[Model] Add is_mini_pad and stride for YOLOv5 python (#949)

* add onnx_ort_runtime demo

* rm in requirements

* support batch eval

* fixed MattingResults bug

* move assignment for DetectionResult

* integrated x2paddle

* add model convert readme

* update readme

* re-lint

* add processor api

* Add MattingResult Free

* change valid_cpu_backends order

* add ppocr benchmark

* mv bs from 64 to 32

* fixed quantize.md

* fixed quantize bugs

* Add Monitor for benchmark

* update mem monitor

* Set trt_max_batch_size default 1

* fixed ocr benchmark bug

* support yolov5 in serving

* Fixed yolov5 serving

* Fixed postprocess

* update yolov5 to 7.0

* add poros runtime demos

* update readme

* Support poros abi=1

* rm useless note

* deal with comments

* support pp_trt for ppseg

* fixed symlink problem

* Add is_mini_pad and stride for yolov5

Co-authored-by: Jason <jiangjiajun@baidu.com>

fastdeploy/vision/detection/contrib/yolov5/preprocessor.h

@@ -61,6 +61,23 @@ class FASTDEPLOY_DECL YOLOv5Preprocessor {
   /// Get is_scale_up, default true
   bool GetScaleUp() const { return is_scale_up_; }
 
+  /// Set is_mini_pad, pad to the minimum rectange
+  /// which height and width is times of stride
+  void SetMiniPad(bool is_mini_pad) {
+    is_mini_pad_ = is_mini_pad;
+  }
+
+  /// Get is_mini_pad, default false
+  bool GetMiniPad() const { return is_mini_pad_; }
+
+  /// Set padding stride, only for mini_pad mode
+  void SetStride(int stride) {
+    stride_ = stride;
+  }
+
+  /// Get padding stride, default 32
+  bool GetStride() const { return stride_; }
+
  protected:
   bool Preprocess(FDMat* mat, FDTensor* output,
                   std::map<std::string, std::array<float, 2>>* im_info);

fastdeploy/vision/detection/contrib/yolov5/yolov5_pybind.cc

@@ -36,7 +36,9 @@ void BindYOLOv5(pybind11::module& m) {
       })
       .def_property("size", &vision::detection::YOLOv5Preprocessor::GetSize, &vision::detection::YOLOv5Preprocessor::SetSize)
       .def_property("padding_value", &vision::detection::YOLOv5Preprocessor::GetPaddingValue, &vision::detection::YOLOv5Preprocessor::SetPaddingValue)
-      .def_property("is_scale_up", &vision::detection::YOLOv5Preprocessor::GetScaleUp, &vision::detection::YOLOv5Preprocessor::SetScaleUp);
+      .def_property("is_scale_up", &vision::detection::YOLOv5Preprocessor::GetScaleUp, &vision::detection::YOLOv5Preprocessor::SetScaleUp)
+      .def_property("is_mini_pad", &vision::detection::YOLOv5Preprocessor::GetMiniPad, &vision::detection::YOLOv5Preprocessor::SetMiniPad)
+      .def_property("stride", &vision::detection::YOLOv5Preprocessor::GetStride, &vision::detection::YOLOv5Preprocessor::SetStride);
 
   pybind11::class_<vision::detection::YOLOv5Postprocessor>(
       m, "YOLOv5Postprocessor")

python/fastdeploy/vision/detection/contrib/yolov5.py

@@ -54,6 +54,20 @@ class YOLOv5Preprocessor:
         """
         return self._preprocessor.is_scale_up
 
+    @property
+    def is_mini_pad(self):
+        """
+        is_mini_pad for preprocessing, pad to the minimum rectange which height and width is times of stride, default false
+        """
+        return self._preprocessor.is_mini_pad
+
+    @property
+    def stride(self):
+        """
+        stride for preprocessing, only for mini_pad mode, default 32
+        """
+        return self._preprocessor.stride
+
     @size.setter
     def size(self, wh):
         assert isinstance(wh, (list, tuple)),\
@@ -77,6 +91,19 @@ class YOLOv5Preprocessor:
             bool), "The value to set `is_scale_up` must be type of bool."
         self._preprocessor.is_scale_up = value
 
+    @is_mini_pad.setter
+    def is_mini_pad(self, value):
+        assert isinstance(
+            value,
+            bool), "The value to set `is_mini_pad` must be type of bool."
+        self._preprocessor.is_mini_pad = value
+
+    @stride.setter
+    def stride(self, value):
+        assert isinstance(
+            stride, int), "The value to set `stride` must be type of int."
+        self._preprocessor.stride = value
+
 
 class YOLOv5Postprocessor:
     def __init__(self):