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https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-12-24 13:28:13 +08:00
[Bug Fix]fix tracking 'LetterBoxResize' (#1711)
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@@ -18,7 +18,8 @@
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namespace fastdeploy{
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namespace vision{
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bool LetterBoxResize::operator()(Mat* mat, ProcLib lib) {
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bool LetterBoxResize::ImplByOpenCV(Mat* mat){
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if (mat->Channels() != color_.size()) {
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FDERROR << "LetterBoxResize: Require input channels equals to size of color value, "
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"but now channels = "
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@@ -45,14 +46,117 @@ bool LetterBoxResize::operator()(Mat* mat, ProcLib lib) {
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int bottom = std::round(padh + 0.1);
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int left = std::round(padw - 0.1);
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int right = std::round(padw + 0.1);
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Resize::Run(mat, new_shape_w, new_shape_h, -1.0, -1.0, 3, false, lib);
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Pad::Run(mat, top, bottom, left, right, color_, lib);
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Resize::Run(mat, new_shape_w, new_shape_h, -1.0, -1.0, 3, false);
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Pad::Run(mat, top, bottom, left, right, color_);
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return true;
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}
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bool LetterBoxResize::Run(Mat* mat, const std::vector<int>& target_size, const std::vector<float>& color, ProcLib lib) {
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#ifdef ENABLE_FLYCV
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bool LetterBoxResize::ImplByFlyCV(Mat* mat){
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if (mat->Channels() != color_.size()) {
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FDERROR << "LetterBoxResize: Require input channels equals to size of color value, "
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"but now channels = "
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<< mat->Channels()
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<< ", the size of color values = " << color_.size() << "."
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<< std::endl;
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return false;
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}
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// generate scale_factor
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int origin_w = mat->Width();
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int origin_h = mat->Height();
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int target_h = target_size_[0];
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int target_w = target_size_[1];
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float ratio_h = static_cast<float>(target_h) / static_cast<float>(origin_h);
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float ratio_w = static_cast<float>(target_w) / static_cast<float>(origin_w);
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float resize_scale = std::min(ratio_h, ratio_w);
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// get_resized_shape
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int new_shape_w = std::round(origin_w * resize_scale);
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int new_shape_h = std::round(origin_h * resize_scale);
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// calculate pad
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float padw = (target_size_[1] - new_shape_w) / 2.;
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float padh = (target_size_[0] - new_shape_h) / 2.;
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int top = std::round(padh - 0.1);
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int bottom = std::round(padh + 0.1);
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int left = std::round(padw - 0.1);
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int right = std::round(padw + 0.1);
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Resize::Run(mat, new_shape_w, new_shape_h, -1.0, -1.0, 3, false, ProcLib::FLYCV);
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Pad::Run(mat, top, bottom, left, right, color_, ProcLib::FLYCV);
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return true;
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}
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#endif
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#ifdef ENABLE_CVCUDA
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bool LetterBoxResize::ImplByCvCuda(Mat* mat){
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if (mat->Channels() != color_.size()) {
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FDERROR << "LetterBoxResize: Require input channels equals to size of color value, "
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"but now channels = "
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<< mat->Channels()
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<< ", the size of color values = " << color_.size() << "."
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<< std::endl;
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return false;
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}
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// generate scale_factor
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int origin_w = mat->Width();
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int origin_h = mat->Height();
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int target_h = target_size_[0];
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int target_w = target_size_[1];
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float ratio_h = static_cast<float>(target_h) / static_cast<float>(origin_h);
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float ratio_w = static_cast<float>(target_w) / static_cast<float>(origin_w);
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float resize_scale = std::min(ratio_h, ratio_w);
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// get_resized_shape
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int new_shape_w = std::round(origin_w * resize_scale);
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int new_shape_h = std::round(origin_h * resize_scale);
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// calculate pad
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float padw = (target_size_[1] - new_shape_w) / 2.;
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float padh = (target_size_[0] - new_shape_h) / 2.;
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int top = std::round(padh - 0.1);
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int bottom = std::round(padh + 0.1);
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int left = std::round(padw - 0.1);
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int right = std::round(padw + 0.1);
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Resize::Run(mat, new_shape_w, new_shape_h, -1.0, -1.0, 3, false, ProcLib::CVCUDA);
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Pad::Run(mat, top, bottom, left, right, color_, ProcLib::CVCUDA);
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return true;
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}
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#endif
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#ifdef ENABLE_CUDA
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bool LetterBoxResize::ImplByCuda(Mat* mat){
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if (mat->Channels() != color_.size()) {
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FDERROR << "LetterBoxResize: Require input channels equals to size of color value, "
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"but now channels = "
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<< mat->Channels()
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<< ", the size of color values = " << color_.size() << "."
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<< std::endl;
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return false;
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}
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// generate scale_factor
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int origin_w = mat->Width();
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int origin_h = mat->Height();
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int target_h = target_size_[0];
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int target_w = target_size_[1];
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float ratio_h = static_cast<float>(target_h) / static_cast<float>(origin_h);
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float ratio_w = static_cast<float>(target_w) / static_cast<float>(origin_w);
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float resize_scale = std::min(ratio_h, ratio_w);
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// get_resized_shape
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int new_shape_w = std::round(origin_w * resize_scale);
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int new_shape_h = std::round(origin_h * resize_scale);
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// calculate pad
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float padw = (target_size_[1] - new_shape_w) / 2.;
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float padh = (target_size_[0] - new_shape_h) / 2.;
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int top = std::round(padh - 0.1);
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int bottom = std::round(padh + 0.1);
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int left = std::round(padw - 0.1);
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int right = std::round(padw + 0.1);
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Resize::Run(mat, new_shape_w, new_shape_h, -1.0, -1.0, 3, false, ProcLib::CUDA);
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Pad::Run(mat, top, bottom, left, right, color_, ProcLib::CUDA);
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return true;
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}
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#endif
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bool LetterBoxResize::Run(Mat* mat, const std::vector<int>& target_size, const std::vector<float>& color,ProcLib lib) {
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auto l = LetterBoxResize(target_size,color);
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return l(mat, lib);
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return l(mat,lib);
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}
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} // namespace vision
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@@ -27,13 +27,21 @@ class LetterBoxResize : public Processor {
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color_ = color;
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}
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std::string Name() { return "LetterBoxResize"; }
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std::string Name() override { return "LetterBoxResize"; }
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bool ImplByOpenCV(Mat* mat) override;
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#ifdef ENABLE_FLYCV
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bool ImplByFlyCV(FDMat* mat)override;
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#endif
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#ifdef ENABLE_CVCUDA
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virtual bool ImplByCvCuda(FDMat* mat)override;
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#endif
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virtual bool operator()(Mat* mat, ProcLib lib = ProcLib::DEFAULT);
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#ifdef ENABLE_CUDA
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virtual bool ImplByCuda(FDMat* mat);
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#endif
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static bool Run(Mat* mat, const std::vector<int>& target_size,
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const std::vector<float>& color,
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ProcLib lib = ProcLib::DEFAULT);
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const std::vector<float>& color,ProcLib lib = ProcLib::DEFAULT);
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private:
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std::vector<int> target_size_;
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