[Other]Refactor PaddleSeg with preprocessor && postprocessor && support batch (#639)

* Refactor PaddleSeg with preprocessor && postprocessor

* Fix bugs

* Delete redundancy code

* Modify by comments

* Refactor according to comments

* Add batch evaluation

* Add single test script

* Add ppliteseg single test script && fix eval(raise) error

* fix bug

* Fix evaluation segmentation.py batch predict

* Fix segmentation evaluation bug

* Fix evaluation segmentation bugs

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

fastdeploy/vision/segmentation/ppseg/preprocessor.h

@@ -0,0 +1,73 @@
+// 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 segmentation {
+
+class FASTDEPLOY_DECL PaddleSegPreprocessor {
+ public:
+  /** \brief Create a preprocessor instance for PaddleSeg serials model
+   *
+   * \param[in] config_file Path of configuration file for deployment, e.g ppliteseg/deploy.yaml
+   */
+  explicit PaddleSegPreprocessor(const std::string& config_file);
+
+  /** \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, include image
+   * \return true if the preprocess successed, otherwise false
+   */
+  virtual bool Run(
+    std::vector<FDMat>* images,
+    std::vector<FDTensor>* outputs,
+    std::map<std::string, std::vector<std::array<int, 2>>>* imgs_info);
+
+  /// Get is_vertical_screen property of PP-HumanSeg model, default is false
+  bool GetIsVerticalScreen() const {
+    return is_vertical_screen_;
+  }
+
+  /// Set is_vertical_screen value, bool type required
+  void SetIsVerticalScreen(bool value) {
+    is_vertical_screen_ = value;
+  }
+
+  // This function will disable normalize and hwc2chw in preprocessing step.
+  void DisableNormalizeAndPermute();
+
+ private:
+  virtual bool BuildPreprocessPipelineFromConfig();
+  std::vector<std::shared_ptr<Processor>> processors_;
+  std::string config_file_;
+
+  /** \brief For PP-HumanSeg model, set true if the input image is vertical image(height > width), default value is false
+   */
+  bool is_vertical_screen_ = false;
+
+  // for recording the switch of normalize and hwc2chw
+  bool disable_normalize_and_permute_ = false;
+
+  bool is_contain_resize_op = false;
+
+  bool initialized_ = false;
+};
+
+}  // namespace segmentation
+}  // namespace vision
+}  // namespace fastdeploy