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* check in cmake * move backend_ops to csrc/backend_ops * check in preprocess, model, some codebase and their c-apis * check in CMakeLists.txt * check in parts of test_csrc * commit everything else * add readme * update core's BUILD_INTERFACE directory * skip codespell on third_party * update trt_net and ort_net's CMakeLists * ignore clion's build directory * check in pybind11 * add onnx.proto. Remove MMDeploy's dependency on ncnn's source code * export MMDeployTargets only when MMDEPLOY_BUILD_SDK is ON * remove useless message * target include directory is wrong * change target name from mmdeploy_ppl_net to mmdeploy_pplnn_net * skip install directory * update project's cmake * remove useless code * set CMAKE_BUILD_TYPE to Release by force if it isn't set by user * update custom ops CMakeLists * pass object target's source lists * fix lint end-of-file * fix lint: trailing whitespace * fix codespell hook * remove bicubic_interpolate to csrc/backend_ops/ * set MMDEPLOY_BUILD_SDK OFF * change custom ops build command * add spdlog installation command * update docs on how to checkout pybind11 * move bicubic_interpolate to backend_ops/tensorrt directory * remove useless code * correct cmake * fix typo * fix typo * fix install directory * correct sdk's readme * set cub dir when cuda version < 11.0 * change directory where clang-format will apply to * fix build command * add .clang-format * change clang-format style from google to file * reformat csrc/backend_ops * format sdk's code * turn off clang-format for some files * add -Xcompiler=-fno-gnu-unique * fix trt topk initialize * check in config for sdk demo * update cmake script and csrc's readme * correct config's path * add cuda include directory, otherwise compile failed in case of tensorrt8.2 * clang-format onnx2ncnn.cpp Co-authored-by: zhangli <lzhang329@gmail.com> Co-authored-by: grimoire <yaoqian@sensetime.com>
53 lines
1.6 KiB
C++
53 lines
1.6 KiB
C++
// Copyright (c) OpenMMLab. All rights reserved.
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#include "opencv_utils.h"
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#include "preprocess/transform/load.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 PrepareImageImpl : public ::mmdeploy::PrepareImageImpl {
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public:
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explicit PrepareImageImpl(const Value& args) : ::mmdeploy::PrepareImageImpl(args){};
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~PrepareImageImpl() override = default;
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protected:
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Result<Tensor> ConvertToBGR(const Mat& img) override {
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auto src_mat = Mat2CVMat(img);
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auto dst_mat = ColorTransfer(src_mat, img.pixel_format(), PixelFormat::kBGR);
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if (arg_.to_float32) {
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cv::Mat _dst_mat;
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dst_mat.convertTo(_dst_mat, CV_32FC3);
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dst_mat = _dst_mat;
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}
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return ::mmdeploy::cpu::CVMat2Tensor(dst_mat);
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}
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Result<Tensor> ConvertToGray(const Mat& img) override {
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auto src_mat = Mat2CVMat(img);
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auto dst_mat = ColorTransfer(src_mat, img.pixel_format(), PixelFormat::kGRAYSCALE);
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if (arg_.to_float32) {
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cv::Mat _dst_mat;
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dst_mat.convertTo(_dst_mat, CV_32FC1);
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dst_mat = _dst_mat;
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}
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return ::mmdeploy::cpu::CVMat2Tensor(dst_mat);
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}
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};
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class PrepareImageImplCreator : public Creator<::mmdeploy::PrepareImageImpl> {
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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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ReturnType Create(const Value& args) override { return make_unique<PrepareImageImpl>(args); }
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};
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} // namespace cpu
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} // namespace mmdeploy
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using mmdeploy::PrepareImageImpl;
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using mmdeploy::cpu::PrepareImageImplCreator;
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REGISTER_MODULE(PrepareImageImpl, PrepareImageImplCreator);
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