Modify YOLOv7 Infer file and the external model namespace

csrcs/fastdeploy/vision.h

@@ -15,29 +15,27 @@
 
 #include "fastdeploy/core/config.h"
 #ifdef ENABLE_VISION
-#include "fastdeploy/vision/biubug6/retinaface.h"
-#include "fastdeploy/vision/deepcam/yolov5face.h"
-#include "fastdeploy/vision/deepinsight/arcface.h"
-#include "fastdeploy/vision/deepinsight/cosface.h"
-#include "fastdeploy/vision/deepinsight/insightface_rec.h"
-#include "fastdeploy/vision/deepinsight/partial_fc.h"
-#include "fastdeploy/vision/deepinsight/scrfd.h"
-#include "fastdeploy/vision/deepinsight/vpl.h"
-
+#include "fastdeploy/vision/detection/contrib/nanodet_plus.h"
 #include "fastdeploy/vision/detection/contrib/scaledyolov4.h"
 #include "fastdeploy/vision/detection/contrib/yolor.h"
+#include "fastdeploy/vision/detection/contrib/yolov5.h"
+#include "fastdeploy/vision/detection/contrib/yolov5lite.h"
+#include "fastdeploy/vision/detection/contrib/yolov6.h"
 #include "fastdeploy/vision/detection/contrib/yolov7.h"
-#include "fastdeploy/vision/detection/ppdet/model.h"
-
-#include "fastdeploy/vision/linzaer/ultraface.h"
-#include "fastdeploy/vision/megvii/yolox.h"
-#include "fastdeploy/vision/meituan/yolov6.h"
+#include "fastdeploy/vision/detection/contrib/yolox.h"
+#include "fastdeploy/vision/facedet/contrib/retinaface.h"
+#include "fastdeploy/vision/facedet/contrib/scrfd.h"
+#include "fastdeploy/vision/facedet/contrib/ultraface.h"
+#include "fastdeploy/vision/facedet/contrib/yolov5face.h"
+#include "fastdeploy/vision/faceid/contrib/arcface.h"
+#include "fastdeploy/vision/faceid/contrib/cosface.h"
+#include "fastdeploy/vision/faceid/contrib/insightface_rec.h"
+#include "fastdeploy/vision/faceid/contrib/partial_fc.h"
+#include "fastdeploy/vision/faceid/contrib/vpl.h"
+#include "fastdeploy/vision/matting/contrib/modnet.h"
 #include "fastdeploy/vision/ppcls/model.h"
-#include "fastdeploy/vision/ppogg/yolov5lite.h"
+#include "fastdeploy/vision/detection/ppdet/model.h"
 #include "fastdeploy/vision/ppseg/model.h"
-#include "fastdeploy/vision/rangilyu/nanodet_plus.h"
-#include "fastdeploy/vision/ultralytics/yolov5.h"
-#include "fastdeploy/vision/zhkkke/modnet.h"
 #endif
 
 #include "fastdeploy/vision/visualize/visualize.h"

csrcs/fastdeploy/vision/rangilyu/nanodet_plus.cc → csrcs/fastdeploy/vision/detection/contrib/nanodet_plus.cc

@@ -10,15 +10,15 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include "fastdeploy/vision/rangilyu/nanodet_plus.h"
+#include "fastdeploy/vision/detection/contrib/nanodet_plus.h"
 #include "fastdeploy/utils/perf.h"
 #include "fastdeploy/vision/utils/utils.h"
 
 namespace fastdeploy {
 
 namespace vision {
 
-namespace rangilyu {
+namespace detection {
 
 struct NanoDetPlusCenterPoint {
   int grid0;
@@ -350,6 +350,6 @@ bool NanoDetPlus::Predict(cv::Mat* im, DetectionResult* result,
   return true;
 }
 
-}  // namespace rangilyu
+}  // namespace detection
 }  // namespace vision
 }  // namespace fastdeploy

csrcs/fastdeploy/vision/rangilyu/nanodet_plus.h → csrcs/fastdeploy/vision/detection/contrib/nanodet_plus.h

@@ -22,7 +22,7 @@ namespace fastdeploy {
 
 namespace vision {
 
-namespace rangilyu {
+namespace detection {
 
 class FASTDEPLOY_DECL NanoDetPlus : public FastDeployModel {
  public:
@@ -34,7 +34,7 @@ class FASTDEPLOY_DECL NanoDetPlus : public FastDeployModel {
               const Frontend& model_format = Frontend::ONNX);
 
   // 定义模型的名称
-  std::string ModelName() const { return "RangiLyu/nanodet"; }
+  std::string ModelName() const { return "nanodet"; }
 
   // 模型预测接口，即用户调用的接口
   // im 为用户的输入数据，目前对于CV均定义为cv::Mat
@@ -96,6 +96,6 @@ class FASTDEPLOY_DECL NanoDetPlus : public FastDeployModel {
   bool is_dynamic_input_;
 };
 
-}  // namespace rangilyu
+}  // namespace detection
 }  // namespace vision
 }  // namespace fastdeploy

csrcs/fastdeploy/vision/megvii/megvii_pybind.cc → csrcs/fastdeploy/vision/detection/contrib/nanodet_plus_pybind.cc

@@ -15,27 +15,25 @@
 #include "fastdeploy/pybind/main.h"
 
 namespace fastdeploy {
-void BindMegvii(pybind11::module& m) {
-  auto megvii_module =
-      m.def_submodule("megvii", "https://github.com/megvii/YOLOX");
-  pybind11::class_<vision::megvii::YOLOX, FastDeployModel>(
-      megvii_module, "YOLOX")
+void BindNanoDetPlus(pybind11::module& m) {
+  pybind11::class_<vision::detection::NanoDetPlus, FastDeployModel>(
+      m, "NanoDetPlus")
       .def(pybind11::init<std::string, std::string, RuntimeOption, Frontend>())
       .def("predict",
-           [](vision::megvii::YOLOX& self, pybind11::array& data,
+           [](vision::detection::NanoDetPlus& self, pybind11::array& data,
               float conf_threshold, float nms_iou_threshold) {
              auto mat = PyArrayToCvMat(data);
              vision::DetectionResult res;
              self.Predict(&mat, &res, conf_threshold, nms_iou_threshold);
              return res;
            })
-      .def_readwrite("size", &vision::megvii::YOLOX::size)
+      .def_readwrite("size", &vision::detection::NanoDetPlus::size)
       .def_readwrite("padding_value",
-                     &vision::megvii::YOLOX::padding_value)
-      .def_readwrite("is_decode_exported", 
-                     &vision::megvii::YOLOX::is_decode_exported)
+                     &vision::detection::NanoDetPlus::padding_value)
+      .def_readwrite("keep_ratio", &vision::detection::NanoDetPlus::keep_ratio)
       .def_readwrite("downsample_strides",
-                     &vision::megvii::YOLOX::downsample_strides)
-      .def_readwrite("max_wh", &vision::megvii::YOLOX::max_wh);
+                     &vision::detection::NanoDetPlus::downsample_strides)
+      .def_readwrite("max_wh", &vision::detection::NanoDetPlus::max_wh)
+      .def_readwrite("reg_max", &vision::detection::NanoDetPlus::reg_max);
 }
 }  // namespace fastdeploy

csrcs/fastdeploy/vision/ultralytics/yolov5.cc → csrcs/fastdeploy/vision/detection/contrib/yolov5.cc

@@ -12,17 +12,17 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include "fastdeploy/vision/ultralytics/yolov5.h"
+#include "fastdeploy/vision/detection/contrib/yolov5.h"
 #include "fastdeploy/utils/perf.h"
 #include "fastdeploy/vision/utils/utils.h"
 
 namespace fastdeploy {
 namespace vision {
-namespace ultralytics {
+namespace detection {
 
-void LetterBox(Mat* mat, std::vector<int> size, std::vector<float> color,
-               bool _auto, bool scale_fill = false, bool scale_up = true,
-               int stride = 32) {
+void YOLOv5::LetterBox(Mat* mat, std::vector<int> size,
+                       std::vector<float> color, bool _auto, bool scale_fill,
+                       bool scale_up, int stride) {
   float scale =
       std::min(size[1] * 1.0 / mat->Height(), size[0] * 1.0 / mat->Width());
   if (!scale_up) {
@@ -204,9 +204,9 @@ bool YOLOv5::Postprocess(
   }
 
   if (result->boxes.size() == 0) {
-    return  true;
+    return true;
   }
- 
+
   utils::NMS(result, nms_iou_threshold);
 
   // scale the boxes to the origin image shape
@@ -290,6 +290,6 @@ bool YOLOv5::Predict(cv::Mat* im, DetectionResult* result, float conf_threshold,
   return true;
 }
 
-}  // namespace ultralytics
+}  // namespace detection
 }  // namespace vision
 }  // namespace fastdeploy

csrcs/fastdeploy/vision/ultralytics/yolov5.h → csrcs/fastdeploy/vision/detection/contrib/yolov5.h

@@ -19,7 +19,7 @@
 
 namespace fastdeploy {
 namespace vision {
-namespace ultralytics {
+namespace detection {
 
 class FASTDEPLOY_DECL YOLOv5 : public FastDeployModel {
  public:
@@ -30,7 +30,7 @@ class FASTDEPLOY_DECL YOLOv5 : public FastDeployModel {
          const Frontend& model_format = Frontend::ONNX);
 
   // 定义模型的名称
-  std::string ModelName() const { return "ultralytics/yolov5"; }
+  std::string ModelName() const { return "yolov5"; }
 
   // 模型预测接口，即用户调用的接口
   // im 为用户的输入数据，目前对于CV均定义为cv::Mat
@@ -39,7 +39,7 @@ class FASTDEPLOY_DECL YOLOv5 : public FastDeployModel {
   // nms_iou_threshold 为后处理的参数
   virtual bool Predict(cv::Mat* im, DetectionResult* result,
                        float conf_threshold = 0.25,
-                       float nms_iou_threshold = 0.5);               
+                       float nms_iou_threshold = 0.5);
 
   // 以下为模型在预测时的一些参数，基本是前后处理所需
   // 用户在创建模型后，可根据模型的要求，以及自己的需求
@@ -81,21 +81,28 @@ class FASTDEPLOY_DECL YOLOv5 : public FastDeployModel {
   // conf_threshold 后处理时过滤box的置信度阈值
   // nms_iou_threshold 后处理时NMS设定的iou阈值
   // multi_label 后处理时box选取是否采用多标签方式
-  bool Postprocess(
-      FDTensor& infer_result, DetectionResult* result,
-      const std::map<std::string, std::array<float, 2>>& im_info,
-      float conf_threshold, float nms_iou_threshold, bool multi_label);
+  bool Postprocess(FDTensor& infer_result, DetectionResult* result,
+                   const std::map<std::string, std::array<float, 2>>& im_info,
+                   float conf_threshold, float nms_iou_threshold,
+                   bool multi_label);
 
   // 查看输入是否为动态维度的 不建议直接使用 不同模型的逻辑可能不一致
-  bool IsDynamicInput() const { return is_dynamic_input_; }        
+  bool IsDynamicInput() const { return is_dynamic_input_; }
 
-  // whether to inference with dynamic shape (e.g ONNX export with dynamic shape or not.)
-  // YOLOv5 official 'export_onnx.py' script will export dynamic ONNX by default.
-  // while is_dynamic_shape if 'false', is_mini_pad will force 'false'. This value will
-  // auto check by fastdeploy after the internal Runtime already initialized. 
+  void LetterBox(Mat* mat, std::vector<int> size, std::vector<float> color,
+                 bool _auto, bool scale_fill = false, bool scale_up = true,
+                 int stride = 32);
+
+  // whether to inference with dynamic shape (e.g ONNX export with dynamic shape
+  // or not.)
+  // YOLOv5 official 'export_onnx.py' script will export dynamic ONNX by
+  // default.
+  // while is_dynamic_shape if 'false', is_mini_pad will force 'false'. This
+  // value will
+  // auto check by fastdeploy after the internal Runtime already initialized.
   bool is_dynamic_input_;
 };
 
-}  // namespace ultralytics
+}  // namespace detection
 }  // namespace vision
 }  // namespace fastdeploy