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* minor changes * support windows * fix GCC build * fix lint * reformat * fix Windows build * fix GCC build * search backend ops for onnxruntime * fix lint * fix lint * code clean-up * code clean-up * fix clang build * fix trt support * fix cmake for ncnn * fix cmake for openvino * fix SDK Python API * handle ops for other backends (ncnn, trt) * handle SDK Python API library location * robustify linkage * fix cuda * minor fix for openvino & ncnn * use CMAKE_CUDA_ARCHITECTURES if set * fix cuda preprocessor * fix misc * fix pplnn & pplcv, drop support for pplcv<0.6.0 * robustify cmake * update build.md (#2) * build dynamic modules as module library & fix demo (partially) * fix candidate path for mmdeploy_python * move "enable CUDA" to cmake config for demo * refine demo cmake * add comment * fix ubuntu build * revert docs/en/build.md * fix C API * fix lint * Windows build doc (#3) * check in docs related to mmdeploy build on windows * update build guide on windows platform * update build guide on windows platform * make path of thirdparty libraries consistent * make path consistency * correct build command for custom ops * correct build command for sdk * update sdk build instructions * update doc * correct build command * fix lint * correct build command and fix lint Co-authored-by: lvhan <lvhan@pjlab.org> * trailing whitespace (#4) * minor fix * fix sr sdk model * fix type deduction * fix cudaFree after driver shutting down * update ppl.cv installation warning (#5) * fix device allocator threshold & fix lint * update doc (#6) * update ppl.cv installation warning * missing 'git clone' Co-authored-by: chenxin <chenxin2@sensetime.com> Co-authored-by: zhangli <zhangli@sensetime.com> Co-authored-by: lvhan028 <lvhan_028@163.com> Co-authored-by: lvhan <lvhan@pjlab.org>
154 lines
3.9 KiB
C++
154 lines
3.9 KiB
C++
// Copyright (c) OpenMMLab. All rights reserved.
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#ifndef MMDEPLOY_CSRC_UTILS_OPENCV_OPENCV_UTILS_H_
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#define MMDEPLOY_CSRC_UTILS_OPENCV_OPENCV_UTILS_H_
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#include "core/mat.h"
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#include "core/mpl/type_traits.h"
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#include "core/serialization.h"
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#include "core/tensor.h"
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#include "opencv2/opencv.hpp"
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namespace mmdeploy {
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namespace cpu {
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MMDEPLOY_API cv::Mat Mat2CVMat(const Mat& mat);
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MMDEPLOY_API cv::Mat Tensor2CVMat(const Tensor& tensor);
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MMDEPLOY_API Mat CVMat2Mat(const cv::Mat& mat, PixelFormat format);
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MMDEPLOY_API Tensor CVMat2Tensor(const cv::Mat& mat);
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/**
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* @brief resize an image to specified size
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*
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* @param src input image
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* @param dst_height output image's height
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* @param dst_width output image's width
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* @return output image if success, error code otherwise
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*/
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MMDEPLOY_API cv::Mat Resize(const cv::Mat& src, int dst_height, int dst_width,
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const std::string& interpolation);
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/**
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* @brief crop an image
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*
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* @param src input image
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* @param top
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* @param left
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* @param bottom
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* @param right
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* @return cv::Mat
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*/
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MMDEPLOY_API cv::Mat Crop(const cv::Mat& src, int top, int left, int bottom, int right);
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/**
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* @brief Do normalization to an image
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*
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* @param src input image. It is assumed to be BGR if the channel is 3
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* @param mean
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* @param std
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* @param to_rgb
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* @param inplace
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* @return cv::Mat
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*/
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MMDEPLOY_API cv::Mat Normalize(cv::Mat& src, const std::vector<float>& mean,
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const std::vector<float>& std, bool to_rgb, bool inplace = true);
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/**
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* @brief tranpose an image, from {h, w, c} to {c, h, w}
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*
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* @param src input image
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* @return
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*/
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MMDEPLOY_API cv::Mat Transpose(const cv::Mat& src);
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/**
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* @brief convert an image to another color space
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*
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* @param src
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* @param src_format
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* @param dst_format
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* @return
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*/
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MMDEPLOY_API cv::Mat ColorTransfer(const cv::Mat& src, PixelFormat src_format,
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PixelFormat dst_format);
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/**
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*
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* @param src
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* @param top
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* @param left
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* @param bottom
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* @param right
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* @param border_type
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* @param val
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* @return
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*/
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MMDEPLOY_API cv::Mat Pad(const cv::Mat& src, int top, int left, int bottom, int right,
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int border_type, float val);
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/**
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* @brief compare two images
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*
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* @param src1 one input image
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* @param src2 the other input image
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* @return bool true means the images are the same
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*/
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MMDEPLOY_API bool Compare(const cv::Mat& src1, const cv::Mat& src2);
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} // namespace cpu
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namespace detail {
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template <typename T>
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struct IsCvPoint : std::false_type {};
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template <typename T>
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struct IsCvPoint<::cv::Point_<T>> : std::true_type {};
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template <typename Archive, typename T,
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std::enable_if_t<detail::IsCvPoint<uncvref_t<T>>::value, int> = 0>
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void serialize(Archive&& archive, T&& p) {
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int size{2};
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std::forward<Archive>(archive).init(size);
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std::forward<Archive>(archive).item(std::forward<T>(p).x);
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std::forward<Archive>(archive).item(std::forward<T>(p).y);
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}
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template <typename Archive, typename T, std::enable_if_t<detail::IsCvPoint<T>::value, int> = 0>
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void save(Archive& archive, std::vector<T>& v) {
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archive.init(array_tag<T>{v.size() * 2});
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for (const auto& p : v) {
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archive.item(p.x);
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archive.item(p.y);
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}
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}
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template <typename Archive, typename T, std::enable_if_t<detail::IsCvPoint<T>::value, int> = 0>
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void save(Archive& archive, const std::vector<T>& v) {
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archive.init(array_tag<T>{v.size() * 2});
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for (const auto& p : v) {
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archive.item(p.x);
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archive.item(p.y);
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}
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}
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template <typename Archive, typename T, std::enable_if_t<detail::IsCvPoint<T>::value, int> = 0>
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void load(Archive& archive, std::vector<T>& v) {
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size_t size{};
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archive.init(size);
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size /= 2;
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T p;
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for (int i = 0; i < size; ++i) {
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archive.item(p.x);
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archive.item(p.y);
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v.push_back(p);
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}
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}
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} // namespace detail
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} // namespace mmdeploy
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#endif // MMDEPLOY_CSRC_UTILS_OPENCV_OPENCV_UTILS_H_
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