Awesome
Code mainly come from https://github.com/MTlab/onnx2caffe https://github.com/seanxcwang/onnx2caffe and https://github.com/205418367/onnx2caffe,thanks for their contribution.
onnx to Caffe
we can convert onnx operations to caffe layer which not only from https://github.com/BVLC/caffe but also from many other caffe modified branch like ssd-caffe,and only onnx opset_version=9 is supported.
- Convert pytorch to Caffe by ONNX
This tool converts pytorch model to Caffe model by ONNX
only use for inference
- Convert tensorflow to Caffe by ONNX
you can use this repo https://github.com/onnx/tensorflow-onnx.
- other deeplearning frame work to caffe bt ONNX
Dependencies
- caffe (with python support)
- pytorch (optional if you want to convert onnx)
- onnx
- onnxruntime
we recomand using protobuf 2.6.1 and install onnx from source
git clone --recursive https://github.com/onnx/onnx.git
cd onnx
python setup.py install
or just using pip
pip install onnx
How to use
- To convert onnx model to caffe:
python convertCaffe.py ./model/MobileNetV2.onnx ./model/MobileNetV2.prototxt ./model/MobileNetV2.caffemodel
pytorch to onnx Tips
- you can refer model_generator folder to learn how to generate onnx from pytorch,or just learn from pytorch.org.
- in pytorch,speeding up model with fusing batch normalization and convolution,so before convert pytorch pth model to onnx fusing fusing batch normalization and convolution is a good choice.you may refer this https://learnml.today/speeding-up-model-with-fusing-batch-normalization-and-convolution-3.
- Sometimes you need to use onnx-simplifier to simplify onnx model and then run convertCaffe.py to convert it into caffe model.
Current support operation
- Conv
- Relu
- LeakyRelu
- PRelu
- Transpose
- ReduceMean
- MatMul
- BatchNormalization
- Add
- Mul
- Add
- Reshape
- MaxPool
- AveragePool
- GlobalAveragePool
- Dropout
- Gemm (InnerProduct only)
- Upsample (nearest and bilinear all supported)
- Concat
- ConvTranspose
- Sigmoid
- Flatten
- Sqrt
- Softmax
- Unsqueeze
- Slice