Flutter app for detecting face with mask or without mask.
https://docs.google.com/document/d/1v5t3yj0o4g1Mn1RA7q4KgMOAicfBiCBE8zRJeRDVBEQ/edit?usp=sharing
- Training codes: http://tinyurl.com/ybmjk9hu
Avoid writing boilerplate codes to us Keras to train on pretrained MobileNetV2, referencing Google codelabs.
- Training dataset: http://tinyurl.com/ya6vvfap
- camera: ^0.5.8+2
- Tensorflow Lite plugin: tflite: ^1.0.5
- oktoast: ^2.3.2
Shooting video with camera plugin.
Use tflite plugin to read frames and inference with tflite (Tensorflow Lite):
....
CameraController _controller;
bool _isDetecting = false;
....
.... .... ....
List<dynamic> _recognitions;
void _updateRecognitions({
List<dynamic> recognitions,
}) {
setState(() {
_recognitions = recognitions;
});
}
.... .... ....
_controller.startImageStream(
(CameraImage img) {
if (!_isDetecting) {
_isDetecting = true;
Tflite.runModelOnFrame(
bytesList: img.planes.map((Plane plane) {
return plane.bytes;
}).toList(),
imageWidth: img.width,
imageHeight: img.height,
numResults: 2,
).then((List<dynamic> recognitions) {
_updateRecognitions(
recognitions: recognitions,
);
_isDetecting = false;
});
}
},
);Copyright 2020 Chris Xinyue Zhao
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.
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