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* feat(tools): add onnx2ncnn_quant_table * feat(tools): add quantization image dataset * feat(tools): add image dataset * feat(tools/deploy.py): support quant * fix(CI): lint * fix(CI): format * docs(zh_cn): add quantization usage * docs(zh_cn): add benchmark * feat(tools): add onnx2ncnn_quant_table * docs(zh_cn): add more test result * CI(github): add quant script * CI(.github/scripts): add test quant * fix(CI): remove pushd and popd * feat(CI): debug * fix(CI): path error * fix(CI): fix path * fix(CI): install wget * fix(CI): review advices * improvement(mmdeploy): review advice * fix(tools): rename to onnx2ncnn_quant_table.py * improvement(tools): rename file * improvement(test): remove useless * fix(tools/quant_image_dataset): remove loadFile in test.pipeline * docs(quantization.md): update description * fix(CI): protobuf version * fix(CI): pip install * docs(quantization): review advice * fix(CI): revert mmcv version * fix(CI): udpate pb version * fix(CI): update
4 lines
113 B
Python
4 lines
113 B
Python
_base_ = ['./classification_static.py', '../_base_/backends/ncnn-int8.py']
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onnx_config = dict(input_shape=None)
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