
  TfLitePadding padding;
  int stride_width;
@@ -328,8 +329,9 @@ typedef struct {
 } TfLitePadV2Params;

 typedef struct {
-  // TODO(ahentz): We can't have dynamic data in this struct, at least not yet.
-  // For now we will fix the maximum possible number of dimensions.
+  // These fields are only used in old models for backward compatibility.
+  // In the current implementation, we use the 2nd input of the op as the shape,
+  // and these fields are unused.
  int shape[TFLITE_RESHAPE_PARAMS_MAX_DIMENSION_COUNT];
  int num_dimensions;
 } TfLiteReshapeParams;
@@ -495,6 +497,27 @@ typedef struct {
  TfLiteType value_dtype;
 } TfLiteHashtableParams;

+typedef struct {
+  const char* container;
+  const char* shared_name;
+} TfLiteVarHandleParams;
+
+typedef struct {
+  int seed;
+  int seed2;
+} TfLiteRandomParams;
+
+typedef struct {
+  int num_boundaries;
+  // This points to the memory stored in the model (flatbuffer),
+  // and is not owned.
+  const float* boundaries;
+} TfLiteBucketizeParams;
+
+typedef struct {
+  bool approximate;
+} TfLiteGeluParams;
+
 #ifdef __cplusplus
 }  // extern "C"
 #endif  // __cplusplus
--- a/code/components/tflite-lib/tensorflow/lite/c/c_api_types.h
+++ b/code/components/tflite-lib/tensorflow/lite/c/c_api_types.h
@@ -29,7 +29,9 @@ extern "C" {
 // library.
 #ifdef SWIG
 #define TFL_CAPI_EXPORT
-#else
+#elif defined(TFL_STATIC_LIBRARY_BUILD)
+#define TFL_CAPI_EXPORT
+#else  // not definded TFL_STATIC_LIBRARY_BUILD
 #if defined(_WIN32)
 #ifdef TFL_COMPILE_LIBRARY
 #define TFL_CAPI_EXPORT __declspec(dllexport)
@@ -41,6 +43,9 @@ extern "C" {
 #endif  // _WIN32
 #endif  // SWIG

+// Note that new error status values may be added in future in order to
+// indicate more fine-grained internal states, therefore, applications should
+// not rely on status values being members of the enum.
 typedef enum TfLiteStatus {
  kTfLiteOk = 0,

@@ -52,9 +57,26 @@ typedef enum TfLiteStatus {

  // Generally referring to an error in applying a delegate due to
  // incompatibility between runtime and delegate, e.g., this error is returned
-  // when trying to apply a TfLite delegate onto a model graph that's already
+  // when trying to apply a TF Lite delegate onto a model graph that's already
  // immutable.
-  kTfLiteApplicationError = 3
+  kTfLiteApplicationError = 3,
+
+  // Generally referring to serialized delegate data not being found.
+  // See tflite::delegates::Serialization.
+  kTfLiteDelegateDataNotFound = 4,
+
+  // Generally referring to data-writing issues in delegate serialization.
+  // See tflite::delegates::Serialization.
+  kTfLiteDelegateDataWriteError = 5,
+
+  // Generally referring to data-reading issues in delegate serialization.
+  // See tflite::delegates::Serialization.
+  kTfLiteDelegateDataReadError = 6,
+
+  // Generally referring to issues when the TF Lite model has ops that cannot be
+  // resolved at runtime. This could happen when the specific op is not
+  // registered or built with the TF Lite framework.
+  kTfLiteUnresolvedOps = 7,
 } TfLiteStatus;

 // Types supported by tensor
--- a/code/components/tflite-lib/tensorflow/lite/c/common.c
+++ b/code/components/tflite-lib/tensorflow/lite/c/common.c
@@ -21,9 +21,15 @@ limitations under the License.
 #include <string.h>
 #endif  // TF_LITE_STATIC_MEMORY

-int TfLiteIntArrayGetSizeInBytes(int size) {
+size_t TfLiteIntArrayGetSizeInBytes(int size) {
  static TfLiteIntArray dummy;
-  return sizeof(dummy) + sizeof(dummy.data[0]) * size;
+
+  size_t computed_size = sizeof(dummy) + sizeof(dummy.data[0]) * size;
+#if defined(_MSC_VER)
+  // Context for why this is needed is in http://b/189926408#comment21
+  computed_size -= sizeof(dummy.data[0]);
+#endif
+  return computed_size;
 }

 int TfLiteIntArrayEqual(const TfLiteIntArray* a, const TfLiteIntArray* b) {
@@ -45,8 +51,10 @@ int TfLiteIntArrayEqualsArray(const TfLiteIntArray* a, int b_size,
 #ifndef TF_LITE_STATIC_MEMORY

 TfLiteIntArray* TfLiteIntArrayCreate(int size) {
-  TfLiteIntArray* ret =
-      (TfLiteIntArray*)malloc(TfLiteIntArrayGetSizeInBytes(size));
+  size_t alloc_size = TfLiteIntArrayGetSizeInBytes(size);
+  if (alloc_size <= 0) return NULL;
+  TfLiteIntArray* ret = (TfLiteIntArray*)malloc(alloc_size);
+  if (!ret) return ret;
  ret->size = size;
  return ret;
 }
@@ -66,7 +74,13 @@ void TfLiteIntArrayFree(TfLiteIntArray* a) { free(a); }

 int TfLiteFloatArrayGetSizeInBytes(int size) {
  static TfLiteFloatArray dummy;
-  return sizeof(dummy) + sizeof(dummy.data[0]) * size;
+
+  int computed_size = sizeof(dummy) + sizeof(dummy.data[0]) * size;
+#if defined(_MSC_VER)
+  // Context for why this is needed is in http://b/189926408#comment21
+  computed_size -= sizeof(dummy.data[0]);
+#endif
+  return computed_size;
 }

 #ifndef TF_LITE_STATIC_MEMORY
@@ -174,6 +188,26 @@ void TfLiteTensorReset(TfLiteType type, const char* name, TfLiteIntArray* dims,
  tensor->quantization.params = NULL;
 }

+TfLiteStatus TfLiteTensorCopy(const TfLiteTensor* src, TfLiteTensor* dst) {
+  if (!src || !dst)
+    return kTfLiteOk;
+  if (src->bytes != dst->bytes)
+    return kTfLiteError;
+  if (src == dst)
+    return kTfLiteOk;
+
+  dst->type = src->type;
+  if (dst->dims)
+    TfLiteIntArrayFree(dst->dims);
+  dst->dims = TfLiteIntArrayCopy(src->dims);
+  memcpy(dst->data.raw, src->data.raw, src->bytes);
+  dst->buffer_handle = src->buffer_handle;
+  dst->data_is_stale = src->data_is_stale;
+  dst->delegate = src->delegate;
+
+  return kTfLiteOk;
+}
+
 void TfLiteTensorRealloc(size_t num_bytes, TfLiteTensor* tensor) {
  if (tensor->allocation_type != kTfLiteDynamic &&
      tensor->allocation_type != kTfLitePersistentRo) {
@@ -181,9 +215,9 @@ void TfLiteTensorRealloc(size_t num_bytes, TfLiteTensor* tensor) {
  }
  // TODO(b/145340303): Tensor data should be aligned.
  if (!tensor->data.raw) {
-    tensor->data.raw = malloc(num_bytes);
+    tensor->data.raw = (char*)malloc(num_bytes);
  } else if (num_bytes > tensor->bytes) {
-    tensor->data.raw = realloc(tensor->data.raw, num_bytes);
+    tensor->data.raw = (char*)realloc(tensor->data.raw, num_bytes);
  }
  tensor->bytes = num_bytes;
 }
@@ -229,7 +263,7 @@ const char* TfLiteTypeGetName(TfLiteType type) {
  return "Unknown type";
 }

-TfLiteDelegate TfLiteDelegateCreate() {
+TfLiteDelegate TfLiteDelegateCreate(void) {
  TfLiteDelegate d = {
      .data_ = NULL,
      .Prepare = NULL,
--- a/code/components/tflite-lib/tensorflow/lite/c/common.h
+++ b/code/components/tflite-lib/tensorflow/lite/c/common.h
@@ -80,12 +80,16 @@ typedef struct TfLiteExternalContext {
 // indices
 typedef struct TfLiteIntArray {
  int size;
-// gcc 6.1+ have a bug where flexible members aren't properly handled
-// https://github.com/google/re2/commit/b94b7cd42e9f02673cd748c1ac1d16db4052514c
-#if (!defined(__clang__) && defined(__GNUC__) && __GNUC__ == 6 && \
-     __GNUC_MINOR__ >= 1) ||                                      \
-    defined(HEXAGON) ||                                           \
+
+#if defined(_MSC_VER)
+  // Context for why this is needed is in http://b/189926408#comment21
+  int data[1];
+#elif (!defined(__clang__) && defined(__GNUC__) && __GNUC__ == 6 && \
+       __GNUC_MINOR__ >= 1) ||                                      \
+    defined(HEXAGON) ||                                             \
    (defined(__clang__) && __clang_major__ == 7 && __clang_minor__ == 1)
+  // gcc 6.1+ have a bug where flexible members aren't properly handled
+  // https://github.com/google/re2/commit/b94b7cd42e9f02673cd748c1ac1d16db4052514c
  int data[0];
 #else
  int data[];
@@ -94,7 +98,7 @@ typedef struct TfLiteIntArray {

 // Given the size (number of elements) in a TfLiteIntArray, calculate its size
 // in bytes.
-int TfLiteIntArrayGetSizeInBytes(int size);
+size_t TfLiteIntArrayGetSizeInBytes(int size);

 #ifndef TF_LITE_STATIC_MEMORY
 // Create a array of a given `size` (uninitialized entries).
@@ -121,11 +125,15 @@ void TfLiteIntArrayFree(TfLiteIntArray* a);
 // Fixed size list of floats. Used for per-channel quantization.
 typedef struct TfLiteFloatArray {
  int size;
-// gcc 6.1+ have a bug where flexible members aren't properly handled
-// https://github.com/google/re2/commit/b94b7cd42e9f02673cd748c1ac1d16db4052514c
-// This also applies to the toolchain used for Qualcomm Hexagon DSPs.
-#if !defined(__clang__) && defined(__GNUC__) && __GNUC__ == 6 && \
-    __GNUC_MINOR__ >= 1
+#if defined(_MSC_VER)
+  // Context for why this is needed is in http://b/189926408#comment21
+  float data[1];
+#elif (!defined(__clang__) && defined(__GNUC__) && __GNUC__ == 6 && \
+       __GNUC_MINOR__ >= 1) ||                                      \
+    defined(HEXAGON) ||                                             \
+    (defined(__clang__) && __clang_major__ == 7 && __clang_minor__ == 1)
+  // gcc 6.1+ have a bug where flexible members aren't properly handled
+  // https://github.com/google/re2/commit/b94b7cd42e9f02673cd748c1ac1d16db4052514c
  float data[0];
 #else
  float data[];
@@ -456,8 +464,8 @@ typedef struct TfLiteTensor {
 } TfLiteTensor;

 // A structure representing an instance of a node.
-// This structure only exhibits the inputs, outputs and user defined data, not
-// other features like the type.
+// This structure only exhibits the inputs, outputs, user defined data and some
+// node properties (like statefulness), not other features like the type.
 typedef struct TfLiteNode {
  // Inputs to this node expressed as indices into the simulator's tensors.
  TfLiteIntArray* inputs;
@@ -490,6 +498,9 @@ typedef struct TfLiteNode {
  // created by calling `interpreter.ModifyGraphWithDelegate`.
  // WARNING: This is an experimental interface that is subject to change.
  struct TfLiteDelegate* delegate;
+
+  // Whether this op might have side effect (e.g. stateful op).
+  bool might_have_side_effect;
 } TfLiteNode;
 #else   // defined(TF_LITE_STATIC_MEMORY)?
 // NOTE: This flag is opt-in only at compile time.
@@ -559,6 +570,10 @@ typedef struct TfLiteNode {
  // Outputs to this node expressed as indices into the simulator's tensors.
  TfLiteIntArray* outputs;

+  // intermediate tensors to this node expressed as indices into the simulator's
+  // tensors.
+  TfLiteIntArray* intermediates;
+
  // Opaque data provided by the node implementer through `Registration.init`.
  void* user_data;

@@ -611,6 +626,16 @@ void TfLiteTensorReset(TfLiteType type, const char* name, TfLiteIntArray* dims,
                       const void* allocation, bool is_variable,
                       TfLiteTensor* tensor);

+// Copies the contents of 'src' in 'dst'.
+// Function does nothing if either 'src' or 'dst' is passed as nullptr and
+// return kTfLiteOk.
+// Returns kTfLiteError if 'src' and 'dst' doesn't have matching data size.
+// Note function copies contents, so it won't create new data pointer
+// or change allocation type.
+// All Tensor related properties will be copied from 'src' to 'dst' like
+// quantization, sparsity, ...
+TfLiteStatus TfLiteTensorCopy(const TfLiteTensor* src, TfLiteTensor* dst);
+
 // Resize the allocated data of a (dynamic) tensor. Tensors with allocation
 // types other than kTfLiteDynamic will be ignored.
 void TfLiteTensorRealloc(size_t num_bytes, TfLiteTensor* tensor);
@@ -640,6 +665,7 @@ typedef struct TfLiteContext {
  // TfLiteDelegates can traverse the current execution plan by iterating
  // through each member of this array and using GetNodeAndRegistration() to
  // access details about a node. i.e.
+  //
  // TfLiteIntArray* execution_plan;
  // TF_LITE_ENSURE_STATUS(context->GetExecutionPlan(context, &execution_plan));
  // for (int exec_index = 0; exec_index < execution_plan->size; exec_index++) {
@@ -648,6 +674,28 @@ typedef struct TfLiteContext {
  //    TfLiteRegistration* reg;
  //    context->GetNodeAndRegistration(context, node_index, &node, &reg);
  // }
+  // Note: the memory pointed by '`*execution_plan` is OWNED by TfLite runtime.
+  // Future calls to GetExecutionPlan invalidates earlier outputs. The following
+  // code snippet shows the issue of such an invocation pattern. After calling
+  // CheckNode, subsequent access to `plan_1st` is undefined.
+  //
+  // void CheckNode(const TfLiteNode* node) {
+  //   ...
+  //   TfLiteIntArray* plan_2nd;
+  //   TF_LITE_ENSURE_STATUS(context->GetExecutionPlan(context, &plan_2nd));
+  //   ...
+  // }
+  //
+  // TfLiteIntArray* plan_1st;
+  // TF_LITE_ENSURE_STATUS(context->GetExecutionPlan(context, &plan_1st));
+  // for (int exec_index = 0; exec_index < plan_1st->size; exec_index++) {
+  //    int node_index = plan_1st->data[exec_index];
+  //    TfLiteNode* node;
+  //    TfLiteRegistration* reg;
+  //    context->GetNodeAndRegistration(context, node_index, &node, &reg);
+  //    CheckNode(node);
+  // }
+  //
  // WARNING: This is an experimental interface that is subject to change.
  TfLiteStatus (*GetExecutionPlan)(struct TfLiteContext* context,
                                   TfLiteIntArray** execution_plan);
@@ -777,10 +825,25 @@ typedef struct TfLiteContext {
  // WARNING: This method may not be available on all platforms.
  TfLiteEvalTensor* (*GetEvalTensor)(const struct TfLiteContext* context,
                                     int tensor_idx);
+
+  // Retrieves named metadata buffer from the TFLite model.
+  // Returns kTfLiteOk if metadata is successfully obtained from the flatbuffer
+  // Model: that is, there exists a `metadata` entry with given `name` string.
+  // (see TFLite's schema.fbs).
+  // The corresponding `buffer` information is populated in `ptr` & `bytes`.
+  // The data from `ptr` is valid for the lifetime of the Interpreter.
+  //
+  // WARNING: This is an experimental interface that is subject to change.
+  TfLiteStatus (*GetModelMetadata)(const struct TfLiteContext* context,
+                                   const char* name, const char** ptr,
+                                   size_t* bytes);
 } TfLiteContext;

 typedef struct TfLiteRegistration {
  // Initializes the op from serialized data.
+  // Called only *once* for the lifetime of the op, so any one-time allocations
+  // should be made here (unless they depend on tensor sizes).
+  //
  // If a built-in op:
  //   `buffer` is the op's params data (TfLiteLSTMParams*).
  //   `length` is zero.
@@ -803,6 +866,7 @@ typedef struct TfLiteRegistration {
  // prepare is called when the inputs this node depends on have been resized.
  // context->ResizeTensor() can be called to request output tensors to be
  // resized.
+  // Can be called multiple times for the lifetime of the op.
  //
  // Returns kTfLiteOk on success.
  TfLiteStatus (*prepare)(TfLiteContext* context, TfLiteNode* node);
@@ -918,7 +982,7 @@ typedef struct TfLiteDelegate {

 // Build a 'null' delegate, with all the fields properly set to their default
 // values.
-TfLiteDelegate TfLiteDelegateCreate();
+TfLiteDelegate TfLiteDelegateCreate(void);

 #ifdef __cplusplus
 }  // extern "C"
--- a/code/components/tflite-lib/tensorflow/lite/core/api/error_reporter.cc
+++ b/code/components/tflite-lib/tensorflow/lite/core/api/error_reporter.cc
--- a/code/components/tflite-lib/tensorflow/lite/core/api/error_reporter.h
+++ b/code/components/tflite-lib/tensorflow/lite/core/api/error_reporter.h
--- a/code/components/tflite-lib/tensorflow/lite/core/api/flatbuffer_conversions.cc
+++ b/code/components/tflite-lib/tensorflow/lite/core/api/flatbuffer_conversions.cc
@@ -1,4 +1,4 @@
-/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.

 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -131,6 +131,17 @@ TfLitePadding ConvertPadding(Padding padding) {
  return kTfLitePaddingUnknown;
 }

+// Converts the flatbuffer mirror padding enum to what is used at runtime.
+TfLiteMirrorPaddingMode ConvertMirrorPadding(MirrorPadMode padding) {
+  switch (padding) {
+    case MirrorPadMode_REFLECT:
+      return kTfLiteMirrorPaddingReflect;
+    case MirrorPadMode_SYMMETRIC:
+      return kTfLiteMirrorPaddingSymmetric;
+  }
+  return kTfLiteMirrorPaddingUnknown;
+}
+
 #ifndef TF_LITE_STATIC_MEMORY
 TfLiteStatus ParseOpDataTfLite(const Operator* op, BuiltinOperator op_type,
                               ErrorReporter* error_reporter,
@@ -181,6 +192,10 @@ TfLiteStatus ParseOpDataTfLite(const Operator* op, BuiltinOperator op_type,
      return ParseArgMin(op, error_reporter, allocator, builtin_data);
    }

+    case BuiltinOperator_ASSIGN_VARIABLE: {
+      return ParseAssignVariable(op, error_reporter, allocator, builtin_data);
+    }
+
    case BuiltinOperator_AVERAGE_POOL_2D: {
      return ParsePool(op, error_reporter, allocator, builtin_data);
    }
@@ -193,6 +208,10 @@ TfLiteStatus ParseOpDataTfLite(const Operator* op, BuiltinOperator op_type,
      return ParseBatchToSpaceNd(op, error_reporter, allocator, builtin_data);
    }

+    case BuiltinOperator_CALL_ONCE: {
+      return ParseCallOnce(op, error_reporter, allocator, builtin_data);
+    }
+
    case BuiltinOperator_CEIL: {
      return ParseCeil(op, error_reporter, allocator, builtin_data);
    }
@@ -325,6 +344,10 @@ TfLiteStatus ParseOpDataTfLite(const Operator* op, BuiltinOperator op_type,
      return ParsePool(op, error_reporter, allocator, builtin_data);
    }

+    case BuiltinOperator_MIRROR_PAD: {
+      return ParseMirrorPad(op, error_reporter, allocator, builtin_data);
+    }
+
    case BuiltinOperator_MEAN: {
      return ParseReducer(op, error_reporter, allocator, builtin_data);
    }
@@ -369,10 +392,18 @@ TfLiteStatus ParseOpDataTfLite(const Operator* op, BuiltinOperator op_type,
      return ParseQuantize(op, error_reporter, allocator, builtin_data);
    }

+    case BuiltinOperator_READ_VARIABLE: {
+      return ParseReadVariable(op, error_reporter, allocator, builtin_data);
+    }
+
    case BuiltinOperator_REDUCE_ANY: {
      return ParseReducer(op, error_reporter, allocator, builtin_data);
    }

+    case BuiltinOperator_REDUCE_ALL: {
+      return ParseReducer(op, error_reporter, allocator, builtin_data);
+    }
+
    case BuiltinOperator_REDUCE_MAX: {
      return ParseReducer(op, error_reporter, allocator, builtin_data);
    }
@@ -482,6 +513,10 @@ TfLiteStatus ParseOpDataTfLite(const Operator* op, BuiltinOperator op_type,
      return ParseUnpack(op, error_reporter, allocator, builtin_data);
    }

+    case BuiltinOperator_VAR_HANDLE: {
+      return ParseVarHandle(op, error_reporter, allocator, builtin_data);
+    }
+
    case BuiltinOperator_ZEROS_LIKE: {
      return ParseZerosLike(op, error_reporter, allocator, builtin_data);
    }
@@ -602,21 +637,8 @@ TfLiteStatus ParseOpDataTfLite(const Operator* op, BuiltinOperator op_type,
      return kTfLiteOk;
    }
    case BuiltinOperator_UNIDIRECTIONAL_SEQUENCE_LSTM: {
-      auto params =
-          safe_allocator.Allocate<TfLiteUnidirectionalSequenceLSTMParams>();
-      TF_LITE_ENSURE(error_reporter, params != nullptr);
-      if (const auto* seq_lstm_params =
-              op->builtin_options_as_UnidirectionalSequenceLSTMOptions()) {
-        params->activation =
-            ConvertActivation(seq_lstm_params->fused_activation_function());
-        params->cell_clip = seq_lstm_params->cell_clip();
-        params->proj_clip = seq_lstm_params->proj_clip();
-        params->time_major = seq_lstm_params->time_major();
-        params->asymmetric_quantize_inputs =
-            seq_lstm_params->asymmetric_quantize_inputs();
-      }
-      *builtin_data = params.release();
-      return kTfLiteOk;
+      return ParseUnidirectionalSequenceLSTM(op, error_reporter, allocator,
+                                             builtin_data);
    }
    case BuiltinOperator_BIDIRECTIONAL_SEQUENCE_LSTM: {
      auto params =
@@ -663,7 +685,6 @@ TfLiteStatus ParseOpDataTfLite(const Operator* op, BuiltinOperator op_type,
      return kTfLiteOk;
    }
    case BuiltinOperator_DELEGATE: {
-      // TODO(ycling): Revisit when supporting saving delegated models.
      TF_LITE_REPORT_ERROR(error_reporter,
                           "DELEGATE op shouldn't exist in model.");
      return kTfLiteError;
@@ -690,19 +711,6 @@ TfLiteStatus ParseOpDataTfLite(const Operator* op, BuiltinOperator op_type,
      *builtin_data = params.release();
      return kTfLiteOk;
    }
-    case BuiltinOperator_MIRROR_PAD: {
-      auto params = safe_allocator.Allocate<TfLiteMirrorPaddingParams>();
-      TF_LITE_ENSURE(error_reporter, params != nullptr);
-      const auto* mirror_pad_params = op->builtin_options_as_MirrorPadOptions();
-      if (mirror_pad_params != nullptr) {
-        params->mode =
-            mirror_pad_params->mode() == tflite::MirrorPadMode_REFLECT
-                ? TfLiteMirrorPaddingMode::kTfLiteMirrorPaddingReflect
-                : TfLiteMirrorPaddingMode::kTfLiteMirrorPaddingSymmetric;
-      }
-      *builtin_data = params.release();
-      return kTfLiteOk;
-    }
    case BuiltinOperator_UNIQUE: {
      auto params = safe_allocator.Allocate<TfLiteUniqueParams>();
      TF_LITE_ENSURE(error_reporter, params != nullptr);
@@ -747,17 +755,8 @@ TfLiteStatus ParseOpDataTfLite(const Operator* op, BuiltinOperator op_type,
      *builtin_data = params.release();
      return kTfLiteOk;
    }
-    case BuiltinOperator_CALL_ONCE: {
-      auto params = safe_allocator.Allocate<TfLiteCallOnceParams>();
-      TF_LITE_ENSURE(error_reporter, params != nullptr);
-      if (const auto* call_once_params =
-              op->builtin_options_as_CallOnceOptions()) {
-        params->init_subgraph_index = call_once_params->init_subgraph_index();
-      }
-      *builtin_data = params.release();
-      return kTfLiteOk;
-    }
-    case BuiltinOperator_CONV_3D: {
+    case BuiltinOperator_CONV_3D:
+    case BuiltinOperator_CONV_3D_TRANSPOSE: {
      auto params = safe_allocator.Allocate<TfLiteConv3DParams>();
      TF_LITE_ENSURE(error_reporter, params != nullptr);
      if (const auto* conv3d_params = op->builtin_options_as_Conv3DOptions()) {
@@ -789,6 +788,73 @@ TfLiteStatus ParseOpDataTfLite(const Operator* op, BuiltinOperator op_type,
      *builtin_data = params.release();
      return kTfLiteOk;
    }
+    case BuiltinOperator_MULTINOMIAL: {
+      auto params = safe_allocator.Allocate<TfLiteRandomParams>();
+      TF_LITE_ENSURE(error_reporter, params != nullptr);
+      if (const auto* multinomial_params =
+              op->builtin_options_as_RandomOptions()) {
+        params->seed = multinomial_params->seed();
+        params->seed2 = multinomial_params->seed2();
+      }
+      *builtin_data = params.release();
+      return kTfLiteOk;
+    }
+    case BuiltinOperator_RANDOM_STANDARD_NORMAL: {
+      auto params = safe_allocator.Allocate<TfLiteRandomParams>();
+      TF_LITE_ENSURE(error_reporter, params != nullptr);
+      if (const auto* random_std_normal_params =
+              op->builtin_options_as_RandomOptions()) {
+        params->seed = random_std_normal_params->seed();
+        params->seed2 = random_std_normal_params->seed2();
+      }
+      *builtin_data = params.release();
+      return kTfLiteOk;
+    }
+    case BuiltinOperator_BUCKETIZE: {
+      auto params = safe_allocator.Allocate<TfLiteBucketizeParams>();
+      TF_LITE_ENSURE(error_reporter, params != nullptr);
+      if (const auto* bucketize_params =
+              op->builtin_options_as_BucketizeOptions()) {
+        const flatbuffers::Vector<float>* boundaries =
+            bucketize_params->boundaries();
+        if (boundaries == nullptr) {
+          TF_LITE_REPORT_ERROR(
+              error_reporter,
+              "boundaries array not provided for operation 'bucketize'.\n");
+          return kTfLiteError;
+        }
+        params->num_boundaries = boundaries->size();
+        if (boundaries->data() == nullptr) {
+          TF_LITE_REPORT_ERROR(error_reporter,
+                               "boundaries.data() returned nullptr for "
+                               "operation 'bucketize'.\n");
+          return kTfLiteError;
+        }
+        params->boundaries = boundaries->data();
+      }
+      *builtin_data = params.release();
+      return kTfLiteOk;
+    }
+    case BuiltinOperator_RANDOM_UNIFORM: {
+      auto params = safe_allocator.Allocate<TfLiteRandomParams>();
+      TF_LITE_ENSURE(error_reporter, params != nullptr);
+      if (const auto* random_uniform_params =
+              op->builtin_options_as_RandomOptions()) {
+        params->seed = random_uniform_params->seed();
+        params->seed2 = random_uniform_params->seed2();
+      }
+      *builtin_data = params.release();
+      return kTfLiteOk;
+    }
+    case BuiltinOperator_GELU: {
+      auto params = safe_allocator.Allocate<TfLiteGeluParams>();
+      TF_LITE_ENSURE(error_reporter, params != nullptr);
+      if (const auto* gelu_params = op->builtin_options_as_GeluOptions()) {
+        params->approximate = gelu_params->approximate();
+      }
+      *builtin_data = params.release();
+      return kTfLiteOk;
+    }
    // Below are the ops with no builtin_data structure.
    // TODO(aselle): Implement call in BuiltinOptions, but nullptrs are
    // ok for now, since there is no call implementation either.
@@ -825,6 +891,7 @@ TfLiteStatus ParseOpDataTfLite(const Operator* op, BuiltinOperator op_type,
    case BuiltinOperator_HASHTABLE_FIND:
    case BuiltinOperator_HASHTABLE_IMPORT:
    case BuiltinOperator_HASHTABLE_SIZE:
+    case BuiltinOperator_BROADCAST_ARGS:
      return kTfLiteOk;
    case BuiltinOperator_PLACEHOLDER_FOR_GREATER_OP_CODES:
      return kTfLiteError;
@@ -981,6 +1048,14 @@ TfLiteStatus ParseArgMin(const Operator* op, ErrorReporter* error_reporter,
  return kTfLiteOk;
 }

+// We have this parse function instead of directly returning kTfLiteOk from the
+// switch-case in ParseOpData because this function is used as part of the
+// selective registration for the OpResolver implementation in micro.
+TfLiteStatus ParseAssignVariable(const Operator*, ErrorReporter*,
+                                 BuiltinDataAllocator*, void**) {
+  return kTfLiteOk;
+}
+
 // We have this parse function instead of directly returning kTfLiteOk from the
 // switch-case in ParseOpData because this function is used as part of the
 // selective registration for the OpResolver implementation in micro.
@@ -1010,6 +1085,33 @@ TfLiteStatus ParseBatchToSpaceNd(const Operator*, ErrorReporter*,
  return kTfLiteOk;
 }

+TfLiteStatus ParseCallOnce(const Operator* op, ErrorReporter* error_reporter,
+                           BuiltinDataAllocator* allocator,
+                           void** builtin_data) {
+  CheckParsePointerParams(op, error_reporter, allocator, builtin_data);
+
+  SafeBuiltinDataAllocator safe_allocator(allocator);
+  std::unique_ptr<TfLiteCallOnceParams,
+                  SafeBuiltinDataAllocator::BuiltinDataDeleter>
+      params = safe_allocator.Allocate<TfLiteCallOnceParams>();
+  TF_LITE_ENSURE(error_reporter, params != nullptr);
+
+  const CallOnceOptions* schema_params =
+      op->builtin_options_as_CallOnceOptions();
+
+  if (schema_params != nullptr) {
+    params->init_subgraph_index = schema_params->init_subgraph_index();
+
+  } else {
+    // TODO(b/157480169): We should either return kTfLiteError or fill in some
+    // reasonable defaults in the params struct. We are not doing so until we
+    // better undertand the ramifications of changing the legacy behavior.
+  }
+
+  *builtin_data = params.release();
+  return kTfLiteOk;
+}
+
 // We have this parse function instead of directly returning kTfLiteOk from the
 // switch-case in ParseOpData because this function is used as part of the
 // selective registration for the OpResolver implementation in micro.
@@ -1372,6 +1474,30 @@ TfLiteStatus ParseHardSwish(const Operator*, ErrorReporter*,
  return kTfLiteOk;
 }

+TfLiteStatus ParseIf(const Operator* op, ErrorReporter* error_reporter,
+                     BuiltinDataAllocator* allocator, void** builtin_data) {
+  CheckParsePointerParams(op, error_reporter, allocator, builtin_data);
+
+  SafeBuiltinDataAllocator safe_allocator(allocator);
+  std::unique_ptr<TfLiteIfParams, SafeBuiltinDataAllocator::BuiltinDataDeleter>
+      params = safe_allocator.Allocate<TfLiteIfParams>();
+  TF_LITE_ENSURE(error_reporter, params != nullptr);
+
+  const IfOptions* schema_params = op->builtin_options_as_IfOptions();
+
+  if (schema_params != nullptr) {
+    params->then_subgraph_index = schema_params->then_subgraph_index();
+    params->else_subgraph_index = schema_params->else_subgraph_index();
+  } else {
+    // TODO(b/157480169): We should either return kTfLiteError or fill in some
+    // reasonable defaults in the params struct. We are not doing so until we
+    // better undertand the ramifications of changing the legacy behavior.
+  }
+
+  *builtin_data = params.release();
+  return kTfLiteOk;
+}
+
 TfLiteStatus ParseL2Normalization(const Operator* op,
                                  ErrorReporter* error_reporter,
                                  BuiltinDataAllocator* allocator,
@@ -1495,6 +1621,32 @@ TfLiteStatus ParseMinimum(const Operator*, ErrorReporter*,
  return kTfLiteOk;
 }

+TfLiteStatus ParseMirrorPad(const Operator* op, ErrorReporter* error_reporter,
+                            BuiltinDataAllocator* allocator,
+                            void** builtin_data) {
+  CheckParsePointerParams(op, error_reporter, allocator, builtin_data);
+
+  SafeBuiltinDataAllocator safe_allocator(allocator);
+  std::unique_ptr<TfLiteMirrorPaddingParams,
+                  SafeBuiltinDataAllocator::BuiltinDataDeleter>
+      params = safe_allocator.Allocate<TfLiteMirrorPaddingParams>();
+  TF_LITE_ENSURE(error_reporter, params != nullptr);
+
+  const MirrorPadOptions* schema_params =
+      op->builtin_options_as_MirrorPadOptions();
+
+  if (schema_params != nullptr) {
+    params->mode = ConvertMirrorPadding(schema_params->mode());
+  } else {
+    // TODO(b/157480169): We should either return kTfLiteError or fill in some
+    // reasonable defaults in the params struct. We are not doing so until we
+    // better undertand the ramifications of changing the legacy behavior.
+  }
+
+  *builtin_data = params.release();
+  return kTfLiteOk;
+}
+
 TfLiteStatus ParseMul(const Operator* op, ErrorReporter* error_reporter,
                      BuiltinDataAllocator* allocator, void** builtin_data) {
  CheckParsePointerParams(op, error_reporter, allocator, builtin_data);
@@ -1630,6 +1782,14 @@ TfLiteStatus ParseQuantize(const Operator*, ErrorReporter*,
  return kTfLiteOk;
 }

+// We have this parse function instead of directly returning kTfLiteOk from the
+// switch-case in ParseOpData because this function is used as part of the
+// selective registration for the OpResolver implementation in micro.
+TfLiteStatus ParseReadVariable(const Operator*, ErrorReporter*,
+                               BuiltinDataAllocator*, void**) {
+  return kTfLiteOk;
+}
+
 TfLiteStatus ParseReducer(const Operator* op, ErrorReporter* error_reporter,
                          BuiltinDataAllocator* allocator,
                          void** builtin_data) {
@@ -1810,6 +1970,14 @@ TfLiteStatus ParseSin(const Operator*, ErrorReporter*, BuiltinDataAllocator*,
  return kTfLiteOk;
 }

+// We have this parse function instead of directly returning kTfLiteOk from the
+// switch-case in ParseOpData because this function is used as part of the
+// selective registration for the OpResolver implementation in micro.
+TfLiteStatus ParseSlice(const Operator*, ErrorReporter*, BuiltinDataAllocator*,
+                        void**) {
+  return kTfLiteOk;
+}
+
 TfLiteStatus ParseSoftmax(const Operator* op, ErrorReporter* error_reporter,
                          BuiltinDataAllocator* allocator,
                          void** builtin_data) {
@@ -1916,6 +2084,29 @@ TfLiteStatus ParseSplitV(const Operator* op, ErrorReporter* error_reporter,
  return kTfLiteOk;
 }

+TfLiteStatus ParseUnidirectionalSequenceLSTM(const Operator* op,
+                                             ErrorReporter* error_reporter,
+                                             BuiltinDataAllocator* allocator,
+                                             void** builtin_data) {
+  CheckParsePointerParams(op, error_reporter, allocator, builtin_data);
+  SafeBuiltinDataAllocator safe_allocator(allocator);
+  auto params =
+      safe_allocator.Allocate<TfLiteUnidirectionalSequenceLSTMParams>();
+  TF_LITE_ENSURE(error_reporter, params != nullptr);
+  if (const auto* seq_lstm_params =
+          op->builtin_options_as_UnidirectionalSequenceLSTMOptions()) {
+    params->activation =
+        ConvertActivation(seq_lstm_params->fused_activation_function());
+    params->cell_clip = seq_lstm_params->cell_clip();
+    params->proj_clip = seq_lstm_params->proj_clip();
+    params->time_major = seq_lstm_params->time_major();
+    params->asymmetric_quantize_inputs =
+        seq_lstm_params->asymmetric_quantize_inputs();
+  }
+  *builtin_data = params.release();
+  return kTfLiteOk;
+}
+
 TfLiteStatus ParseSqueeze(const Operator* op, ErrorReporter* error_reporter,
                          BuiltinDataAllocator* allocator,
                          void** builtin_data) {
@@ -2115,6 +2306,37 @@ TfLiteStatus ParseUnpack(const Operator* op, ErrorReporter* error_reporter,
  return kTfLiteOk;
 }

+TfLiteStatus ParseVarHandle(const Operator* op, ErrorReporter* error_reporter,
+                            BuiltinDataAllocator* allocator,
+                            void** builtin_data) {
+  CheckParsePointerParams(op, error_reporter, allocator, builtin_data);
+
+  SafeBuiltinDataAllocator safe_allocator(allocator);
+  std::unique_ptr<TfLiteVarHandleParams,
+                  SafeBuiltinDataAllocator::BuiltinDataDeleter>
+      params = safe_allocator.Allocate<TfLiteVarHandleParams>();
+  TF_LITE_ENSURE(error_reporter, params != nullptr);
+
+  const VarHandleOptions* schema_params =
+      op->builtin_options_as_VarHandleOptions();
+
+  if (schema_params != nullptr) {
+    if (schema_params->container()) {
+      params->container = schema_params->container()->c_str();
+    }
+    if (schema_params->shared_name()) {
+      params->shared_name = schema_params->shared_name()->c_str();
+    }
+  } else {
+    // TODO(b/157480169): We should either return kTfLiteError or fill in some
+    // reasonable defaults in the params struct. We are not doing so until we
+    // better undertand the ramifications of changing the legacy behavior.
+  }
+
+  *builtin_data = params.release();
+  return kTfLiteOk;
+}
+
 // We have this parse function instead of directly returning kTfLiteOk from the
 // switch-case in ParseOpData because this function is used as part of the
 // selective registration for the OpResolver implementation in micro.
--- a/code/components/tflite-lib/tensorflow/lite/core/api/flatbuffer_conversions.h
+++ b/code/components/tflite-lib/tensorflow/lite/core/api/flatbuffer_conversions.h
@@ -1,4 +1,4 @@
-/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.

 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -84,6 +84,11 @@ TfLiteStatus ParseArgMax(const Operator* op, ErrorReporter* error_reporter,
 TfLiteStatus ParseArgMin(const Operator* op, ErrorReporter* error_reporter,
                         BuiltinDataAllocator* allocator, void** builtin_data);

+TfLiteStatus ParseAssignVariable(const Operator* op,
+                                 ErrorReporter* error_reporter,
+                                 BuiltinDataAllocator* allocator,
+                                 void** builtin_data);
+
 TfLiteStatus ParseBatchMatMul(const Operator* op, ErrorReporter* error_reporter,
                              BuiltinDataAllocator* allocator,
                              void** builtin_data);
@@ -93,6 +98,10 @@ TfLiteStatus ParseBatchToSpaceNd(const Operator* op,
                                 BuiltinDataAllocator* allocator,
                                 void** builtin_data);

+TfLiteStatus ParseCallOnce(const Operator* op, ErrorReporter* error_reporter,
+                           BuiltinDataAllocator* allocator,
+                           void** builtin_data);
+
 TfLiteStatus ParseCeil(const Operator* op, ErrorReporter* error_reporter,
                       BuiltinDataAllocator* allocator, void** builtin_data);

@@ -181,6 +190,9 @@ TfLiteStatus ParseHardSwish(const Operator* op, ErrorReporter* error_reporter,
                            BuiltinDataAllocator* allocator,
                            void** builtin_data);

+TfLiteStatus ParseIf(const Operator* op, ErrorReporter* error_reporter,
+                     BuiltinDataAllocator* allocator, void** builtin_data);
+
 TfLiteStatus ParseL2Normalization(const Operator* op,
                                  ErrorReporter* error_reporter,
                                  BuiltinDataAllocator* allocator,
@@ -226,6 +238,10 @@ TfLiteStatus ParseMaximum(const Operator* op, ErrorReporter* error_reporter,
 TfLiteStatus ParseMinimum(const Operator* op, ErrorReporter* error_reporter,
                          BuiltinDataAllocator* allocator, void** builtin_data);

+TfLiteStatus ParseMirrorPad(const Operator* op, ErrorReporter* error_reporter,
+                            BuiltinDataAllocator* allocator,
+                            void** builtin_data);
+
 TfLiteStatus ParseMul(const Operator* op, ErrorReporter* error_reporter,
                      BuiltinDataAllocator* allocator, void** builtin_data);

@@ -258,6 +274,11 @@ TfLiteStatus ParseQuantize(const Operator* op, ErrorReporter* error_reporter,
                           BuiltinDataAllocator* allocator,
                           void** builtin_data);

+TfLiteStatus ParseReadVariable(const Operator* op,
+                               ErrorReporter* error_reporter,
+                               BuiltinDataAllocator* allocator,
+                               void** builtin_data);
+
 TfLiteStatus ParseReducer(const Operator* op, ErrorReporter* error_reporter,
                          BuiltinDataAllocator* allocator, void** builtin_data);

@@ -292,6 +313,9 @@ TfLiteStatus ParseShape(const Operator* op, ErrorReporter* error_reporter,
 TfLiteStatus ParseSin(const Operator* op, ErrorReporter* error_reporter,
                      BuiltinDataAllocator* allocator, void** builtin_data);

+TfLiteStatus ParseSlice(const Operator* op, ErrorReporter* error_reporter,
+                        BuiltinDataAllocator* allocator, void** builtin_data);
+
 TfLiteStatus ParseSoftmax(const Operator* op, ErrorReporter* error_reporter,
                          BuiltinDataAllocator* allocator, void** builtin_data);

@@ -346,6 +370,15 @@ TfLiteStatus ParseTransposeConv(const Operator* op,
 TfLiteStatus ParseUnpack(const Operator* op, ErrorReporter* error_reporter,
                         BuiltinDataAllocator* allocator, void** builtin_data);

+TfLiteStatus ParseUnidirectionalSequenceLSTM(const Operator* op,
+                                             ErrorReporter* error_reporter,
+                                             BuiltinDataAllocator* allocator,
+                                             void** builtin_data);
+
+TfLiteStatus ParseVarHandle(const Operator* op, ErrorReporter* error_reporter,
+                            BuiltinDataAllocator* allocator,
+                            void** builtin_data);
+
 TfLiteStatus ParseZerosLike(const Operator* op, ErrorReporter* error_reporter,
                            BuiltinDataAllocator* allocator,
                            void** builtin_data);
--- a/code/components/tflite-lib/tensorflow/lite/core/api/op_resolver.cc
+++ b/code/components/tflite-lib/tensorflow/lite/core/api/op_resolver.cc
@@ -30,8 +30,7 @@ TfLiteStatus GetRegistrationFromOpCode(
  auto builtin_code = GetBuiltinCode(opcode);
  int version = opcode->version();

-  if (builtin_code > BuiltinOperator_MAX ||
-      builtin_code < BuiltinOperator_MIN) {
+  if (builtin_code > BuiltinOperator_MAX) {
    TF_LITE_REPORT_ERROR(
        error_reporter,
        "Op builtin_code out of range: %d. Are you using old TFLite binary "
--- a/code/components/tflite-lib/tensorflow/lite/core/api/op_resolver.h
+++ b/code/components/tflite-lib/tensorflow/lite/core/api/op_resolver.h
@@ -15,6 +15,7 @@ limitations under the License.
 #ifndef TENSORFLOW_LITE_CORE_API_OP_RESOLVER_H_
 #define TENSORFLOW_LITE_CORE_API_OP_RESOLVER_H_

+#include <functional>
 #include <memory>
 #include <vector>

@@ -36,16 +37,43 @@ class OpResolver {
  virtual const TfLiteRegistration* FindOp(const char* op,
                                           int version) const = 0;

+  using TfLiteDelegatePtrVector =
+      std::vector<std::unique_ptr<TfLiteDelegate, void (*)(TfLiteDelegate*)>>;
  // Returns optional delegates for resolving and handling ops in the flatbuffer
  // model. This may be used in addition to the standard TfLiteRegistration
  // lookup for graph resolution.
-  using TfLiteDelegatePtrVector =
-      std::vector<std::unique_ptr<TfLiteDelegate, void (*)(TfLiteDelegate*)>>;
+  // WARNING: This API is deprecated, GetDelegateCreators is preferred.
  virtual TfLiteDelegatePtrVector GetDelegates(int num_threads) const {
-    return TfLiteDelegatePtrVector();
+    return {};
  }

+  // Represent a function that creates a TfLite delegate instance.
+  using TfLiteDelegateCreator =
+      std::function<std::unique_ptr<TfLiteDelegate, void (*)(TfLiteDelegate*)>(
+          int /*num_threads*/)>;
+  using TfLiteDelegateCreators = std::vector<TfLiteDelegateCreator>;
+  // Returns a vector of delegate creators to create optional delegates for
+  // resolving and handling ops in the flatbuffer model. This may be used in
+  // addition to the standard TfLiteRegistration lookup for graph resolution.
+  virtual TfLiteDelegateCreators GetDelegateCreators() const { return {}; }
+
  virtual ~OpResolver() {}
+
+ private:
+  /// Returns true if this OpResolver may contain any "user defined" ops.
+  /// By "user defined" ops, we mean any op definitions other than those
+  /// contained in tflite::ops::builtin::BuiltinOpResolver.
+  ///
+  /// If this method returns true, it doesn't necessarily mean that the
+  /// OpResolver contains a user-defined op, just that the absence of
+  /// user-defined ops can't be guaranteed.
+  ///
+  /// Note that "user-defined" ops are not the same as "custom" ops;
+  /// BuiltinOpResolver may support certain "custom" ops, in addition to
+  /// "builtin" ops, and may not support all of the "builtin" op enum values.
+  virtual bool MayContainUserDefinedOps() const { return true; }
+
+  friend class OpResolverInternal;
 };

 // Handles the logic for converting between an OperatorCode structure extracted
--- a/code/components/tflite-lib/tensorflow/lite/core/api/tensor_utils.cc
+++ b/code/components/tflite-lib/tensorflow/lite/core/api/tensor_utils.cc
--- a/code/components/tflite-lib/tensorflow/lite/core/api/tensor_utils.h
+++ b/code/components/tflite-lib/tensorflow/lite/core/api/tensor_utils.h
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/bits.h
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/bits.h
@@ -0,0 +1,102 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_BITS_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_BITS_H_
+
+#ifdef __cplusplus
+#include <cstdint>
+
+extern "C" {
+#endif
+
+static inline int CountLeadingZeros32Slow(uint64_t n) {
+  int zeroes = 28;
+  if (n >> 16) zeroes -= 16, n >>= 16;
+  if (n >> 8) zeroes -= 8, n >>= 8;
+  if (n >> 4) zeroes -= 4, n >>= 4;
+  return "\4\3\2\2\1\1\1\1\0\0\0\0\0\0\0"[n] + zeroes;
+}
+
+static inline int CountLeadingZeros32(uint32_t n) {
+#if defined(_MSC_VER)
+  unsigned long result = 0;  // NOLINT(runtime/int)
+  if (_BitScanReverse(&result, n)) {
+    return 31 - result;
+  }
+  return 32;
+#elif defined(__GNUC__)
+
+  // Handle 0 as a special case because __builtin_clz(0) is undefined.
+  if (n == 0) {
+    return 32;
+  }
+  return __builtin_clz(n);
+#else
+  return CountLeadingZeros32Slow(n);
+#endif
+}
+
+static inline int MostSignificantBit32(uint32_t n) {
+  return 32 - CountLeadingZeros32(n);
+}
+
+static inline int CountLeadingZeros64Slow(uint64_t n) {
+  int zeroes = 60;
+  if (n >> 32) zeroes -= 32, n >>= 32;
+  if (n >> 16) zeroes -= 16, n >>= 16;
+  if (n >> 8) zeroes -= 8, n >>= 8;
+  if (n >> 4) zeroes -= 4, n >>= 4;
+  return "\4\3\2\2\1\1\1\1\0\0\0\0\0\0\0"[n] + zeroes;
+}
+
+static inline int CountLeadingZeros64(uint64_t n) {
+#if defined(_MSC_VER) && defined(_M_X64)
+  // MSVC does not have __builtin_clzll. Use _BitScanReverse64.
+  unsigned long result = 0;  // NOLINT(runtime/int)
+  if (_BitScanReverse64(&result, n)) {
+    return 63 - result;
+  }
+  return 64;
+#elif defined(_MSC_VER)
+  // MSVC does not have __builtin_clzll. Compose two calls to _BitScanReverse
+  unsigned long result = 0;  // NOLINT(runtime/int)
+  if ((n >> 32) && _BitScanReverse(&result, n >> 32)) {
+    return 31 - result;
+  }
+  if (_BitScanReverse(&result, n)) {
+    return 63 - result;
+  }
+  return 64;
+#elif defined(__GNUC__)
+
+  // Handle 0 as a special case because __builtin_clzll(0) is undefined.
+  if (n == 0) {
+    return 64;
+  }
+  return __builtin_clzll(n);
+#else
+  return CountLeadingZeros64Slow(n);
+#endif
+}
+
+static inline int MostSignificantBit64(uint64_t n) {
+  return 64 - CountLeadingZeros64(n);
+}
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_BITS_H_
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/fft.cc
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/fft.cc
@@ -0,0 +1,52 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/experimental/microfrontend/lib/fft.h"
+#include "tensorflow/lite/experimental/microfrontend/lib/kiss_fft_int16.h"
+
+#include <string.h>
+
+
+void FftCompute(struct FftState* state, const int16_t* input,
+                int input_scale_shift) {
+  const size_t input_size = state->input_size;
+  const size_t fft_size = state->fft_size;
+
+  int16_t* fft_input = state->input;
+  // First, scale the input by the given shift.
+  size_t i;
+  for (i = 0; i < input_size; ++i) {
+    fft_input[i] = static_cast<int16_t>(static_cast<uint16_t>(input[i])
+                                        << input_scale_shift);
+  }
+  // Zero out whatever else remains in the top part of the input.
+  for (; i < fft_size; ++i) {
+    fft_input[i] = 0;
+  }
+
+  // Apply the FFT.
+  kissfft_fixed16::kiss_fftr(
+    reinterpret_cast<kissfft_fixed16::kiss_fftr_cfg>(state->scratch),
+    state->input,
+    reinterpret_cast<kissfft_fixed16::kiss_fft_cpx*>(state->output));
+}
+
+void FftInit(struct FftState* state) {
+  // All the initialization is done in FftPopulateState()
+}
+
+void FftReset(struct FftState* state) {
+  memset(state->input, 0, state->fft_size * sizeof(*state->input));
+  memset(state->output, 0, (state->fft_size / 2 + 1) * sizeof(*state->output));
+}
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/fft.h
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/fft.h
@@ -0,0 +1,50 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_FFT_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_FFT_H_
+
+#include <stdint.h>
+#include <stdlib.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+struct complex_int16_t {
+  int16_t real;
+  int16_t imag;
+};
+
+struct FftState {
+  int16_t* input;
+  struct complex_int16_t* output;
+  size_t fft_size;
+  size_t input_size;
+  void* scratch;
+  size_t scratch_size;
+};
+
+void FftCompute(struct FftState* state, const int16_t* input,
+                int input_scale_shift);
+
+void FftInit(struct FftState* state);
+
+void FftReset(struct FftState* state);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_FFT_H_
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/fft_util.cc
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/fft_util.cc
@@ -0,0 +1,69 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/experimental/microfrontend/lib/fft_util.h"
+#include "tensorflow/lite/experimental/microfrontend/lib/kiss_fft_int16.h"
+
+#include <stdio.h>
+
+int FftPopulateState(struct FftState* state, size_t input_size) {
+  state->input_size = input_size;
+  state->fft_size = 1;
+  while (state->fft_size < state->input_size) {
+    state->fft_size <<= 1;
+  }
+
+  state->input = reinterpret_cast<int16_t*>(
+      malloc(state->fft_size * sizeof(*state->input)));
+  if (state->input == nullptr) {
+    fprintf(stderr, "Failed to alloc fft input buffer\n");
+    return 0;
+  }
+
+  state->output = reinterpret_cast<complex_int16_t*>(
+      malloc((state->fft_size / 2 + 1) * sizeof(*state->output) * 2));
+  if (state->output == nullptr) {
+    fprintf(stderr, "Failed to alloc fft output buffer\n");
+    return 0;
+  }
+
+  // Ask kissfft how much memory it wants.
+  size_t scratch_size = 0;
+  kissfft_fixed16::kiss_fftr_cfg kfft_cfg = kissfft_fixed16::kiss_fftr_alloc(
+      state->fft_size, 0, nullptr, &scratch_size);
+  if (kfft_cfg != nullptr) {
+    fprintf(stderr, "Kiss memory sizing failed.\n");
+    return 0;
+  }
+  state->scratch = malloc(scratch_size);
+  if (state->scratch == nullptr) {
+    fprintf(stderr, "Failed to alloc fft scratch buffer\n");
+    return 0;
+  }
+  state->scratch_size = scratch_size;
+  // Let kissfft configure the scratch space we just allocated
+  kfft_cfg = kissfft_fixed16::kiss_fftr_alloc(state->fft_size, 0,
+                                              state->scratch, &scratch_size);
+  if (kfft_cfg != state->scratch) {
+    fprintf(stderr, "Kiss memory preallocation strategy failed.\n");
+    return 0;
+  }
+  return 1;
+}
+
+void FftFreeStateContents(struct FftState* state) {
+  free(state->input);
+  free(state->output);
+  free(state->scratch);
+}
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/fft_util.h
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/fft_util.h
@@ -0,0 +1,34 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_FFT_UTIL_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_FFT_UTIL_H_
+
+#include "tensorflow/lite/experimental/microfrontend/lib/fft.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+// Prepares and FFT for the given input size.
+int FftPopulateState(struct FftState* state, size_t input_size);
+
+// Frees any allocated buffers.
+void FftFreeStateContents(struct FftState* state);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_FFT_UTIL_H_
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/filterbank.c
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/filterbank.c
@@ -0,0 +1,134 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/experimental/microfrontend/lib/filterbank.h"
+
+#include <string.h>
+
+#include "tensorflow/lite/experimental/microfrontend/lib/bits.h"
+
+void FilterbankConvertFftComplexToEnergy(struct FilterbankState* state,
+                                         struct complex_int16_t* fft_output,
+                                         int32_t* energy) {
+  const int end_index = state->end_index;
+  int i;
+  energy += state->start_index;
+  fft_output += state->start_index;
+  for (i = state->start_index; i < end_index; ++i) {
+    const int32_t real = fft_output->real;
+    const int32_t imag = fft_output->imag;
+    fft_output++;
+    const uint32_t mag_squared = (real * real) + (imag * imag);
+    *energy++ = mag_squared;
+  }
+}
+
+void FilterbankAccumulateChannels(struct FilterbankState* state,
+                                  const int32_t* energy) {
+  uint64_t* work = state->work;
+  uint64_t weight_accumulator = 0;
+  uint64_t unweight_accumulator = 0;
+
+  const int16_t* channel_frequency_starts = state->channel_frequency_starts;
+  const int16_t* channel_weight_starts = state->channel_weight_starts;
+  const int16_t* channel_widths = state->channel_widths;
+
+  int num_channels_plus_1 = state->num_channels + 1;
+  int i;
+  for (i = 0; i < num_channels_plus_1; ++i) {
+    const int32_t* magnitudes = energy + *channel_frequency_starts++;
+    const int16_t* weights = state->weights + *channel_weight_starts;
+    const int16_t* unweights = state->unweights + *channel_weight_starts++;
+    const int width = *channel_widths++;
+    int j;
+    for (j = 0; j < width; ++j) {
+      weight_accumulator += *weights++ * ((uint64_t)*magnitudes);
+      unweight_accumulator += *unweights++ * ((uint64_t)*magnitudes);
+      ++magnitudes;
+    }
+    *work++ = weight_accumulator;
+    weight_accumulator = unweight_accumulator;
+    unweight_accumulator = 0;
+  }
+}
+
+static uint16_t Sqrt32(uint32_t num) {
+  if (num == 0) {
+    return 0;
+  }
+  uint32_t res = 0;
+  int max_bit_number = 32 - MostSignificantBit32(num);
+  max_bit_number |= 1;
+  uint32_t bit = 1U << (31 - max_bit_number);
+  int iterations = (31 - max_bit_number) / 2 + 1;
+  while (iterations--) {
+    if (num >= res + bit) {
+      num -= res + bit;
+      res = (res >> 1U) + bit;
+    } else {
+      res >>= 1U;
+    }
+    bit >>= 2U;
+  }
+  // Do rounding - if we have the bits.
+  if (num > res && res != 0xFFFF) {
+    ++res;
+  }
+  return res;
+}
+
+static uint32_t Sqrt64(uint64_t num) {
+  // Take a shortcut and just use 32 bit operations if the upper word is all
+  // clear. This will cause a slight off by one issue for numbers close to 2^32,
+  // but it probably isn't going to matter (and gives us a big performance win).
+  if ((num >> 32) == 0) {
+    return Sqrt32((uint32_t)num);
+  }
+  uint64_t res = 0;
+  int max_bit_number = 64 - MostSignificantBit64(num);
+  max_bit_number |= 1;
+  uint64_t bit = 1ULL << (63 - max_bit_number);
+  int iterations = (63 - max_bit_number) / 2 + 1;
+  while (iterations--) {
+    if (num >= res + bit) {
+      num -= res + bit;
+      res = (res >> 1U) + bit;
+    } else {
+      res >>= 1U;
+    }
+    bit >>= 2U;
+  }
+  // Do rounding - if we have the bits.
+  if (num > res && res != 0xFFFFFFFFLL) {
+    ++res;
+  }
+  return res;
+}
+
+uint32_t* FilterbankSqrt(struct FilterbankState* state, int scale_down_shift) {
+  const int num_channels = state->num_channels;
+  const uint64_t* work = state->work + 1;
+  // Reuse the work buffer since we're fine clobbering it at this point to hold
+  // the output.
+  uint32_t* output = (uint32_t*)state->work;
+  int i;
+  for (i = 0; i < num_channels; ++i) {
+    *output++ = Sqrt64(*work++) >> scale_down_shift;
+  }
+  return (uint32_t*)state->work;
+}
+
+void FilterbankReset(struct FilterbankState* state) {
+  memset(state->work, 0, (state->num_channels + 1) * sizeof(*state->work));
+}
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/filterbank.h
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/filterbank.h
@@ -0,0 +1,63 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_FILTERBANK_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_FILTERBANK_H_
+
+#include <stdint.h>
+#include <stdlib.h>
+
+#include "tensorflow/lite/experimental/microfrontend/lib/fft.h"
+
+#define kFilterbankBits 12
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+struct FilterbankState {
+  int num_channels;
+  int start_index;
+  int end_index;
+  int16_t* channel_frequency_starts;
+  int16_t* channel_weight_starts;
+  int16_t* channel_widths;
+  int16_t* weights;
+  int16_t* unweights;
+  uint64_t* work;
+};
+
+// Converts the relevant complex values of an FFT output into energy (the
+// square magnitude).
+void FilterbankConvertFftComplexToEnergy(struct FilterbankState* state,
+                                         struct complex_int16_t* fft_output,
+                                         int32_t* energy);
+
+// Computes the mel-scale filterbank on the given energy array. Output is cached
+// internally - to fetch it, you need to call FilterbankSqrt.
+void FilterbankAccumulateChannels(struct FilterbankState* state,
+                                  const int32_t* energy);
+
+// Applies an integer square root to the 64 bit intermediate values of the
+// filterbank, and returns a pointer to them. Memory will be invalidated the
+// next time FilterbankAccumulateChannels is called.
+uint32_t* FilterbankSqrt(struct FilterbankState* state, int scale_down_shift);
+
+void FilterbankReset(struct FilterbankState* state);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_FILTERBANK_H_
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/filterbank_util.c
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/filterbank_util.c
@@ -0,0 +1,220 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/experimental/microfrontend/lib/filterbank_util.h"
+
+#include <assert.h>
+#include <math.h>
+#include <stdio.h>
+
+#define kFilterbankIndexAlignment 4
+#define kFilterbankChannelBlockSize 4
+
+void FilterbankFillConfigWithDefaults(struct FilterbankConfig* config) {
+  config->num_channels = 32;
+  config->lower_band_limit = 125.0f;
+  config->upper_band_limit = 7500.0f;
+  config->output_scale_shift = 7;
+}
+
+static float FreqToMel(float freq) { return 1127.0 * log1p(freq / 700.0); }
+
+static void CalculateCenterFrequencies(const int num_channels,
+                                       const float lower_frequency_limit,
+                                       const float upper_frequency_limit,
+                                       float* center_frequencies) {
+  assert(lower_frequency_limit >= 0.0f);
+  assert(upper_frequency_limit > lower_frequency_limit);
+
+  const float mel_low = FreqToMel(lower_frequency_limit);
+  const float mel_hi = FreqToMel(upper_frequency_limit);
+  const float mel_span = mel_hi - mel_low;
+  const float mel_spacing = mel_span / ((float)num_channels);
+  int i;
+  for (i = 0; i < num_channels; ++i) {
+    center_frequencies[i] = mel_low + (mel_spacing * (i + 1));
+  }
+}
+
+static void QuantizeFilterbankWeights(const float float_weight, int16_t* weight,
+                                      int16_t* unweight) {
+  *weight = floor(float_weight * (1 << kFilterbankBits) + 0.5);
+  *unweight = floor((1.0 - float_weight) * (1 << kFilterbankBits) + 0.5);
+}
+
+int FilterbankPopulateState(const struct FilterbankConfig* config,
+                            struct FilterbankState* state, int sample_rate,
+                            int spectrum_size) {
+  state->num_channels = config->num_channels;
+  const int num_channels_plus_1 = config->num_channels + 1;
+
+  // How should we align things to index counts given the byte alignment?
+  const int index_alignment =
+      (kFilterbankIndexAlignment < sizeof(int16_t)
+           ? 1
+           : kFilterbankIndexAlignment / sizeof(int16_t));
+
+  state->channel_frequency_starts =
+      malloc(num_channels_plus_1 * sizeof(*state->channel_frequency_starts));
+  state->channel_weight_starts =
+      malloc(num_channels_plus_1 * sizeof(*state->channel_weight_starts));
+  state->channel_widths =
+      malloc(num_channels_plus_1 * sizeof(*state->channel_widths));
+  state->work = malloc(num_channels_plus_1 * sizeof(*state->work));
+
+  float* center_mel_freqs =
+      malloc(num_channels_plus_1 * sizeof(*center_mel_freqs));
+  int16_t* actual_channel_starts =
+      malloc(num_channels_plus_1 * sizeof(*actual_channel_starts));
+  int16_t* actual_channel_widths =
+      malloc(num_channels_plus_1 * sizeof(*actual_channel_widths));
+
+  if (state->channel_frequency_starts == NULL ||
+      state->channel_weight_starts == NULL || state->channel_widths == NULL ||
+      center_mel_freqs == NULL || actual_channel_starts == NULL ||
+      actual_channel_widths == NULL) {
+    free(center_mel_freqs);
+    free(actual_channel_starts);
+    free(actual_channel_widths);
+    fprintf(stderr, "Failed to allocate channel buffers\n");
+    return 0;
+  }
+
+  CalculateCenterFrequencies(num_channels_plus_1, config->lower_band_limit,
+                             config->upper_band_limit, center_mel_freqs);
+
+  // Always exclude DC.
+  const float hz_per_sbin = 0.5 * sample_rate / ((float)spectrum_size - 1);
+  state->start_index = 1.5 + config->lower_band_limit / hz_per_sbin;
+  state->end_index = 0;  // Initialized to zero here, but actually set below.
+
+  // For each channel, we need to figure out what frequencies belong to it, and
+  // how much padding we need to add so that we can efficiently multiply the
+  // weights and unweights for accumulation. To simplify the multiplication
+  // logic, all channels will have some multiplication to do (even if there are
+  // no frequencies that accumulate to that channel) - they will be directed to
+  // a set of zero weights.
+  int chan_freq_index_start = state->start_index;
+  int weight_index_start = 0;
+  int needs_zeros = 0;
+
+  int chan;
+  for (chan = 0; chan < num_channels_plus_1; ++chan) {
+    // Keep jumping frequencies until we overshoot the bound on this channel.
+    int freq_index = chan_freq_index_start;
+    while (FreqToMel((freq_index)*hz_per_sbin) <= center_mel_freqs[chan]) {
+      ++freq_index;
+    }
+
+    const int width = freq_index - chan_freq_index_start;
+    actual_channel_starts[chan] = chan_freq_index_start;
+    actual_channel_widths[chan] = width;
+
+    if (width == 0) {
+      // This channel doesn't actually get anything from the frequencies, it's
+      // always zero. We need then to insert some 'zero' weights into the
+      // output, and just redirect this channel to do a single multiplication at
+      // this point. For simplicity, the zeros are placed at the beginning of
+      // the weights arrays, so we have to go and update all the other
+      // weight_starts to reflect this shift (but only once).
+      state->channel_frequency_starts[chan] = 0;
+      state->channel_weight_starts[chan] = 0;
+      state->channel_widths[chan] = kFilterbankChannelBlockSize;
+      if (!needs_zeros) {
+        needs_zeros = 1;
+        int j;
+        for (j = 0; j < chan; ++j) {
+          state->channel_weight_starts[j] += kFilterbankChannelBlockSize;
+        }
+        weight_index_start += kFilterbankChannelBlockSize;
+      }
+    } else {
+      // How far back do we need to go to ensure that we have the proper
+      // alignment?
+      const int aligned_start =
+          (chan_freq_index_start / index_alignment) * index_alignment;
+      const int aligned_width = (chan_freq_index_start - aligned_start + width);
+      const int padded_width =
+          (((aligned_width - 1) / kFilterbankChannelBlockSize) + 1) *
+          kFilterbankChannelBlockSize;
+
+      state->channel_frequency_starts[chan] = aligned_start;
+      state->channel_weight_starts[chan] = weight_index_start;
+      state->channel_widths[chan] = padded_width;
+      weight_index_start += padded_width;
+    }
+    chan_freq_index_start = freq_index;
+  }
+
+  // Allocate the two arrays to store the weights - weight_index_start contains
+  // the index of what would be the next set of weights that we would need to
+  // add, so that's how many weights we need to allocate.
+  state->weights = calloc(weight_index_start, sizeof(*state->weights));
+  state->unweights = calloc(weight_index_start, sizeof(*state->unweights));
+
+  // If the alloc failed, we also need to nuke the arrays.
+  if (state->weights == NULL || state->unweights == NULL) {
+    free(center_mel_freqs);
+    free(actual_channel_starts);
+    free(actual_channel_widths);
+    fprintf(stderr, "Failed to allocate weights or unweights\n");
+    return 0;
+  }
+
+  // Next pass, compute all the weights. Since everything has been memset to
+  // zero, we only need to fill in the weights that correspond to some frequency
+  // for a channel.
+  const float mel_low = FreqToMel(config->lower_band_limit);
+  for (chan = 0; chan < num_channels_plus_1; ++chan) {
+    int frequency = actual_channel_starts[chan];
+    const int num_frequencies = actual_channel_widths[chan];
+    const int frequency_offset =
+        frequency - state->channel_frequency_starts[chan];
+    const int weight_start = state->channel_weight_starts[chan];
+    const float denom_val = (chan == 0) ? mel_low : center_mel_freqs[chan - 1];
+
+    int j;
+    for (j = 0; j < num_frequencies; ++j, ++frequency) {
+      const float weight =
+          (center_mel_freqs[chan] - FreqToMel(frequency * hz_per_sbin)) /
+          (center_mel_freqs[chan] - denom_val);
+
+      // Make the float into an integer for the weights (and unweights).
+      const int weight_index = weight_start + frequency_offset + j;
+      QuantizeFilterbankWeights(weight, state->weights + weight_index,
+                                state->unweights + weight_index);
+    }
+    if (frequency > state->end_index) {
+      state->end_index = frequency;
+    }
+  }
+
+  free(center_mel_freqs);
+  free(actual_channel_starts);
+  free(actual_channel_widths);
+  if (state->end_index >= spectrum_size) {
+    fprintf(stderr, "Filterbank end_index is above spectrum size.\n");
+    return 0;
+  }
+  return 1;
+}
+
+void FilterbankFreeStateContents(struct FilterbankState* state) {
+  free(state->channel_frequency_starts);
+  free(state->channel_weight_starts);
+  free(state->channel_widths);
+  free(state->weights);
+  free(state->unweights);
+  free(state->work);
+}
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/filterbank_util.h
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/filterbank_util.h
@@ -0,0 +1,50 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_FILTERBANK_UTIL_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_FILTERBANK_UTIL_H_
+
+#include "tensorflow/lite/experimental/microfrontend/lib/filterbank.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+struct FilterbankConfig {
+  // number of frequency channel buckets for filterbank
+  int num_channels;
+  // maximum frequency to include
+  float upper_band_limit;
+  // minimum frequency to include
+  float lower_band_limit;
+  // unused
+  int output_scale_shift;
+};
+
+// Fills the frontendConfig with "sane" defaults.
+void FilterbankFillConfigWithDefaults(struct FilterbankConfig* config);
+
+// Allocates any buffers.
+int FilterbankPopulateState(const struct FilterbankConfig* config,
+                            struct FilterbankState* state, int sample_rate,
+                            int spectrum_size);
+
+// Frees any allocated buffers.
+void FilterbankFreeStateContents(struct FilterbankState* state);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_FILTERBANK_UTIL_H_
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/frontend.c
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/frontend.c
@@ -0,0 +1,72 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/experimental/microfrontend/lib/frontend.h"
+
+#include "tensorflow/lite/experimental/microfrontend/lib/bits.h"
+
+struct FrontendOutput FrontendProcessSamples(struct FrontendState* state,
+                                             const int16_t* samples,
+                                             size_t num_samples,
+                                             size_t* num_samples_read) {
+  struct FrontendOutput output;
+  output.values = NULL;
+  output.size = 0;
+
+  // Try to apply the window - if it fails, return and wait for more data.
+  if (!WindowProcessSamples(&state->window, samples, num_samples,
+                            num_samples_read)) {
+    return output;
+  }
+
+  // Apply the FFT to the window's output (and scale it so that the fixed point
+  // FFT can have as much resolution as possible).
+  int input_shift =
+      15 - MostSignificantBit32(state->window.max_abs_output_value);
+  FftCompute(&state->fft, state->window.output, input_shift);
+
+  // We can re-ruse the fft's output buffer to hold the energy.
+  int32_t* energy = (int32_t*)state->fft.output;
+
+  FilterbankConvertFftComplexToEnergy(&state->filterbank, state->fft.output,
+                                      energy);
+
+  FilterbankAccumulateChannels(&state->filterbank, energy);
+  uint32_t* scaled_filterbank = FilterbankSqrt(&state->filterbank, input_shift);
+
+  // Apply noise reduction.
+  NoiseReductionApply(&state->noise_reduction, scaled_filterbank);
+
+  if (state->pcan_gain_control.enable_pcan) {
+    PcanGainControlApply(&state->pcan_gain_control, scaled_filterbank);
+  }
+
+  // Apply the log and scale.
+  int correction_bits =
+      MostSignificantBit32(state->fft.fft_size) - 1 - (kFilterbankBits / 2);
+  uint16_t* logged_filterbank =
+      LogScaleApply(&state->log_scale, scaled_filterbank,
+                    state->filterbank.num_channels, correction_bits);
+
+  output.size = state->filterbank.num_channels;
+  output.values = logged_filterbank;
+  return output;
+}
+
+void FrontendReset(struct FrontendState* state) {
+  WindowReset(&state->window);
+  FftReset(&state->fft);
+  FilterbankReset(&state->filterbank);
+  NoiseReductionReset(&state->noise_reduction);
+}
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/frontend.h
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/frontend.h
@@ -0,0 +1,64 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_FRONTEND_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_FRONTEND_H_
+
+#include <stdint.h>
+#include <stdlib.h>
+
+#include "tensorflow/lite/experimental/microfrontend/lib/fft.h"
+#include "tensorflow/lite/experimental/microfrontend/lib/filterbank.h"
+#include "tensorflow/lite/experimental/microfrontend/lib/log_scale.h"
+#include "tensorflow/lite/experimental/microfrontend/lib/noise_reduction.h"
+#include "tensorflow/lite/experimental/microfrontend/lib/pcan_gain_control.h"
+#include "tensorflow/lite/experimental/microfrontend/lib/window.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+struct FrontendState {
+  struct WindowState window;
+  struct FftState fft;
+  struct FilterbankState filterbank;
+  struct NoiseReductionState noise_reduction;
+  struct PcanGainControlState pcan_gain_control;
+  struct LogScaleState log_scale;
+};
+
+struct FrontendOutput {
+  const uint16_t* values;
+  size_t size;
+};
+
+// Main entry point to processing frontend samples. Updates num_samples_read to
+// contain the number of samples that have been consumed from the input array.
+// Returns a struct containing the generated output. If not enough samples were
+// added to generate a feature vector, the returned size will be 0 and the
+// values pointer will be NULL. Note that the output pointer will be invalidated
+// as soon as FrontendProcessSamples is called again, so copy the contents
+// elsewhere if you need to use them later.
+struct FrontendOutput FrontendProcessSamples(struct FrontendState* state,
+                                             const int16_t* samples,
+                                             size_t num_samples,
+                                             size_t* num_samples_read);
+
+void FrontendReset(struct FrontendState* state);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_FRONTEND_H_
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/frontend_util.c
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/frontend_util.c
@@ -0,0 +1,85 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/experimental/microfrontend/lib/frontend_util.h"
+
+#include <stdio.h>
+#include <string.h>
+
+#include "tensorflow/lite/experimental/microfrontend/lib/bits.h"
+
+void FrontendFillConfigWithDefaults(struct FrontendConfig* config) {
+  WindowFillConfigWithDefaults(&config->window);
+  FilterbankFillConfigWithDefaults(&config->filterbank);
+  NoiseReductionFillConfigWithDefaults(&config->noise_reduction);
+  PcanGainControlFillConfigWithDefaults(&config->pcan_gain_control);
+  LogScaleFillConfigWithDefaults(&config->log_scale);
+}
+
+int FrontendPopulateState(const struct FrontendConfig* config,
+                          struct FrontendState* state, int sample_rate) {
+  memset(state, 0, sizeof(*state));
+
+  if (!WindowPopulateState(&config->window, &state->window, sample_rate)) {
+    fprintf(stderr, "Failed to populate window state\n");
+    return 0;
+  }
+
+  if (!FftPopulateState(&state->fft, state->window.size)) {
+    fprintf(stderr, "Failed to populate fft state\n");
+    return 0;
+  }
+  FftInit(&state->fft);
+
+  if (!FilterbankPopulateState(&config->filterbank, &state->filterbank,
+                               sample_rate, state->fft.fft_size / 2 + 1)) {
+    fprintf(stderr, "Failed to populate filterbank state\n");
+    return 0;
+  }
+
+  if (!NoiseReductionPopulateState(&config->noise_reduction,
+                                   &state->noise_reduction,
+                                   state->filterbank.num_channels)) {
+    fprintf(stderr, "Failed to populate noise reduction state\n");
+    return 0;
+  }
+
+  int input_correction_bits =
+      MostSignificantBit32(state->fft.fft_size) - 1 - (kFilterbankBits / 2);
+  if (!PcanGainControlPopulateState(
+          &config->pcan_gain_control, &state->pcan_gain_control,
+          state->noise_reduction.estimate, state->filterbank.num_channels,
+          state->noise_reduction.smoothing_bits, input_correction_bits)) {
+    fprintf(stderr, "Failed to populate pcan gain control state\n");
+    return 0;
+  }
+
+  if (!LogScalePopulateState(&config->log_scale, &state->log_scale)) {
+    fprintf(stderr, "Failed to populate log scale state\n");
+    return 0;
+  }
+
+  FrontendReset(state);
+
+  // All good, return a true value.
+  return 1;
+}
+
+void FrontendFreeStateContents(struct FrontendState* state) {
+  WindowFreeStateContents(&state->window);
+  FftFreeStateContents(&state->fft);
+  FilterbankFreeStateContents(&state->filterbank);
+  NoiseReductionFreeStateContents(&state->noise_reduction);
+  PcanGainControlFreeStateContents(&state->pcan_gain_control);
+}
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/frontend_util.h
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/frontend_util.h
@@ -0,0 +1,52 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_FRONTEND_UTIL_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_FRONTEND_UTIL_H_
+
+#include "tensorflow/lite/experimental/microfrontend/lib/fft_util.h"
+#include "tensorflow/lite/experimental/microfrontend/lib/filterbank_util.h"
+#include "tensorflow/lite/experimental/microfrontend/lib/frontend.h"
+#include "tensorflow/lite/experimental/microfrontend/lib/log_scale_util.h"
+#include "tensorflow/lite/experimental/microfrontend/lib/noise_reduction_util.h"
+#include "tensorflow/lite/experimental/microfrontend/lib/pcan_gain_control_util.h"
+#include "tensorflow/lite/experimental/microfrontend/lib/window_util.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+struct FrontendConfig {
+  struct WindowConfig window;
+  struct FilterbankConfig filterbank;
+  struct NoiseReductionConfig noise_reduction;
+  struct PcanGainControlConfig pcan_gain_control;
+  struct LogScaleConfig log_scale;
+};
+
+// Fills the frontendConfig with "sane" defaults.
+void FrontendFillConfigWithDefaults(struct FrontendConfig* config);
+
+// Allocates any buffers.
+int FrontendPopulateState(const struct FrontendConfig* config,
+                          struct FrontendState* state, int sample_rate);
+
+// Frees any allocated buffers.
+void FrontendFreeStateContents(struct FrontendState* state);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_FRONTEND_UTIL_H_
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/kiss_fft_common.h
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/kiss_fft_common.h
@@ -0,0 +1,48 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_KISS_FFT_COMMON_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_KISS_FFT_COMMON_H_
+
+// This header file should be included in all variants of kiss_fft_$type.{h,cc}
+// so that their sub-included source files do not mistakenly wrap libc header
+// files within their kissfft_$type namespaces.
+// E.g, This header avoids kissfft_int16.h containing:
+//   namespace kiss_fft_int16 {
+//     #include "kiss_fft.h"
+//   }
+// where kiss_fft_.h contains:
+//   #include <math.h>
+//
+// TRICK: By including the following header files here, their preprocessor
+// header guards prevent them being re-defined inside of the kiss_fft_$type
+// namespaces declared within the kiss_fft_$type.{h,cc} sources.
+// Note that the original kiss_fft*.h files are untouched since they
+// may be used in libraries that include them directly.
+
+#include <limits.h>
+#include <math.h>
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+
+#ifdef FIXED_POINT
+#include <sys/types.h>
+#endif
+
+#ifdef USE_SIMD
+#include <xmmintrin.h>
+#endif
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_KISS_FFT_COMMON_H_
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/kiss_fft_int16.cc
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/kiss_fft_int16.cc
@@ -0,0 +1,8 @@
+#include "tensorflow/lite/experimental/microfrontend/lib/kiss_fft_common.h"
+
+#define FIXED_POINT 16
+namespace kissfft_fixed16 {
+#include "kiss_fft.c"
+#include "tools/kiss_fftr.c"
+}  // namespace kissfft_fixed16
+#undef FIXED_POINT
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/kiss_fft_int16.h
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/kiss_fft_int16.h
@@ -0,0 +1,34 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_KISS_FFT_INT16_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_KISS_FFT_INT16_H_
+
+#include "tensorflow/lite/experimental/microfrontend/lib/kiss_fft_common.h"
+
+// Wrap 16-bit kiss fft in its own namespace. Enables us to link an application
+// with different kiss fft resultions (16/32 bit interger, float, double)
+// without getting a linker error.
+#define FIXED_POINT 16
+namespace kissfft_fixed16 {
+#include "kiss_fft.h"
+#include "tools/kiss_fftr.h"
+}  // namespace kissfft_fixed16
+#undef FIXED_POINT
+#undef kiss_fft_scalar
+#undef KISS_FFT_H
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_KISS_FFT_INT16_H_
+
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/log_lut.c
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/log_lut.c
@@ -0,0 +1,30 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/experimental/microfrontend/lib/log_lut.h"
+const uint16_t kLogLut[]
+#ifndef _MSC_VER
+    __attribute__((aligned(4)))
+#endif  // _MSV_VER
+    = {0,    224,  442,  654,  861,  1063, 1259, 1450, 1636, 1817, 1992, 2163,
+       2329, 2490, 2646, 2797, 2944, 3087, 3224, 3358, 3487, 3611, 3732, 3848,
+       3960, 4068, 4172, 4272, 4368, 4460, 4549, 4633, 4714, 4791, 4864, 4934,
+       5001, 5063, 5123, 5178, 5231, 5280, 5326, 5368, 5408, 5444, 5477, 5507,
+       5533, 5557, 5578, 5595, 5610, 5622, 5631, 5637, 5640, 5641, 5638, 5633,
+       5626, 5615, 5602, 5586, 5568, 5547, 5524, 5498, 5470, 5439, 5406, 5370,
+       5332, 5291, 5249, 5203, 5156, 5106, 5054, 5000, 4944, 4885, 4825, 4762,
+       4697, 4630, 4561, 4490, 4416, 4341, 4264, 4184, 4103, 4020, 3935, 3848,
+       3759, 3668, 3575, 3481, 3384, 3286, 3186, 3084, 2981, 2875, 2768, 2659,
+       2549, 2437, 2323, 2207, 2090, 1971, 1851, 1729, 1605, 1480, 1353, 1224,
+       1094, 963,  830,  695,  559,  421,  282,  142,  0,    0};
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/log_lut.h
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/log_lut.h
@@ -0,0 +1,40 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_LOG_LUT_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_LOG_LUT_H_
+
+#include <stdint.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+// Number of segments in the log lookup table. The table will be kLogSegments+1
+// in length (with some padding).
+#define kLogSegments 128
+#define kLogSegmentsLog2 7
+
+// Scale used by lookup table.
+#define kLogScale 65536
+#define kLogScaleLog2 16
+#define kLogCoeff 45426
+
+extern const uint16_t kLogLut[];
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_LOG_LUT_H_
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/log_scale.c
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/log_scale.c
@@ -0,0 +1,83 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/experimental/microfrontend/lib/log_scale.h"
+
+#include "tensorflow/lite/experimental/microfrontend/lib/bits.h"
+#include "tensorflow/lite/experimental/microfrontend/lib/log_lut.h"
+
+#define kuint16max 0x0000FFFF
+
+// The following functions implement integer logarithms of various sizes. The
+// approximation is calculated according to method described in
+//       www.inti.gob.ar/electronicaeinformatica/instrumentacion/utic/
+//       publicaciones/SPL2007/Log10-spl07.pdf
+// It first calculates log2 of the input and then converts it to natural
+// logarithm.
+
+static uint32_t Log2FractionPart(const uint32_t x, const uint32_t log2x) {
+  // Part 1
+  int32_t frac = x - (1LL << log2x);
+  if (log2x < kLogScaleLog2) {
+    frac <<= kLogScaleLog2 - log2x;
+  } else {
+    frac >>= log2x - kLogScaleLog2;
+  }
+  // Part 2
+  const uint32_t base_seg = frac >> (kLogScaleLog2 - kLogSegmentsLog2);
+  const uint32_t seg_unit =
+      (((uint32_t)1) << kLogScaleLog2) >> kLogSegmentsLog2;
+
+  const int32_t c0 = kLogLut[base_seg];
+  const int32_t c1 = kLogLut[base_seg + 1];
+  const int32_t seg_base = seg_unit * base_seg;
+  const int32_t rel_pos = ((c1 - c0) * (frac - seg_base)) >> kLogScaleLog2;
+  return frac + c0 + rel_pos;
+}
+
+static uint32_t Log(const uint32_t x, const uint32_t scale_shift) {
+  const uint32_t integer = MostSignificantBit32(x) - 1;
+  const uint32_t fraction = Log2FractionPart(x, integer);
+  const uint32_t log2 = (integer << kLogScaleLog2) + fraction;
+  const uint32_t round = kLogScale / 2;
+  const uint32_t loge = (((uint64_t)kLogCoeff) * log2 + round) >> kLogScaleLog2;
+  // Finally scale to our output scale
+  const uint32_t loge_scaled = ((loge << scale_shift) + round) >> kLogScaleLog2;
+  return loge_scaled;
+}
+
+uint16_t* LogScaleApply(struct LogScaleState* state, uint32_t* signal,
+                        int signal_size, int correction_bits) {
+  const int scale_shift = state->scale_shift;
+  uint16_t* output = (uint16_t*)signal;
+  uint16_t* ret = output;
+  int i;
+  for (i = 0; i < signal_size; ++i) {
+    uint32_t value = *signal++;
+    if (state->enable_log) {
+      if (correction_bits < 0) {
+        value >>= -correction_bits;
+      } else {
+        value <<= correction_bits;
+      }
+      if (value > 1) {
+        value = Log(value, scale_shift);
+      } else {
+        value = 0;
+      }
+    }
+    *output++ = (value < kuint16max) ? value : kuint16max;
+  }
+  return ret;
+}
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/log_scale.h
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/log_scale.h
@@ -0,0 +1,39 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_LOG_SCALE_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_LOG_SCALE_H_
+
+#include <stdint.h>
+#include <stdlib.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+struct LogScaleState {
+  int enable_log;
+  int scale_shift;
+};
+
+// Applies a fixed point logarithm to the signal and converts it to 16 bit. Note
+// that the signal array will be modified.
+uint16_t* LogScaleApply(struct LogScaleState* state, uint32_t* signal,
+                        int signal_size, int correction_bits);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_LOG_SCALE_H_
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/log_scale_util.c
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/log_scale_util.c
@@ -1,4 +1,4 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.

 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -12,11 +12,16 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License.
 ==============================================================================*/
+#include "tensorflow/lite/experimental/microfrontend/lib/log_scale_util.h"

-#ifndef TENSORFLOW_LITE_MICRO_BENCHMARKS_KEYWORD_SCRAMBLED_MODEL_DATA_H_
-#define TENSORFLOW_LITE_MICRO_BENCHMARKS_KEYWORD_SCRAMBLED_MODEL_DATA_H_
+void LogScaleFillConfigWithDefaults(struct LogScaleConfig* config) {
+  config->enable_log = 1;
+  config->scale_shift = 6;
+}

-extern const unsigned char g_keyword_scrambled_model_data[];
-extern const unsigned int g_keyword_scrambled_model_data_length;
-
-#endif  // TENSORFLOW_LITE_MICRO_BENCHMARKS_KEYWORD_SCRAMBLED_MODEL_DATA_H_
+int LogScalePopulateState(const struct LogScaleConfig* config,
+                          struct LogScaleState* state) {
+  state->enable_log = config->enable_log;
+  state->scale_shift = config->scale_shift;
+  return 1;
+}
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/log_scale_util.h
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/log_scale_util.h
@@ -0,0 +1,45 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_LOG_SCALE_UTIL_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_LOG_SCALE_UTIL_H_
+
+#include <stdint.h>
+#include <stdlib.h>
+
+#include "tensorflow/lite/experimental/microfrontend/lib/log_scale.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+struct LogScaleConfig {
+  // set to false (0) to disable this module
+  int enable_log;
+  // scale results by 2^(scale_shift)
+  int scale_shift;
+};
+
+// Populates the LogScaleConfig with "sane" default values.
+void LogScaleFillConfigWithDefaults(struct LogScaleConfig* config);
+
+// Allocates any buffers.
+int LogScalePopulateState(const struct LogScaleConfig* config,
+                          struct LogScaleState* state);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_LOG_SCALE_UTIL_H_
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/noise_reduction.c
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/noise_reduction.c
@@ -0,0 +1,51 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/experimental/microfrontend/lib/noise_reduction.h"
+
+#include <string.h>
+
+void NoiseReductionApply(struct NoiseReductionState* state, uint32_t* signal) {
+  int i;
+  for (i = 0; i < state->num_channels; ++i) {
+    const uint32_t smoothing =
+        ((i & 1) == 0) ? state->even_smoothing : state->odd_smoothing;
+    const uint32_t one_minus_smoothing = (1 << kNoiseReductionBits) - smoothing;
+
+    // Update the estimate of the noise.
+    const uint32_t signal_scaled_up = signal[i] << state->smoothing_bits;
+    uint32_t estimate =
+        (((uint64_t)signal_scaled_up * smoothing) +
+         ((uint64_t)state->estimate[i] * one_minus_smoothing)) >>
+        kNoiseReductionBits;
+    state->estimate[i] = estimate;
+
+    // Make sure that we can't get a negative value for the signal - estimate.
+    if (estimate > signal_scaled_up) {
+      estimate = signal_scaled_up;
+    }
+
+    const uint32_t floor =
+        ((uint64_t)signal[i] * state->min_signal_remaining) >>
+        kNoiseReductionBits;
+    const uint32_t subtracted =
+        (signal_scaled_up - estimate) >> state->smoothing_bits;
+    const uint32_t output = subtracted > floor ? subtracted : floor;
+    signal[i] = output;
+  }
+}
+
+void NoiseReductionReset(struct NoiseReductionState* state) {
+  memset(state->estimate, 0, sizeof(*state->estimate) * state->num_channels);
+}
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/noise_reduction.h
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/noise_reduction.h
@@ -0,0 +1,46 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_NOISE_REDUCTION_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_NOISE_REDUCTION_H_
+
+#define kNoiseReductionBits 14
+
+#include <stdint.h>
+#include <stdlib.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+struct NoiseReductionState {
+  int smoothing_bits;
+  uint16_t even_smoothing;
+  uint16_t odd_smoothing;
+  uint16_t min_signal_remaining;
+  int num_channels;
+  uint32_t* estimate;
+};
+
+// Removes stationary noise from each channel of the signal using a low pass
+// filter.
+void NoiseReductionApply(struct NoiseReductionState* state, uint32_t* signal);
+
+void NoiseReductionReset(struct NoiseReductionState* state);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_NOISE_REDUCTION_H_
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/noise_reduction_util.c
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/noise_reduction_util.c
@@ -0,0 +1,45 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/experimental/microfrontend/lib/noise_reduction_util.h"
+
+#include <stdio.h>
+
+void NoiseReductionFillConfigWithDefaults(struct NoiseReductionConfig* config) {
+  config->smoothing_bits = 10;
+  config->even_smoothing = 0.025;
+  config->odd_smoothing = 0.06;
+  config->min_signal_remaining = 0.05;
+}
+
+int NoiseReductionPopulateState(const struct NoiseReductionConfig* config,
+                                struct NoiseReductionState* state,
+                                int num_channels) {
+  state->smoothing_bits = config->smoothing_bits;
+  state->odd_smoothing = config->odd_smoothing * (1 << kNoiseReductionBits);
+  state->even_smoothing = config->even_smoothing * (1 << kNoiseReductionBits);
+  state->min_signal_remaining =
+      config->min_signal_remaining * (1 << kNoiseReductionBits);
+  state->num_channels = num_channels;
+  state->estimate = calloc(state->num_channels, sizeof(*state->estimate));
+  if (state->estimate == NULL) {
+    fprintf(stderr, "Failed to alloc estimate buffer\n");
+    return 0;
+  }
+  return 1;
+}
+
+void NoiseReductionFreeStateContents(struct NoiseReductionState* state) {
+  free(state->estimate);
+}
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/noise_reduction_util.h
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/noise_reduction_util.h
@@ -0,0 +1,50 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_NOISE_REDUCTION_UTIL_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_NOISE_REDUCTION_UTIL_H_
+
+#include "tensorflow/lite/experimental/microfrontend/lib/noise_reduction.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+struct NoiseReductionConfig {
+  // scale the signal up by 2^(smoothing_bits) before reduction
+  int smoothing_bits;
+  // smoothing coefficient for even-numbered channels
+  float even_smoothing;
+  // smoothing coefficient for odd-numbered channels
+  float odd_smoothing;
+  // fraction of signal to preserve (1.0 disables this module)
+  float min_signal_remaining;
+};
+
+// Populates the NoiseReductionConfig with "sane" default values.
+void NoiseReductionFillConfigWithDefaults(struct NoiseReductionConfig* config);
+
+// Allocates any buffers.
+int NoiseReductionPopulateState(const struct NoiseReductionConfig* config,
+                                struct NoiseReductionState* state,
+                                int num_channels);
+
+// Frees any allocated buffers.
+void NoiseReductionFreeStateContents(struct NoiseReductionState* state);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_NOISE_REDUCTION_UTIL_H_
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/pcan_gain_control.c
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/pcan_gain_control.c
@@ -0,0 +1,56 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/experimental/microfrontend/lib/pcan_gain_control.h"
+
+#include "tensorflow/lite/experimental/microfrontend/lib/bits.h"
+
+int16_t WideDynamicFunction(const uint32_t x, const int16_t* lut) {
+  if (x <= 2) {
+    return lut[x];
+  }
+
+  const int16_t interval = MostSignificantBit32(x);
+  lut += 4 * interval - 6;
+
+  const int16_t frac =
+      ((interval < 11) ? (x << (11 - interval)) : (x >> (interval - 11))) &
+      0x3FF;
+
+  int32_t result = ((int32_t)lut[2] * frac) >> 5;
+  result += (int32_t)((uint32_t)lut[1] << 5);
+  result *= frac;
+  result = (result + (1 << 14)) >> 15;
+  result += lut[0];
+  return (int16_t)result;
+}
+
+uint32_t PcanShrink(const uint32_t x) {
+  if (x < (2 << kPcanSnrBits)) {
+    return (x * x) >> (2 + 2 * kPcanSnrBits - kPcanOutputBits);
+  } else {
+    return (x >> (kPcanSnrBits - kPcanOutputBits)) - (1 << kPcanOutputBits);
+  }
+}
+
+void PcanGainControlApply(struct PcanGainControlState* state,
+                          uint32_t* signal) {
+  int i;
+  for (i = 0; i < state->num_channels; ++i) {
+    const uint32_t gain =
+        WideDynamicFunction(state->noise_estimate[i], state->gain_lut);
+    const uint32_t snr = ((uint64_t)signal[i] * gain) >> state->snr_shift;
+    signal[i] = PcanShrink(snr);
+  }
+}
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/pcan_gain_control.h
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/pcan_gain_control.h
@@ -0,0 +1,47 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_PCAN_GAIN_CONTROL_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_PCAN_GAIN_CONTROL_H_
+
+#include <stdint.h>
+#include <stdlib.h>
+
+#define kPcanSnrBits 12
+#define kPcanOutputBits 6
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+// Details at https://research.google/pubs/pub45911.pdf
+struct PcanGainControlState {
+  int enable_pcan;
+  uint32_t* noise_estimate;
+  int num_channels;
+  int16_t* gain_lut;
+  int32_t snr_shift;
+};
+
+int16_t WideDynamicFunction(const uint32_t x, const int16_t* lut);
+
+uint32_t PcanShrink(const uint32_t x);
+
+void PcanGainControlApply(struct PcanGainControlState* state, uint32_t* signal);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_PCAN_GAIN_CONTROL_H_
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/pcan_gain_control_util.c
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/pcan_gain_control_util.c
@@ -0,0 +1,92 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/experimental/microfrontend/lib/pcan_gain_control_util.h"
+
+#include <math.h>
+#include <stdio.h>
+
+#define kint16max 0x00007FFF
+
+void PcanGainControlFillConfigWithDefaults(
+    struct PcanGainControlConfig* config) {
+  config->enable_pcan = 0;
+  config->strength = 0.95;
+  config->offset = 80.0;
+  config->gain_bits = 21;
+}
+
+int16_t PcanGainLookupFunction(const struct PcanGainControlConfig* config,
+                               int32_t input_bits, uint32_t x) {
+  const float x_as_float = ((float)x) / ((uint32_t)1 << input_bits);
+  const float gain_as_float =
+      ((uint32_t)1 << config->gain_bits) *
+      powf(x_as_float + config->offset, -config->strength);
+
+  if (gain_as_float > kint16max) {
+    return kint16max;
+  }
+  return (int16_t)(gain_as_float + 0.5f);
+}
+
+int PcanGainControlPopulateState(const struct PcanGainControlConfig* config,
+                                 struct PcanGainControlState* state,
+                                 uint32_t* noise_estimate,
+                                 const int num_channels,
+                                 const uint16_t smoothing_bits,
+                                 const int32_t input_correction_bits) {
+  state->enable_pcan = config->enable_pcan;
+  if (!state->enable_pcan) {
+    return 1;
+  }
+  state->noise_estimate = noise_estimate;
+  state->num_channels = num_channels;
+  state->gain_lut = malloc(kWideDynamicFunctionLUTSize * sizeof(int16_t));
+  if (state->gain_lut == NULL) {
+    fprintf(stderr, "Failed to allocate gain LUT\n");
+    return 0;
+  }
+  state->snr_shift = config->gain_bits - input_correction_bits - kPcanSnrBits;
+
+  const int32_t input_bits = smoothing_bits - input_correction_bits;
+  state->gain_lut[0] = PcanGainLookupFunction(config, input_bits, 0);
+  state->gain_lut[1] = PcanGainLookupFunction(config, input_bits, 1);
+  state->gain_lut -= 6;
+  int interval;
+  for (interval = 2; interval <= kWideDynamicFunctionBits; ++interval) {
+    const uint32_t x0 = (uint32_t)1 << (interval - 1);
+    const uint32_t x1 = x0 + (x0 >> 1);
+    const uint32_t x2 =
+        (interval == kWideDynamicFunctionBits) ? x0 + (x0 - 1) : 2 * x0;
+
+    const int16_t y0 = PcanGainLookupFunction(config, input_bits, x0);
+    const int16_t y1 = PcanGainLookupFunction(config, input_bits, x1);
+    const int16_t y2 = PcanGainLookupFunction(config, input_bits, x2);
+
+    const int32_t diff1 = (int32_t)y1 - y0;
+    const int32_t diff2 = (int32_t)y2 - y0;
+    const int32_t a1 = 4 * diff1 - diff2;
+    const int32_t a2 = diff2 - a1;
+
+    state->gain_lut[4 * interval] = y0;
+    state->gain_lut[4 * interval + 1] = (int16_t)a1;
+    state->gain_lut[4 * interval + 2] = (int16_t)a2;
+  }
+  state->gain_lut += 6;
+  return 1;
+}
+
+void PcanGainControlFreeStateContents(struct PcanGainControlState* state) {
+  free(state->gain_lut);
+}
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/pcan_gain_control_util.h
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/pcan_gain_control_util.h
@@ -0,0 +1,57 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_PCAN_GAIN_CONTROL_UTIL_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_PCAN_GAIN_CONTROL_UTIL_H_
+
+#include "tensorflow/lite/experimental/microfrontend/lib/pcan_gain_control.h"
+
+#define kWideDynamicFunctionBits 32
+#define kWideDynamicFunctionLUTSize (4 * kWideDynamicFunctionBits - 3)
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+struct PcanGainControlConfig {
+  // set to false (0) to disable this module
+  int enable_pcan;
+  // gain normalization exponent (0.0 disables, 1.0 full strength)
+  float strength;
+  // positive value added in the normalization denominator
+  float offset;
+  // number of fractional bits in the gain
+  int gain_bits;
+};
+
+void PcanGainControlFillConfigWithDefaults(
+    struct PcanGainControlConfig* config);
+
+int16_t PcanGainLookupFunction(const struct PcanGainControlConfig* config,
+                               int32_t input_bits, uint32_t x);
+
+int PcanGainControlPopulateState(const struct PcanGainControlConfig* config,
+                                 struct PcanGainControlState* state,
+                                 uint32_t* noise_estimate,
+                                 const int num_channels,
+                                 const uint16_t smoothing_bits,
+                                 const int32_t input_correction_bits);
+
+void PcanGainControlFreeStateContents(struct PcanGainControlState* state);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_PCAN_GAIN_CONTROL_UTIL_H_
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/window.c
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/window.c
@@ -0,0 +1,70 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/experimental/microfrontend/lib/window.h"
+
+#include <string.h>
+
+int WindowProcessSamples(struct WindowState* state, const int16_t* samples,
+                         size_t num_samples, size_t* num_samples_read) {
+  const int size = state->size;
+
+  // Copy samples from the samples buffer over to our local input.
+  size_t max_samples_to_copy = state->size - state->input_used;
+  if (max_samples_to_copy > num_samples) {
+    max_samples_to_copy = num_samples;
+  }
+  memcpy(state->input + state->input_used, samples,
+         max_samples_to_copy * sizeof(*samples));
+  *num_samples_read = max_samples_to_copy;
+  state->input_used += max_samples_to_copy;
+
+  if (state->input_used < state->size) {
+    // We don't have enough samples to compute a window.
+    return 0;
+  }
+
+  // Apply the window to the input.
+  const int16_t* coefficients = state->coefficients;
+  const int16_t* input = state->input;
+  int16_t* output = state->output;
+  int i;
+  int16_t max_abs_output_value = 0;
+  for (i = 0; i < size; ++i) {
+    int16_t new_value =
+        (((int32_t)*input++) * *coefficients++) >> kFrontendWindowBits;
+    *output++ = new_value;
+    if (new_value < 0) {
+      new_value = -new_value;
+    }
+    if (new_value > max_abs_output_value) {
+      max_abs_output_value = new_value;
+    }
+  }
+  // Shuffle the input down by the step size, and update how much we have used.
+  memmove(state->input, state->input + state->step,
+          sizeof(*state->input) * (state->size - state->step));
+  state->input_used -= state->step;
+  state->max_abs_output_value = max_abs_output_value;
+
+  // Indicate that the output buffer is valid for the next stage.
+  return 1;
+}
+
+void WindowReset(struct WindowState* state) {
+  memset(state->input, 0, state->size * sizeof(*state->input));
+  memset(state->output, 0, state->size * sizeof(*state->output));
+  state->input_used = 0;
+  state->max_abs_output_value = 0;
+}
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/window.h
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/window.h
@@ -0,0 +1,49 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_WINDOW_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_WINDOW_H_
+
+#include <stdint.h>
+#include <stdlib.h>
+
+#define kFrontendWindowBits 12
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+struct WindowState {
+  size_t size;
+  int16_t* coefficients;
+  size_t step;
+
+  int16_t* input;
+  size_t input_used;
+  int16_t* output;
+  int16_t max_abs_output_value;
+};
+
+// Applies a window to the samples coming in, stepping forward at the given
+// rate.
+int WindowProcessSamples(struct WindowState* state, const int16_t* samples,
+                         size_t num_samples, size_t* num_samples_read);
+
+void WindowReset(struct WindowState* state);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_WINDOW_H_
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/window_util.c
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/window_util.c
@@ -0,0 +1,73 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/experimental/microfrontend/lib/window_util.h"
+
+#include <math.h>
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+
+// Some platforms don't have M_PI
+#ifndef M_PI
+#define M_PI 3.14159265358979323846
+#endif
+
+void WindowFillConfigWithDefaults(struct WindowConfig* config) {
+  config->size_ms = 25;
+  config->step_size_ms = 10;
+}
+
+int WindowPopulateState(const struct WindowConfig* config,
+                        struct WindowState* state, int sample_rate) {
+  state->size = config->size_ms * sample_rate / 1000;
+  state->step = config->step_size_ms * sample_rate / 1000;
+
+  state->coefficients = malloc(state->size * sizeof(*state->coefficients));
+  if (state->coefficients == NULL) {
+    fprintf(stderr, "Failed to allocate window coefficients\n");
+    return 0;
+  }
+
+  // Populate the window values.
+  const float arg = M_PI * 2.0 / ((float)state->size);
+  int i;
+  for (i = 0; i < state->size; ++i) {
+    float float_value = 0.5 - (0.5 * cos(arg * (i + 0.5)));
+    // Scale it to fixed point and round it.
+    state->coefficients[i] =
+        floor(float_value * (1 << kFrontendWindowBits) + 0.5);
+  }
+
+  state->input_used = 0;
+  state->input = malloc(state->size * sizeof(*state->input));
+  if (state->input == NULL) {
+    fprintf(stderr, "Failed to allocate window input\n");
+    return 0;
+  }
+
+  state->output = malloc(state->size * sizeof(*state->output));
+  if (state->output == NULL) {
+    fprintf(stderr, "Failed to allocate window output\n");
+    return 0;
+  }
+
+  return 1;
+}
+
+void WindowFreeStateContents(struct WindowState* state) {
+  free(state->coefficients);
+  free(state->input);
+  free(state->output);
+}
--- a/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/window_util.h
+++ b/code/components/tflite-lib/tensorflow/lite/experimental/microfrontend/lib/window_util.h
@@ -0,0 +1,45 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_WINDOW_UTIL_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_WINDOW_UTIL_H_
+
+#include "tensorflow/lite/experimental/microfrontend/lib/window.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+struct WindowConfig {
+  // length of window frame in milliseconds
+  size_t size_ms;
+  // length of step for next frame in milliseconds
+  size_t step_size_ms;
+};
+
+// Populates the WindowConfig with "sane" default values.
+void WindowFillConfigWithDefaults(struct WindowConfig* config);
+
+// Allocates any buffers.
+int WindowPopulateState(const struct WindowConfig* config,
+                        struct WindowState* state, int sample_rate);
+
+// Frees any allocated buffers.
+void WindowFreeStateContents(struct WindowState* state);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICROFRONTEND_LIB_WINDOW_UTIL_H_
--- a/code/components/tflite-lib/tensorflow/lite/kernels/internal/common.h
+++ b/code/components/tflite-lib/tensorflow/lite/kernels/internal/common.h
@@ -75,6 +75,7 @@ float ActivationFunction(float x) {
 inline void BiasAndClamp(float clamp_min, float clamp_max, int bias_size,
                         const float* bias_data, int array_size,
                         float* array_data) {
+  if (bias_size == 0) return;
  // Note: see b/132215220: in May 2019 we thought it would be OK to replace
  // this with the Eigen one-liner:
  //   return (array.colwise() + bias).cwiseMin(clamp_max).cwiseMin(clamp_max).
@@ -138,6 +139,100 @@ inline void BiasAndClamp(float clamp_min, float clamp_max, int bias_size,
 #endif
 }

+// Single-rounding MultiplyByQuantizedMultiplier
+#if TFLITE_SINGLE_ROUNDING
+inline int32_t MultiplyByQuantizedMultiplier(int32_t x,
+                                             int32_t quantized_multiplier,
+                                             int shift) {
+  TFLITE_DCHECK(quantized_multiplier >= 0);
+  TFLITE_DCHECK(shift >= -31 && shift <= 30);
+
+  const int64_t total_shift = 31 - shift;
+  const int64_t round = static_cast<int64_t>(1) << (total_shift - 1);
+  int64_t result = x * static_cast<int64_t>(quantized_multiplier) + round;
+  result = result >> total_shift;
+
+  TFLITE_DCHECK(result >= std::numeric_limits<int32_t>::min() &&
+                result <= std::numeric_limits<int32_t>::max());
+  return static_cast<int32_t>(result);
+}
+
+inline int32_t MultiplyByQuantizedMultiplierSmallerThanOneExp(
+    int32_t x, int32_t quantized_multiplier, int shift) {
+  TFLITE_DCHECK_LE(shift, 0);
+  return MultiplyByQuantizedMultiplier(x, quantized_multiplier, shift);
+}
+
+inline int32_t MultiplyByQuantizedMultiplierGreaterThanOne(
+    int32_t x, int32_t quantized_multiplier, int shift) {
+  TFLITE_DCHECK_GE(shift, 0);
+  return MultiplyByQuantizedMultiplier(x, quantized_multiplier, shift);
+}
+
+inline int32_t MultiplyByQuantizedMultiplier(int64_t x,
+                                             int32_t quantized_multiplier,
+                                             int shift) {
+  // Inputs:
+  // - quantized_multiplier has fixed point at bit 31
+  // - shift is -31 to +7 (negative for right shift)
+  //
+  // Assumptions: The following input ranges are assumed
+  // - quantize_scale>=0  (the usual range is (1<<30) to (1>>31)-1)
+  // - scaling is chosen so final scaled result fits in int32_t
+  // - input x is in the range -(1<<47) <= x < (1<<47)
+  TFLITE_DCHECK(quantized_multiplier >= 0);
+  TFLITE_DCHECK(shift >= -31 && shift < 8);
+  TFLITE_DCHECK(x >= -(static_cast<int64_t>(1) << 47) &&
+                x < (static_cast<int64_t>(1) << 47));
+
+  const int32_t reduced_multiplier =
+      (quantized_multiplier < 0x7FFF0000)
+          ? ((quantized_multiplier + (1 << 15)) >> 16)
+          : 0x7FFF;
+  const int64_t total_shift = 15 - shift;
+  const int64_t round = static_cast<int64_t>(1) << (total_shift - 1);
+  int64_t result = x * static_cast<int64_t>(reduced_multiplier) + round;
+  result = result >> total_shift;
+
+  TFLITE_DCHECK(result >= std::numeric_limits<int32_t>::min() &&
+                result <= std::numeric_limits<int32_t>::max());
+  return static_cast<int32_t>(result);
+}
+
+#ifdef USE_NEON
+inline int32x4x4_t MultiplyByQuantizedMultiplier4Rows(
+    int32x4x4_t input_val, int32_t quantized_multiplier, int shift) {
+  TFLITE_DCHECK(quantized_multiplier >= 0);
+
+  const int right_shift = std::min(-1, shift);
+  const int left_shift = shift - right_shift;
+
+  const int32x4_t multiplier_dup = vdupq_n_s32(quantized_multiplier);
+  const int32x4_t left_shift_dup = vdupq_n_s32(left_shift);
+  const int32x4_t right_shift_dup = vdupq_n_s32(right_shift);
+
+  int32x4x4_t result;
+  result.val[0] = vrshlq_s32(
+      vqdmulhq_s32(vshlq_s32(input_val.val[0], left_shift_dup), multiplier_dup),
+      right_shift_dup);
+
+  result.val[1] = vrshlq_s32(
+      vqdmulhq_s32(vshlq_s32(input_val.val[1], left_shift_dup), multiplier_dup),
+      right_shift_dup);
+
+  result.val[2] = vrshlq_s32(
+      vqdmulhq_s32(vshlq_s32(input_val.val[2], left_shift_dup), multiplier_dup),
+      right_shift_dup);
+
+  result.val[3] = vrshlq_s32(
+      vqdmulhq_s32(vshlq_s32(input_val.val[3], left_shift_dup), multiplier_dup),
+      right_shift_dup);
+
+  return result;
+}
+#endif  // USE_NEON
+// Double-rounding MultiplyByQuantizedMultiplier
+#else
 inline int32_t MultiplyByQuantizedMultiplierSmallerThanOneExp(
    int32_t x, int32_t quantized_multiplier, int left_shift) {
  using gemmlowp::RoundingDivideByPOT;
@@ -224,7 +319,8 @@ inline int32x4x4_t MultiplyByQuantizedMultiplier4Rows(

  return result;
 }
-#endif
+#endif  // USE_NEON
+#endif  // TFLITE_SINGLE_ROUNDING

 template <typename T>
 int CountLeadingZeros(T integer_input) {
@@ -279,81 +375,125 @@ inline Integer FloorLog2(Integer n) {
  }
 }

-// generate INT16 LUT for function(), e.g., table exp(x) and 1/(1+x) used in
-// softmax
-// func - the function to build the LUT for (e.g exp(x))
-// min,max - table limits
-// table - pointer to buffer
-// num - number of elements in the LUT
-inline void gen_lut(double (*func)(double), double min, double max,
-                    int16_t* table, const int num) {
-  // size of table should equal to num + 1
-  // last element only for slope calculation
-  double step = (max - min) / (num - 1);
-  double half_step = step / 2.0;
-  for (int i = 0; i < num - 1; i++) {
-    double sample_val = TfLiteRound(func(min + i * step) * 32768.0);
-    double midpoint_interp_val =
-        TfLiteRound((func(min + (i + 1) * step) * 32768.0 +
-                     TfLiteRound(func(min + i * step) * 32768.0)) /
-                    2.0);
-    double midpoint_val =
-        TfLiteRound(func(min + i * step + half_step) * 32768.0);
-    double midpoint_err = midpoint_interp_val - midpoint_val;
-    double bias = TfLiteRound(midpoint_err / 2.0);
-    table[i] = std::min<double>(std::max<double>(sample_val - bias, -32768.0),
-                                32767.0);
-  }
-  table[num - 1] = std::min<double>(
-      std::max<double>(TfLiteRound(func(max) * 32768.0), -32768.0), 32767.0);
+// The size of the LUT depends on the type of input. For int8 inputs a simple
+// 256 entries LUT is used. For int16 inputs the high 9 bits are used for
+// indexing and the 7 remaining bits are used for interpolation. We thus use a
+// 513-entries LUT for int16 cases, 512 for the 9-bit indexing and 1 extra entry
+// to interpolate the last value.
+template <typename LutInT>
+constexpr int lut_size() {
+  static_assert(std::is_same<LutInT, int8_t>::value ||
+                    std::is_same<LutInT, int16_t>::value,
+                "Only LUTs with int8 or int16 inputs are supported.");
+  return std::is_same<LutInT, int8_t>::value ? 256 : 513;
 }

-// generate INT16 LUT for function(), e.g., table exp(x) and 1/(1+x) used in
-// softmax
-// func - the function to build the LUT for (e.g exp(x))
-// min,max - table limits
-// table - pointer to buffer
-// num - number of elements in the LUT
-inline void gen_lut(float (*func)(float), float min, float max, int16_t* table,
-                    const int num) {
-  // size of table should equal to num + 1
-  // last element only for slope calculation
-  float step = (max - min) / (num - 1);
-  float half_step = step / 2.0f;
-  for (int i = 0; i < num - 1; i++) {
-    float sample_val = TfLiteRound(func(min + i * step) * 32768.0f);
-    float midpoint_interp_val =
-        TfLiteRound((func(min + (i + 1) * step) * 32768.0f +
-                     TfLiteRound(func(min + i * step) * 32768.0f)) /
-                    2.0f);
-    float midpoint_val =
-        TfLiteRound(func(min + i * step + half_step) * 32768.0f);
-    float midpoint_err = midpoint_interp_val - midpoint_val;
-    float bias = TfLiteRound(midpoint_err / 2.0f);
-    table[i] = std::min<float>(std::max<float>(sample_val - bias, -32768.0f),
-                               32767.0f);
+// Generate a LUT for 'func' which can be used to approximate functions like
+// exp, log, ...
+//
+// - func: the function to build the LUT for (e.g exp(x))
+// - input_min, input_max: range of the func inputs
+// - output_min, output_max: range of the func outputs
+// - lut: pointer to the LUT table to fill, the table must be of size
+// lut_size<LutInT>()
+template <typename FloatT, typename LutInT, typename LutOutT>
+inline void gen_lut(FloatT (*func)(FloatT), FloatT input_min, FloatT input_max,
+                    FloatT output_min, FloatT output_max, LutOutT* lut) {
+  static_assert(std::is_same<LutInT, int8_t>::value ||
+                    std::is_same<LutInT, int16_t>::value,
+                "Only LUTs with int8 or int16 inputs are supported.");
+  static_assert(std::is_same<LutOutT, int8_t>::value ||
+                    std::is_same<LutOutT, int16_t>::value,
+                "Only LUTs with int8 or int16 outputs are supported.");
+  static_assert(std::is_floating_point<FloatT>::value,
+                "FloatT must be a floating-point type.");
+
+  const int nb_steps = std::is_same<LutInT, int8_t>::value ? 256 : 512;
+  const FloatT step = (input_max - input_min) / nb_steps;
+  const FloatT half_step = step / 2;
+  const FloatT output_scaling_inv =
+      static_cast<FloatT>(std::numeric_limits<LutOutT>::max() -
+                          std::numeric_limits<LutOutT>::min() + 1) /
+      (output_max - output_min);
+  const FloatT table_min =
+      static_cast<FloatT>(std::numeric_limits<LutOutT>::min());
+  const FloatT table_max =
+      static_cast<FloatT>(std::numeric_limits<LutOutT>::max());
+
+  for (int i = 0; i < nb_steps; i++) {
+    const FloatT val = func(input_min + i * step);
+    const FloatT val_midpoint = func(input_min + i * step + half_step);
+    const FloatT val_next = func(input_min + (i + 1) * step);
+
+    const FloatT sample_val = TfLiteRound(val * output_scaling_inv);
+    const FloatT midpoint_interp_val =
+        TfLiteRound((val_next * output_scaling_inv +
+                     TfLiteRound(val * output_scaling_inv)) /
+                    2);
+    const FloatT midpoint_val = TfLiteRound(val_midpoint * output_scaling_inv);
+    const FloatT midpoint_err = midpoint_interp_val - midpoint_val;
+    const FloatT bias = TfLiteRound(midpoint_err / 2);
+
+    lut[i] = static_cast<LutOutT>(std::min<FloatT>(
+        std::max<FloatT>(sample_val - bias, table_min), table_max));
+  }
+
+  const bool with_extra_interpolation_value =
+      std::is_same<LutInT, int16_t>::value;
+  if (with_extra_interpolation_value) {
+    lut[nb_steps] = static_cast<LutOutT>(std::min<FloatT>(
+        std::max<FloatT>(TfLiteRound(func(input_max) * output_scaling_inv),
+                         table_min),
+        table_max));
  }
-  table[num - 1] = std::min<float>(
-      std::max<float>(TfLiteRound(func(max) * 32768.0f), -32768.0f), 32767.0f);
 }

-// int16_t func table lookup, e.g., lookup exp() and 1/(1+x) used in softmax
-inline int16_t generic_int16_table_lookup(int16_t value, const int16_t* lut) {
-  // 512 base value, lut[513] only for calculate slope
-  uint16_t index = static_cast<uint16_t>(256 + (value >> 7));
+// LUT must have 513 values
+template <typename LutOutT>
+inline LutOutT lut_lookup_with_interpolation(int16_t value,
+                                             const LutOutT* lut) {
+  static_assert(std::is_same<LutOutT, int8_t>::value ||
+                    std::is_same<LutOutT, int16_t>::value,
+                "Only LUTs with int8 or int16 outputs are supported.");
+  // 512 base values, lut[513] is only used to calculate the slope
+  const uint16_t index = static_cast<uint16_t>(256 + (value >> 7));
  assert(index < 512 && "LUT index out of range.");
-  int16_t offset = value & 0x7f;
+  const int16_t offset = value & 0x7f;

-  // base and slope are Q0.15
-  int16_t base = lut[index];
-  int16_t slope = lut[index + 1] - lut[index];
+  // Base and slope are Q0.x
+  const LutOutT base = lut[index];
+  const LutOutT slope = lut[index + 1] - lut[index];

-  // Q0.15 * Q0.7 = Q0.22
-  // Round and convert from Q0.22 to Q0.15
-  int32_t delta = (static_cast<int32_t>(slope) * offset + 64) >> 7;
+  // Q0.x * Q0.7 = Q0.(x + 7)
+  // Round and convert from Q0.(x + 7) to Q0.x
+  const int delta = (slope * offset + 64) >> 7;

  // Q0.15 + Q0.15
-  return base + delta;
+  return static_cast<LutOutT>(base + delta);
+}
+
+// int16_t -> int16_t table lookup with interpolation
+// LUT must have 513 values
+inline int16_t lut_lookup(int16_t value, const int16_t* lut) {
+  return lut_lookup_with_interpolation(value, lut);
+}
+
+// int16_t -> int8_t table lookup with interpolation
+// LUT must have 513 values
+inline int8_t lut_lookup(int16_t value, const int8_t* lut) {
+  return lut_lookup_with_interpolation(value, lut);
+}
+
+// int8_t -> int8_t table lookup without interpolation
+// LUT must have 256 values
+inline int8_t lut_lookup(int8_t value, const int8_t* lut) {
+  return lut[128 + value];
+}
+
+// int8_t -> int16_t table lookup without interpolation
+// LUT must have 256 values
+inline int16_t lut_lookup(int8_t value, const int16_t* lut) {
+  return lut[128 + value];
 }

 // Table of sigmoid(i/24) at 0.16 format - 256 elements.
@@ -575,7 +715,8 @@ log_x_for_x_greater_than_or_equal_to_1_impl(
  //                   InputIntegerBits - z_b_headroom - 0.25);
  const FixedPointAccum z_a_pow_2_adj = SaturatingAddNonGemmlowp(
      FixedPointAccum::FromRaw(SaturatingRoundingMultiplyByPOTParam(
-          InputIntegerBits - z_a_headroom_plus_1, 31 - kAccumIntegerBits)),
+          static_cast<int32_t>(InputIntegerBits - z_a_headroom_plus_1),
+          31 - kAccumIntegerBits)),
      shifted_quarter);

  // z_b is treated like z_a, but premultiplying by sqrt(0.5).
@@ -585,7 +726,8 @@ log_x_for_x_greater_than_or_equal_to_1_impl(
      SaturatingRoundingMultiplyByPOTParam(z_a.raw(), z_b_headroom);
  const FixedPointAccum z_b_pow_2_adj = SaturatingSub(
      FixedPointAccum::FromRaw(SaturatingRoundingMultiplyByPOTParam(
-          InputIntegerBits - z_b_headroom, 31 - kAccumIntegerBits)),
+          static_cast<int32_t>(InputIntegerBits - z_b_headroom),
+          31 - kAccumIntegerBits)),
      shifted_quarter);

  const FixedPoint0 r = FixedPoint0::FromRaw(std::min(r_a_raw, r_b_raw));
--- a/code/components/tflite-lib/tensorflow/lite/kernels/internal/compatibility.h
+++ b/code/components/tflite-lib/tensorflow/lite/kernels/internal/compatibility.h
--- a/code/components/tflite-lib/tensorflow/lite/kernels/internal/cppmath.h
+++ b/code/components/tflite-lib/tensorflow/lite/kernels/internal/cppmath.h
@@ -19,9 +19,8 @@ limitations under the License.

 namespace tflite {

-#if defined(TF_LITE_USE_GLOBAL_CMATH_FUNCTIONS) ||                           \
-    (defined(__ANDROID__) && !defined(__NDK_MAJOR__)) || defined(ARDUINO) || \
-    defined(__ZEPHYR__)
+#if defined(TF_LITE_USE_GLOBAL_CMATH_FUNCTIONS) || \
+    (defined(__ANDROID__) && !defined(__NDK_MAJOR__)) || defined(__ZEPHYR__)
 #define TF_LITE_GLOBAL_STD_PREFIX
 #else
 #define TF_LITE_GLOBAL_STD_PREFIX std
--- a/code/components/tflite-lib/tensorflow/lite/kernels/internal/max.h
+++ b/code/components/tflite-lib/tensorflow/lite/kernels/internal/max.h
--- a/code/components/tflite-lib/tensorflow/lite/kernels/internal/min.h
+++ b/code/components/tflite-lib/tensorflow/lite/kernels/internal/min.h
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
jomjol	2daf6c8b3f	v10.1.0	2022-01-09 09:47:16 +01:00
jomjol	24b46158de	v10.1.0	2022-01-09 09:43:22 +01:00
jomjol	63d336ba28	Rolling 20220104	2022-01-04 21:17:20 +01:00
jomjol	8dd3a92671	Rolling 20220103	2022-01-03 17:32:01 +01:00
jomjol	8e8897c70d	v10.0.2	2022-01-01 08:57:07 +01:00
jomjol	eac513411e	v10.0.2	2022-01-01 08:53:55 +01:00
jomjol	98f9274085	V10.0.1	2021-12-31 09:02:59 +01:00
jomjol	884dd9fc3b	V10.0.0	2021-12-30 18:38:15 +01:00
jomjol	04c564936a	Master 10.0.0	2021-12-30 18:29:01 +01:00
jomjol	957138960a	Rolling 20211230	2021-12-30 11:02:20 +01:00
jomjol	58a0297915	Rolling 20211223	2021-12-23 08:03:46 +01:00
jomjol	61bf536207	Rolling 20211212	2021-12-12 19:30:07 +01:00
jomjol	4136a7b372	Merge pull request #456 from mad2xlc/master tabindex to html	2021-12-12 17:45:25 +01:00
Stefan	b3afc9961d	Merge branch 'jomjol:master' into master	2021-12-12 10:36:53 +01:00
jomjol	27e2e042da	Rolling 2021-21-03	2021-12-03 18:12:45 +01:00
Frederik Kemner	cc659bad30	Time based flow rate limiting Take time since last valid value into account for flow rate limiting	2021-12-03 11:27:20 +01:00
jomjol	776931c0ad	v9.2.0	2021-12-02 21:56:05 +01:00
jomjol	e22b4b6fe1	v9.2.0	2021-12-02 21:52:45 +01:00
jomjol	cad534bffe	update wiki	2021-12-02 21:47:37 +01:00
jomjol	3b44adb6fa	Rolling 20211128	2021-11-28 09:09:24 +01:00
jomjol	cc0bd1473f	Rolling 20211124	2021-11-24 07:32:03 +01:00
jomjol	58124d27bf	Rolling 2021-11-23	2021-11-23 17:57:07 +01:00
Sven Rojek	9ad118814a	add basic exception handling for the camera module	2021-11-21 19:05:17 +01:00
jomjol	270f8dd093	v9.1.1	2021-11-16 07:15:55 +01:00
jomjol	fde0ae4781	v9.1.0	2021-11-14 08:57:19 +01:00
jomjol	b87ce8c75d	Merge branch 'master' into rolling	2021-11-14 08:52:40 +01:00
jomjol	e372c87836	v9.1.0	2021-11-14 08:52:28 +01:00
jomjol	f8478d7742	Merge branch 'master' into rolling	2021-11-14 08:48:42 +01:00
jomjol	a3d6923fec	v9.1.0	2021-11-14 08:47:55 +01:00
jomjol	7bfa22187d	Merge branch 'pr/398' into rolling	2021-11-14 08:19:13 +01:00
pixel::doc	7a8affae32	Update Helper.cpp Change "open config file" to "open file"	2021-11-14 01:05:40 +01:00
jomjol	e48dd7c4c4	rolling 20211106	2021-11-06 22:46:16 +01:00
mad2xlc	6d298c1746	added tabindex for coordinate fields	2021-11-04 17:17:22 +01:00
jomjol	4fe9ab92e0	image update	2021-10-27 18:57:07 +02:00
jomjol	f2ac4cdc64	v9.0.0	2021-10-23 16:35:40 +02:00
jomjol	be902401d1	Merge branch 'rolling'	2021-10-23 16:32:44 +02:00
jomjol	020e93bca2	v9.0.0	2021-10-23 16:31:55 +02:00
jomjol	61dfdc2258	Add files via upload	2021-10-23 15:44:46 +02:00
jomjol	a98e3c8eab	Add files via upload	2021-10-22 21:31:21 +02:00
jomjol	58a90ff706	v8.5.0	2021-10-07 07:45:40 +02:00
jomjol	d0bf12f3d4	v8.5.0	2021-10-07 07:16:46 +02:00
jomjol	af16785bbf	Rolling 20211002	2021-10-02 14:59:09 +02:00
jomjol	18f6e83a2c	v8.4.0	2021-09-25 18:57:40 +02:00
jomjol	147d97421b	Merge branch 'rolling'	2021-09-25 18:53:47 +02:00
jomjol	dcf2feb7aa	v8.4.0	2021-09-25 18:53:14 +02:00
jomjol	e63e940b96	v8.4.0	2021-09-25 08:08:21 +02:00
jomjol	68b0fb83ee	v8.4.0	2021-09-24 19:57:48 +02:00
jomjol	f15e5f060a	v8.4.0	2021-09-23 18:43:53 +02:00
jomjol	e2a403441f	Rolling 20210922	2021-09-22 22:13:08 +02:00
jomjol	9b3665b9c6	Rolling 20210921 v2	2021-09-21 19:41:20 +02:00
jomjol	f4c8bf9206	Rolling 20210921	2021-09-21 18:49:32 +02:00
jomjol	c033db9c31	Rolling 20210921	2021-09-21 07:27:46 +02:00
jomjol	9300526f49	Rolling 2021-09-20	2021-09-20 21:18:34 +02:00
jomjol	b6dd1f7f2d	Update	2021-09-14 20:00:45 +02:00
jomjol	1e6eddca04	Rolling 20210913	2021-09-13 20:05:54 +02:00
jomjol	19ca0d7dd7	Update Versioninfo	2021-09-12 07:33:30 +02:00
jomjol	7fcb5d1c0c	v8.3.0	2021-09-12 07:29:30 +02:00
jomjol	dd995ec28a	Rolling 20210910	2021-09-10 09:26:52 +02:00
jomjol	af99de3535	IgnoreLeadingNaN	2021-09-02 11:04:01 +02:00
jomjol	3567cc2fb0	Merge pull request #330 from pixeldoc2000/pixeldoc2000-patch-1 Pixeldoc2000 patch 1	2021-09-02 11:00:49 +02:00
pixel::doc	5e9d9bd264	Update edit_config_param.html Fixed some more Text.	2021-09-02 10:09:36 +02:00
pixel::doc	62447c1bb9	Update edit_config_param.html Fixed some Text	2021-09-02 00:23:59 +02:00
jomjol	a86434c9a2	Rolling 20210831	2021-08-31 11:40:29 +02:00
jomjol	b7b70299f7	Rolling 20210830	2021-08-30 21:21:18 +02:00
jomjol	eb02e0aec1	new images	2021-08-29 20:57:21 +02:00
jomjol	7816e53db7	v8.2.0	2021-08-24 08:37:18 +02:00
jomjol	7ae08e572a	Merge branch 'rolling'	2021-08-24 08:34:32 +02:00
jomjol	47d15d8adb	v8.2.0	2021-08-24 08:33:56 +02:00
jomjol	0dac0e87e4	rolling 20210823	2021-08-23 18:57:48 +02:00
jomjol	b290099d5b	v12.0.0	2021-08-12 07:25:12 +02:00
jomjol	f6b1a41a0b	v12.0.0	2021-08-12 07:20:58 +02:00
jomjol	e529af04cf	Update FeatureRequest.md	2021-08-10 20:19:05 +02:00
jomjol	6c365dd949	rolling v20210809	2021-08-09 21:53:07 +02:00
jomjol	32f15fc557	rolling 20210708	2021-08-07 15:25:27 +02:00
jomjol	6f06af1d5f	Update README.md	2021-08-01 21:52:00 +02:00
jomjol	a91f99faab	update	2021-08-01 21:49:29 +02:00
jomjol	17a87b23a1	v8.0.5	2021-08-01 21:46:17 +02:00
jomjol	d4b5ec2ae2	v8.0.4	2021-07-29 20:18:53 +02:00
jomjol	1bcaf09855	v8.0.4	2021-07-29 20:14:36 +02:00