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https://github.com/open-mmlab/mmdeploy.git
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* hold async data and wait only at the end of the pipeline * fix use-after-free bugs * fix wording * bypass trivial cases for Pad to avoid ppl.cv's bug * fix pad * fix lint * cleanup * fix DefaultFormatBundle * fix all cpu preprocess impl * suppress log * fix dynamic library build & add comments for SyncOnScopeExit
45 lines
1.3 KiB
C++
45 lines
1.3 KiB
C++
// Copyright (c) OpenMMLab. All rights reserved.
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#include "core/registry.h"
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#include "core/utils/device_utils.h"
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#include "opencv_utils.h"
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#include "preprocess/transform/normalize.h"
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using namespace std;
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namespace mmdeploy {
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namespace cpu {
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class NormalizeImpl : public ::mmdeploy::NormalizeImpl {
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public:
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NormalizeImpl(const Value& value) : ::mmdeploy::NormalizeImpl(value){};
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~NormalizeImpl() = default;
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protected:
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Result<Tensor> NormalizeImage(const Tensor& tensor) override {
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OUTCOME_TRY(auto src_tensor, MakeAvailableOnDevice(tensor, device_, stream_));
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SyncOnScopeExit(stream_, src_tensor.buffer() != tensor.buffer(), src_tensor);
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auto mat = Tensor2CVMat(src_tensor);
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auto dst_mat = Normalize(mat, arg_.mean, arg_.std, arg_.to_rgb, true);
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return CVMat2Tensor(dst_mat);
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}
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};
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class NormalizeImplCreator : public Creator<::mmdeploy::NormalizeImpl> {
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public:
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const char* GetName() const override { return "cpu"; }
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int GetVersion() const override { return 1; }
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std::unique_ptr<::mmdeploy::NormalizeImpl> Create(const Value& args) override {
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return make_unique<NormalizeImpl>(args);
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}
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};
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} // namespace cpu
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} // namespace mmdeploy
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using mmdeploy::NormalizeImpl;
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using mmdeploy::cpu::NormalizeImplCreator;
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REGISTER_MODULE(NormalizeImpl, NormalizeImplCreator);
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