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https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-05 16:48:03 +08:00
[Bug fix]add yolov7face landmarks (#1297)
* add yolov7face benchmark * fix review problem * fix review problems
This commit is contained in:
@@ -24,7 +24,7 @@ namespace facedet {
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Yolov7FacePostprocessor::Yolov7FacePostprocessor() {
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Yolov7FacePostprocessor::Yolov7FacePostprocessor() {
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conf_threshold_ = 0.5;
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conf_threshold_ = 0.5;
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nms_threshold_ = 0.45;
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nms_threshold_ = 0.45;
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max_wh_ = 7680.0;
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landmarks_per_face_ = 5;
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}
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}
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bool Yolov7FacePostprocessor::Run(const std::vector<FDTensor>& infer_result,
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bool Yolov7FacePostprocessor::Run(const std::vector<FDTensor>& infer_result,
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@@ -36,6 +36,8 @@ bool Yolov7FacePostprocessor::Run(const std::vector<FDTensor>& infer_result,
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for (size_t bs = 0; bs < batch; ++bs) {
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for (size_t bs = 0; bs < batch; ++bs) {
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(*results)[bs].Clear();
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(*results)[bs].Clear();
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// must be setup landmarks_per_face before reserve
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(*results)[bs].landmarks_per_face = landmarks_per_face_;
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(*results)[bs].Reserve(infer_result[0].shape[1]);
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(*results)[bs].Reserve(infer_result[0].shape[1]);
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if (infer_result[0].dtype != FDDataType::FP32) {
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if (infer_result[0].dtype != FDDataType::FP32) {
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FDERROR << "Only support post process with float32 data." << std::endl;
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FDERROR << "Only support post process with float32 data." << std::endl;
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@@ -61,6 +63,15 @@ bool Yolov7FacePostprocessor::Run(const std::vector<FDTensor>& infer_result,
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(*results)[bs].boxes.emplace_back(std::array<float, 4>{
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(*results)[bs].boxes.emplace_back(std::array<float, 4>{
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(x - w / 2.f), (y - h / 2.f), (x + w / 2.f), (y + h / 2.f)});
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(x - w / 2.f), (y - h / 2.f), (x + w / 2.f), (y + h / 2.f)});
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(*results)[bs].scores.push_back(confidence);
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(*results)[bs].scores.push_back(confidence);
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// decode landmarks (default 5 landmarks)
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if (landmarks_per_face_ > 0) {
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float* landmarks_ptr = const_cast<float*>(reg_cls_ptr + 6);
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for (size_t j = 0; j < landmarks_per_face_ * 3; j += 3) {
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(*results)[bs].landmarks.emplace_back(
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std::array<float, 2>{landmarks_ptr[j], landmarks_ptr[j + 1]});
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}
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}
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}
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}
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if ((*results)[bs].boxes.size() == 0) {
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if ((*results)[bs].boxes.size() == 0) {
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@@ -79,9 +90,9 @@ bool Yolov7FacePostprocessor::Run(const std::vector<FDTensor>& infer_result,
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float ipt_h = iter_ipt->second[0];
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float ipt_h = iter_ipt->second[0];
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float ipt_w = iter_ipt->second[1];
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float ipt_w = iter_ipt->second[1];
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float scale = std::min(out_h / ipt_h, out_w / ipt_w);
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float scale = std::min(out_h / ipt_h, out_w / ipt_w);
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float pad_h = (out_h - ipt_h * scale) / 2;
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float pad_w = (out_w - ipt_w * scale) / 2;
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for (size_t i = 0; i < (*results)[bs].boxes.size(); ++i) {
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for (size_t i = 0; i < (*results)[bs].boxes.size(); ++i) {
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float pad_h = (out_h - ipt_h * scale) / 2;
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float pad_w = (out_w - ipt_w * scale) / 2;
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// clip box
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// clip box
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(*results)[bs].boxes[i][0] = std::max(((*results)[bs].boxes[i][0] - pad_w) / scale, 0.0f);
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(*results)[bs].boxes[i][0] = std::max(((*results)[bs].boxes[i][0] - pad_w) / scale, 0.0f);
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(*results)[bs].boxes[i][1] = std::max(((*results)[bs].boxes[i][1] - pad_h) / scale, 0.0f);
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(*results)[bs].boxes[i][1] = std::max(((*results)[bs].boxes[i][1] - pad_h) / scale, 0.0f);
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@@ -92,6 +103,16 @@ bool Yolov7FacePostprocessor::Run(const std::vector<FDTensor>& infer_result,
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(*results)[bs].boxes[i][2] = std::min((*results)[bs].boxes[i][2], ipt_w - 1.0f);
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(*results)[bs].boxes[i][2] = std::min((*results)[bs].boxes[i][2], ipt_w - 1.0f);
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(*results)[bs].boxes[i][3] = std::min((*results)[bs].boxes[i][3], ipt_h - 1.0f);
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(*results)[bs].boxes[i][3] = std::min((*results)[bs].boxes[i][3], ipt_h - 1.0f);
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}
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}
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// scale and clip landmarks
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for (size_t i = 0; i < (*results)[bs].landmarks.size(); ++i) {
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(*results)[bs].landmarks[i][0] =
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std::max(((*results)[bs].landmarks[i][0] - pad_w) / scale, 0.0f);
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(*results)[bs].landmarks[i][1] =
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std::max(((*results)[bs].landmarks[i][1] - pad_h) / scale, 0.0f);
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(*results)[bs].landmarks[i][0] = std::min((*results)[bs].landmarks[i][0], ipt_w - 1.0f);
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(*results)[bs].landmarks[i][1] = std::min((*results)[bs].landmarks[i][1], ipt_h - 1.0f);
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}
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}
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}
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return true;
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return true;
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}
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}
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@@ -56,11 +56,19 @@ class FASTDEPLOY_DECL Yolov7FacePostprocessor{
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/// Get nms_threshold, default 0.45
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/// Get nms_threshold, default 0.45
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float GetNMSThreshold() const { return nms_threshold_; }
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float GetNMSThreshold() const { return nms_threshold_; }
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/// Set landmarks_per_face, default 5
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void SetLandmarksPerFace(const int& landmarks_per_face) {
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landmarks_per_face_ = landmarks_per_face;
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}
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/// Get landmarks_per_face, default 5
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int GetLandmarksPerFace() const { return landmarks_per_face_; }
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protected:
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protected:
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float conf_threshold_;
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float conf_threshold_;
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float nms_threshold_;
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float nms_threshold_;
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bool multi_label_;
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int landmarks_per_face_;
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float max_wh_;
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};
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};
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} // namespace facedet
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} // namespace facedet
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@@ -60,7 +60,8 @@ void BindYOLOv7Face(pybind11::module& m) {
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return results;
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return results;
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})
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})
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.def_property("conf_threshold", &vision::facedet::Yolov7FacePostprocessor::GetConfThreshold, &vision::facedet::Yolov7FacePostprocessor::SetConfThreshold)
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.def_property("conf_threshold", &vision::facedet::Yolov7FacePostprocessor::GetConfThreshold, &vision::facedet::Yolov7FacePostprocessor::SetConfThreshold)
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.def_property("nms_threshold", &vision::facedet::Yolov7FacePostprocessor::GetNMSThreshold, &vision::facedet::Yolov7FacePostprocessor::SetNMSThreshold);
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.def_property("nms_threshold", &vision::facedet::Yolov7FacePostprocessor::GetNMSThreshold, &vision::facedet::Yolov7FacePostprocessor::SetNMSThreshold)
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.def_property("landmarks_per_face", &vision::facedet::Yolov7FacePostprocessor::GetLandmarksPerFace, &vision::facedet::Yolov7FacePostprocessor::SetLandmarksPerFace);
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pybind11::class_<vision::facedet::YOLOv7Face, FastDeployModel>(m, "YOLOv7Face")
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pybind11::class_<vision::facedet::YOLOv7Face, FastDeployModel>(m, "YOLOv7Face")
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.def(pybind11::init<std::string, std::string, RuntimeOption,
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.def(pybind11::init<std::string, std::string, RuntimeOption,
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@@ -107,6 +107,13 @@ class Yolov7FacePostprocessor:
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"""
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"""
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return self._postprocessor.nms_threshold
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return self._postprocessor.nms_threshold
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@property
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def landmarks_per_face(self):
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"""
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landmarks per face for postprocessing, default is 5
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"""
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return self._postprocessor.landmarks_per_face
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@conf_threshold.setter
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@conf_threshold.setter
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def conf_threshold(self, conf_threshold):
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def conf_threshold(self, conf_threshold):
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assert isinstance(conf_threshold, float),\
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assert isinstance(conf_threshold, float),\
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@@ -119,6 +126,11 @@ class Yolov7FacePostprocessor:
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"The value to set `nms_threshold` must be type of float."
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"The value to set `nms_threshold` must be type of float."
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self._postprocessor.nms_threshold = nms_threshold
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self._postprocessor.nms_threshold = nms_threshold
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@landmarks_per_face.setter
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def landmarks_per_face(self, landmarks_per_face):
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assert isinstance(landmarks_per_face, int),\
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"The value to set `landmarks_per_face` must be type of int."
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self._postprocessor.landmarks_per_face = landmarks_per_face
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class YOLOv7Face(FastDeployModel):
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class YOLOv7Face(FastDeployModel):
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def __init__(self,
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def __init__(self,
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