yolov5 servitization optimization (#262)

* yolov5 split pre and post process

* yolov5 postprocess

* yolov5 postprocess

python/fastdeploy/__init__.py

@@ -17,9 +17,10 @@ import os
 import sys
 
 from .c_lib_wrap import (Frontend, Backend, FDDataType, TensorInfo, Device,
-                         is_built_with_gpu, is_built_with_ort,
+                         FDTensor, is_built_with_gpu, is_built_with_ort,
                          is_built_with_paddle, is_built_with_trt,
                          get_default_cuda_directory)
+
 from .runtime import Runtime, RuntimeOption
 from .model import FastDeployModel
 from . import c_lib_wrap as C

python/fastdeploy/runtime.py

@@ -23,7 +23,8 @@ class Runtime:
             runtime_option._option), "Initialize Runtime Failed!"
 
     def infer(self, data):
-        assert isinstance(data, dict), "The input data should be type of dict."
+        assert isinstance(data, dict) or isinstance(
+            data, list), "The input data should be type of dict or list."
         return self._runtime.infer(data)
 
     def num_inputs(self):

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

@@ -37,6 +37,31 @@ class YOLOv5(FastDeployModel):
         return self._model.predict(input_image, conf_threshold,
                                    nms_iou_threshold)
 
+    @staticmethod
+    def preprocess(input_image,
+                   size=[640, 640],
+                   padding_value=[114.0, 114.0, 114.0],
+                   is_mini_pad=False,
+                   is_no_pad=False,
+                   is_scale_up=False,
+                   stride=32,
+                   max_wh=7680.0,
+                   multi_label=True):
+        return C.vision.detection.YOLOv5.preprocess(
+            input_image, size, padding_value, is_mini_pad, is_no_pad,
+            is_scale_up, stride, max_wh, multi_label)
+
+    @staticmethod
+    def postprocess(infer_result,
+                    im_info,
+                    conf_threshold=0.25,
+                    nms_iou_threshold=0.5,
+                    multi_label=True,
+                    max_wh=7680.0):
+        return C.vision.detection.YOLOv5.postprocess(
+            infer_result, im_info, conf_threshold, nms_iou_threshold,
+            multi_label, max_wh)
+
     # 一些跟YOLOv5模型有关的属性封装
     # 多数是预处理相关，可通过修改如model.size = [1280, 1280]改变预处理时resize的大小（前提是模型支持）
     @property