churlyhomles/onnx2tflite

Tool for onnx->keras or onnx->tflite. If tool is useful for you, please star it.

ONNX->Keras and ONNX->TFLite tools

How to use

# base
python converter.py --weights "./your_model.onnx"

# give save path
python converter.py --weights "./your_model.onnx" --outpath "./save_path"

# save keras model
python converter.py --weights "./your_model.onnx" --outpath "./save_path" --formats "keras"

# save tflite model
python converter.py --weights "./your_model.onnx" --outpath "./save_path" --formats "tflite"

# save keras and tflite model
python converter.py --weights "./your_model.onnx" --outpath "./save_path" --formats "tflite" "keras"

# quantitative model weight, only weight
python converter.py --weights "./your_model.onnx" --formats "tflite" --weigthquant

# quantitative model weight, include input and output
## recommend
python converter.py --weights "./your_model.onnx" --formats "tflite" --int8 --imgroot "./dataset_path" --int8mean 0 0 0 --int8std 1 1 1
## generate random data, instead of read from image file
python converter.py --weights "./your_model.onnx" --formats "tflite" --int8

注意(Caution)

• please use comfirm_acc.py comfirm output is correct after convertion, because some of methods rely on practice.
• comfirm_acc.py only support tflite, and tflite should not be any quantification.
• only support 2D CNN, may be support more types of CNN or transformer in the future.
• 因为大部分是靠实践经验的，所以转换完成最好使用comfirm_acc.py确认转换精度。
• 目前只支持2D卷积网络

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添加新算子时，API查询地址(API reference docs)

• onnx_api : https://github.com/onnx/onnx/blob/main/docs/Operators.md
• tensorflow_api : https://tensorflow.google.cn/api_docs/python/tf
• keras_api : https://keras.io/search.html

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已验证的模型列表(support models)

• Resnet
• Densenet
• Mobilenet
• Alexnet
• VGG
• UNet\FPN
• YOLOX
• YOLOV4
• YOLOV5
• MobileNetV2 SSD-Lite
• MoveNet
• BigGAN
• DCGAN
• normal CNN