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docs/Alignment.md
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@@ -11,7 +11,7 @@ with the target to be in exactly the same position as the reference image.
## Precondition
Please make sure to have setup your camera properly and taken a good [Reference Image](../Reference-Image).
Please make sure to have setup your camera properly and taken a good [Reference Image](Reference-Image.md).
## Define two Reference Images

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docs/Choosing-the-Model.md
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# Model Selection
!!! Notes
See [Neural Network Types](../Neural-Network-Types) for additional details.
See [Neural Network Types](Neural-Network-Types.md) for additional details.
In the [Graphical Configuration Page](../Graphical-configuration), you can choose different models depending on your needs.
In the [Graphical Configuration Page](Configuration.md), you can choose different models depending on your needs.
This page tries to help you on which model to select.
For more technical/deeper explanations have a look on [Neural-Network-Types](../Neural-Network-Types).
For more technical/deeper explanations have a look on [Neural-Network-Types](Neural-Network-Types.md).
## Digit Models

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docs/Configuration.md
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@@ -9,7 +9,7 @@ It can be reached via the menu `Settings > Configuration`.
- To activate the changes, the device needs to be restarted after saving the changes.
- Most of the commands need processing on the ESP32 device. This is not very fast - so please be patient.
All parameters are documented on the [Parameters](../Parameters) page and as tooltips on the config page.
All parameters are documented on the [Parameters](Parameters.md) page and as tooltips on the config page.
## Expert Parameters
Some parameters are treated as **Expert Parameters** and are hidden by default.

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docs/Error-Codes.md
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@@ -12,7 +12,7 @@ Most likely they are caused by a hardware issue!
### `0x00000001` PSRAM bad
Your device most likely has no PSRAM at all or it is too small (needs to have at least 4 MBytes)!
See [Hardware Compatibility](../Hardware-Compatibility).
See [Hardware Compatibility](Hardware-Compatibility.md).
Usually the log shows something like this:
```
@@ -27,7 +27,7 @@ The firmware failed to allocate enough memory. This most likely is a consequenti
The attached camera can not be initialized.
This usually is because on of the following reasons:
* The camera is not supported, see [Hardware Compatibility](../Hardware-Compatibility)
* The camera is not supported, see [Hardware Compatibility](Hardware-Compatibility.md)
* The camera is not attached properly -> Try to remove and attach it again. Make sure you move the black part enough into the socket!
* The camera or the camera cable is damaged

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docs/FAQs.md
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@@ -6,9 +6,9 @@ There are several reasons for frequent reboots:
* Frequent HTML requests
* Wrong configuration, missing configuration files
* Unstable hardware - see [Hardware Compatibility](../Hardware-Compatibility).
* Unstable hardware - see [Hardware Compatibility](Hardware-Compatibility.md).
There is a dedicated page about this: [Frequent Reboots](../Frequent-Reboots/).
There is a dedicated page about this: [Frequent Reboots](Frequent-Reboots.md).
## Bad WebUI responsiveness. What can I do?
@@ -49,7 +49,7 @@ See the FAQs below for more details and configuration hints.
## My numbers are not correctly detected. What can I do?
* There is a dedicated page about the correct setting [ROI Configuration](../ROI-Configuration/).
* There is a dedicated page about the correct setting [ROI Configuration](ROI-Configuration.md).
* This page also includes the instructions for gathering new images for the training.
## How can I ensure invalid numbers are never reported?

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docs/Influx-DB.md
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# Influx DB
The device also supports direct sending of data to an Influx DB.
See also [Influx Graph in Home Assistant](../Integration-Home-Assistant#influxdb-graphs).
See also [Influx Graph in Home Assistant](Integration-Home-Assistant.md#influxdb-graphs).

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docs/Installation.md
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@@ -15,7 +15,7 @@ For point 2 and 3 we provide multiple ways to do it. Pick the one that looks the
* 4 or 8 MB PSRAM.
It can be easily found on the typical internet stores, searching for ESP32-CAM for less than 10 EUR.
How ever since the hardware is cheap and coming from China, you unluckily could pick a malfunctioning device. See [Hardware Compatibility](../Hardware-Compatibility) for further advice!
How ever since the hardware is cheap and coming from China, you unluckily could pick a malfunctioning device. See [Hardware Compatibility](Hardware-Compatibility.md) for further advice!
### USB->UART interface
For first time flashing the firmware a USB -> UART connector is needed. Later firmware upgrades than can be flashed via OTA.
@@ -46,7 +46,7 @@ A example for wiring can be found here:
![](img/progammer_manual.jpg)
It is also possible to use external LEDs for the illumination instead of the internal flash LED. This is described [here](../External-LED)
It is also possible to use external LEDs for the illumination instead of the internal flash LED. This is described [here](External-LED.md)
## 2. Firmware
### Web Installer
@@ -63,7 +63,7 @@ You can access it with the following link: [Web Installer](https://jomjol.github
Grab the firmware from the
- [Releases page](https://github.com/jomjol/AI-on-the-edge-device/releases) (Stable, tested versions), or the
- [Automatically build development branch](https://github.com/jomjol/AI-on-the-edge-device/actions?query=branch%3Arolling) (experimental, untested versions). Please have a look on [Living on the Edge](../rolling-installation) first!
- [Automatically build development branch](https://github.com/jomjol/AI-on-the-edge-device/actions?query=branch%3Arolling) (experimental, untested versions). Please have a look on [Living on the Edge](rolling-installation.md) first!
You need:

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docs/Integration-Home-Assistant.md
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@@ -131,7 +131,7 @@ Note that there seems to be a bug in the graph, see [https://github.com/home-ass
### InfluxDb Graphs
See also [Influx-DB](../Influx-DB).
See also [Influx-DB](Influx-DB.md).
If you have setup InfluxDB already, it is also possible to fetch statistics from there, e.g. daily usage:
```
@@ -150,7 +150,7 @@ from(bucket: "HomeAssistant")
## Using REST
When using REST, Home Assistant has to periodically call an URL on the ESP32 which in return provides the requested data.
See [REST API](../REST-API) for a list of available URLs.
See [REST API](REST-API.md) for a list of available URLs.
The most practical one is the `json` entrypoint which provides the most relevant data JSON formatted:
`http://<IP>/json`

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docs/Neural-Network-Types.md
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# Neural Network Types
!!! Note
For an overview, see [Choosing the Model](../Choosing-the-Model).
For an overview, see [Choosing the Model](Choosing-the-Model.md).
This section is describing the different types of neural networks, that are used with the AI-on-the-edge approach and gives an introduction on how and where to use them.

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docs/REST-API.md
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@@ -145,4 +145,4 @@ Note: For more detailed information to the REST handler, have a look to the code
## Prometheus/OpenMetrics
### metrics
Provides a set of metrics that can be scraped by prometheus. See [Prometheus/OpenMetrics](../prometheus-openmetrics) for details.
Provides a set of metrics that can be scraped by prometheus. See [Prometheus/OpenMetrics](prometheus-openmetrics.md) for details.

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docs/ROI-Configuration.md
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@@ -13,14 +13,14 @@ The most critical components for an accurate detection are:
2. Using a well trained Model.
Have a look on the [Digital Counters](https://jomjol.github.io/neural-network-digital-counter-readout/) resp. [Analog Needles](https://jomjol.github.io/neural-network-analog-needle-readout) to check if your types are contained. If your number types are **not** contained, you should take the effort to record them so we can add them to the training data. See [Collect images to improve the models](../Learn-models-with-your-own-images) on how to collect new training data.
Have a look on the [Digital Counters](https://jomjol.github.io/neural-network-digital-counter-readout/) resp. [Analog Needles](https://jomjol.github.io/neural-network-analog-needle-readout) to check if your types are contained. If your number types are **not** contained, you should take the effort to record them so we can add them to the training data. See [Collect images to improve the models](Learn-models-with-your-own-images.md) on how to collect new training data.
## Precondition
Please make sure to have:
1. Setup your camera properly and taken a good [Reference Image](../Reference-Image).
1. Selected good [Alignment References](../Alignment).
1. Setup your camera properly and taken a good [Reference Image](Reference-Image.md).
1. Selected good [Alignment References](Alignment.md).
## Define the ROIs
@@ -34,7 +34,7 @@ Depending if you have only one of those types, you can enable/disable `(1)` it o
You can switch between the individual ROIs with the Drop down box `(2)`.
If you need additional ROIs or delete them you can do this with the control at `(3)`.
Like for the [Alignment References](../Alignment), you can change the position, size and name of a ROI in the text fields or define them via drag and drop through the mouse button.
Like for the [Alignment References](Alignment.md), you can change the position, size and name of a ROI in the text fields or define them via drag and drop through the mouse button.
Make sure the ROIs are in the right order, matching the significance of a digit/analog counter!
!!! Warning
@@ -71,7 +71,7 @@ The configuration of ROIs differs a bit on the selected model (see below).
If you are in the initial setup, the model will be selectable in the next step. By default it is a `dig-cont` resp. `ana-cont` model.
In [Model Selection](../Choosing-the-Model) you find the differences between the different available models. Pick the one you think fits best your purpose. If you don't get to good result, try another model.
In [Model Selection](Choosing-the-Model.md) you find the differences between the different available models. Pick the one you think fits best your purpose. If you don't get to good result, try another model.
Here we only show the different configuration of the ROIs.
@@ -123,7 +123,7 @@ For this model, there should be a border of `20%` of the image size around the n
| :x: **Not** Okay | ![](img/bw_not_okay_big.jpg) | ![](img/wb_not_okay_big.jpg) |
If you have perfect alignment and still are not getting satisfying results, most probably your numbers are not part of the training data yet. See [Collect images to improve the models](../Learn-models-with-your-own-images) on how to collect new training data.
If you have perfect alignment and still are not getting satisfying results, most probably your numbers are not part of the training data yet. See [Collect images to improve the models](Learn-models-with-your-own-images.md) on how to collect new training data.
##### Setup using `dig-class100` or `dig-cont` Models

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docs/data-logging.md
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# Data Logging
When Data Logging is enabled (See parameter [`DataLogActive`](../Parameters/#parameter-datalogactive)),
When Data Logging is enabled (See parameter [`DataLogActive`](Parameters.md/#parameter-datalogactive)),
the results of every round gets written to the SD-Card.
The data files are stored in `/log/data` on the SD-Card.

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docs/ota.md
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@@ -3,7 +3,7 @@ You can do an OTA (over-the-air) update via the Web Interface.
Grab the firmware from the
* [Releases page](https://github.com/jomjol/AI-on-the-edge-device/releases) (Stable, tested versions), or the
* [Automatically build development branch](https://github.com/jomjol/AI-on-the-edge-device/actions?query=branch%3Arolling) (experimental, untested versions). Please inform yourself on [Living on the Edge](../rolling-installation) first!
* [Automatically build development branch](https://github.com/jomjol/AI-on-the-edge-device/actions?query=branch%3Arolling) (experimental, untested versions). Please inform yourself on [Living on the Edge](rolling-installation.md) first!
## Update Procedure
1. Create a backup of your configuration. Either use the Backup/Restore function of your device for this (menu `System > Backup/Restore`) or back the files manually up using the File Server (menu `File Server`, folder `config`). It is recommended to at least save the config file `config.ini`!

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docs/rolling-installation.md
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@@ -3,7 +3,7 @@
The [Github repository](https://github.com/jomjol/AI-on-the-edge-device) contains multiple branches:
- The [master](https://github.com/jomjol/AI-on-the-edge-device/tree/master) branch contains the same firmware version as provided on the [release page](https://github.com/jomjol/AI-on-the-edge-device/releases).
- The [rolling](https://github.com/jomjol/AI-on-the-edge-device/tree/rolling) branch contains the **latest** version of the Firmware and the Web Interface. It might already contain a fix for your issue. But it is work in progress, don't expect it to work stable or be an improvement for your AI-on-the-edge-device! Also it might break the [OTA Update](../ota) and thus require manual flashing over USB!
- The [rolling](https://github.com/jomjol/AI-on-the-edge-device/tree/rolling) branch contains the **latest** version of the Firmware and the Web Interface. It might already contain a fix for your issue. But it is work in progress, don't expect it to work stable or be an improvement for your AI-on-the-edge-device! Also it might break the [OTA Update](ota.md) and thus require manual flashing over USB!
- Any other branch is used to develop a feature or fix, only use them when you know what it is about!
## I still want to try it
@@ -14,4 +14,4 @@ Ok, then grab the latest `rolling` build from [Github Actions](https://github.co
![](actions.png)
2. Scroll down and download the `AI-on-the-edge-device__update__*.zip`:
![](update-artifact.png)
5. Flash the zip file using the [OTA Update](../ota) page of your device.
5. Flash the zip file using the [OTA Update](ota.md) page of your device.

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param-docs/templates/overview.md
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# Parameters
This page lists all available [Configuration](../Configuration) Parameters.
This page lists all available [Configuration](Configuration.md) Parameters.
If a **parameter** or **section** has a tick box on its left side, you can disable it.
In such case the functionality gets disabled respectively the default values will be used.