[Model] Support PP-StructureV2-Layout model (#1867)

* [Model] init pp-structurev2-layout code * [Model] init pp-structurev2-layout code * [Model] init pp-structurev2-layout code * [Model] add structurev2_layout_preprocessor * [PP-StructureV2] add postprocessor and layout detector class * [PP-StructureV2] add postprocessor and layout detector class * [PP-StructureV2] add postprocessor and layout detector class * [PP-StructureV2] add postprocessor and layout detector class * [PP-StructureV2] add postprocessor and layout detector class * [pybind] add pp-structurev2-layout model pybind * [pybind] add pp-structurev2-layout model pybind * [Bug Fix] fixed code style * [examples] add pp-structurev2-layout c++ examples * [PP-StructureV2] add python example and docs * [benchmark] add pp-structurev2-layout benchmark support
2026-04-23 17:11:21 +08:00 · 2023-05-05 13:05:58 +08:00
parent 2c5fd91a7f
commit 6d0261e9e4
26 changed files with 1255 additions and 23 deletions
@@ -0,0 +1,80 @@
+// 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 ocr {
+
+/*! @brief Postprocessor object for PaddleDet serials model.
+ */
+class FASTDEPLOY_DECL StructureV2LayoutPostprocessor {
+ public:
+  StructureV2LayoutPostprocessor() {}
+  /** \brief Process the result of runtime and fill to batch DetectionResult
+   *
+   * \param[in] tensors The inference result from runtime
+   * \param[in] results The output result of layout detection
+   * \param[in] batch_layout_img_info The image info of input images,
+   *            {{image width, image height, resize width, resize height},...}
+   * \return true if the postprocess successed, otherwise false
+   */
+  bool Run(const std::vector<FDTensor>& tensors,
+           std::vector<DetectionResult>* results,
+           const std::vector<std::array<int, 4>>& batch_layout_img_info);
+
+  /// Set score_threshold_ for layout detection postprocess, default is 0.4
+  void SetScoreThreshold(float score_threshold) { score_threshold_ = score_threshold; }
+  /// Set nms_threshold_ for layout detection postprocess, default is 0.5
+  void SetNMSThreshold(float nms_threshold) { nms_threshold_ = nms_threshold; }
+  /// Set num_class_ for layout detection postprocess, default is 5
+  void SetNumClass(int num_class) { num_class_ = num_class; }
+  /// Set fpn_stride_ for layout detection postprocess, default is {8, 16, 32, 64}
+  void SetFPNStride(const std::vector<int>& fpn_stride) { fpn_stride_ = fpn_stride; }
+  /// Set reg_max_ for layout detection postprocess, default is 8
+  void SetRegMax(int reg_max) { reg_max_ = reg_max; } // should private ?
+  /// Get score_threshold_ of layout detection postprocess, default is 0.4
+  float GetScoreThreshold() const { return score_threshold_; }
+  /// Get nms_threshold_ of layout detection postprocess, default is 0.5
+  float GetNMSThreshold() const { return nms_threshold_; }
+  /// Get num_class_ of layout detection postprocess, default is 5
+  int GetNumClass() const { return num_class_; }
+  /// Get fpn_stride_ of layout detection postprocess, default is {8, 16, 32, 64}
+  std::vector<int> GetFPNStride() const { return fpn_stride_; }
+  /// Get reg_max_ of layout detection postprocess, default is 8
+  int GetRegMax() const { return reg_max_; }
+
+ private:
+  std::array<float, 4> DisPred2Bbox(const std::vector<float>& bbox_pred, int x, int y,
+                                    int stride, int resize_w, int resize_h, int reg_max);
+  bool SingleBatchPostprocessor(const std::vector<FDTensor>& single_batch_tensors,
+                                const std::array<int, 4>& layout_img_info,
+                                DetectionResult* result);
+  void SetSingleBatchExternalData(const std::vector<FDTensor>& tensors,
+                                  std::vector<FDTensor>& single_batch_tensors,
+                                  size_t batch_idx);
+
+  std::vector<int> fpn_stride_ = {8, 16, 32, 64};
+  float score_threshold_ = 0.4;
+  float nms_threshold_ = 0.5;
+  int num_class_ = 5;
+  int reg_max_ = 8;
+};
+
+}  // namespace ocr
+}  // namespace vision
+}  // namespace fastdeploy