BinaryClassify
Implementation of a binary classify By pytorch
DataSets
Prepare a dataset for positive and negative samples. Such as Eye Dataset, determine open eyes as positive samples, closed eyes as negative samples.
1.put positive samples to ./data/positive/
2.put negative samples to ./data/negative/
3.run ./data/train_test_data.py
$ cd ./data
$ python3 train_test_data.py
training & testing
training :
$ sh train.sh
testing:
$ python3 test_img.py
pytorch -> onnx -> ncnn
Pytorch -> onnx -> onnx_sim
make sure pip3 install onnx-simplifier
$ python3 pytorch2onnx.py
$ python3 -m onnxsim model.onnx model_sim.onnx
onnx_sim -> ncnn
how to build :https://github.com/Tencent/ncnn/wiki/how-to-build
$ cd ncnn/build/tools/onnx
$ ./onnx2ncnn model_sim.onnx model_sim.param model_sim.bin
TODO:
- ncnn inference
- train on FocalLoss
- train on multi-class model
- fix bugs