[Model] Refactoring code of YOLOv5Cls with new model type (#1237)

* Refactoring code of YOLOv5Cls with new model type

* fix reviewed problem

* Normalize&HWC2CHW -> NormalizeAndPermute

* remove cast()

fastdeploy/vision/classification/contrib/yolov5cls/preprocessor.h

@@ -0,0 +1,57 @@
+// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+#include "fastdeploy/vision/common/processors/transform.h"
+#include "fastdeploy/vision/common/result.h"
+
+namespace fastdeploy {
+namespace vision {
+
+namespace classification {
+/*! @brief Preprocessor object for YOLOv5Cls serials model.
+ */
+class FASTDEPLOY_DECL YOLOv5ClsPreprocessor {
+ public:
+  /** \brief Create a preprocessor instance for YOLOv5Cls serials model
+   */
+  YOLOv5ClsPreprocessor();
+
+  /** \brief Process the input image and prepare input tensors for runtime
+   *
+   * \param[in] images The input image data list, all the elements are returned by cv::imread()
+   * \param[in] outputs The output tensors which will feed in runtime
+   * \param[in] ims_info The shape info list, record input_shape and output_shape
+   * \return true if the preprocess successed, otherwise false
+   */
+  bool Run(std::vector<FDMat>* images, std::vector<FDTensor>* outputs,
+           std::vector<std::map<std::string, std::array<float, 2>>>* ims_info);
+
+  /// Set target size, tuple of (width, height), default size = {224, 224}
+  void SetSize(const std::vector<int>& size) { size_ = size; }
+
+  /// Get target size, tuple of (width, height), default size = {224, 224}
+  std::vector<int> GetSize() const { return size_; }
+
+ protected:
+  bool Preprocess(FDMat* mat, FDTensor* output,
+                  std::map<std::string, std::array<float, 2>>* im_info);
+
+  // target size, tuple of (width, height), default size = {224, 224}
+  std::vector<int> size_;
+};
+
+}  // namespace classification
+}  // namespace vision
+}  // namespace fastdeploy