mirror of
https://github.com/jomjol/AI-on-the-edge-device.git
synced 2026-01-27 04:40:39 +03:00
removed redundant log entries (some now are DEBUG isntread of INFO or ERROR)
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@@ -548,8 +548,7 @@ bool ClassFlowCNNGeneral::getNetworkParameter()
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zwcnn = FormatFileName(zwcnn);
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ESP_LOGD(TAG, "%s", zwcnn.c_str());
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if (!tflite->LoadModel(zwcnn)) {
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ESP_LOGD(TAG, "Can't read model file /sdcard%s", cnnmodelfile.c_str());
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LogFile.WriteToFile("Cannot load model");
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LogFile.WriteToFile("Can't read model file /sdcard%s", cnnmodelfile.c_str());
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delete tflite;
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return false;
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}
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@@ -617,8 +616,7 @@ bool ClassFlowCNNGeneral::doNeuralNetwork(string time)
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zwcnn = FormatFileName(zwcnn);
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ESP_LOGD(TAG, "%s", zwcnn.c_str());
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if (!tflite->LoadModel(zwcnn)) {
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ESP_LOGD(TAG, "Can't read model file /sdcard%s", cnnmodelfile.c_str());
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LogFile.WriteToFile("Cannot load model");
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LogFile.WriteToFile("Can't read model file /sdcard%s", cnnmodelfile.c_str());
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delete tflite;
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return false;
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@@ -804,8 +802,7 @@ bool ClassFlowCNNGeneral::doNeuralNetwork(string time)
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GENERAL[_ana]->ROI[i]->isReject = true;
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result = -1;
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_result_save_file+= 100; // Für den Fall, dass fit nicht ausreichend, soll trotzdem das Ergebnis mit "-10x.y" abgespeichert werden.
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string zw = "Value Rejected due to Threshold (Fit: " + to_string(_fit) + "Threshold: " + to_string(CNNGoodThreshold);
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ESP_LOGD(TAG, "Value Rejected due to Threshold (Fit: %f, Threshold: %f", _fit, CNNGoodThreshold);
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string zw = "Value Rejected due to Threshold (Fit: " + to_string(_fit) + "Threshold: " + to_string(CNNGoodThreshold) + ")";
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LogFile.WriteToFile(zw);
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}
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else
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