Add RKYOLOv5 RKYOLOX RKYOLOV7 (#709)

* 更正代码格式 * 更正代码格式 * 修复语法错误 * fix rk error * update * update * update * update * update * update * update Co-authored-by: Jason <jiangjiajun@baidu.com>
2025-10-06 09:07:10 +08:00 · 2022-12-10 15:44:00 +08:00
parent 6f5521e63e
commit c7dc7d5eee
25 changed files with 1516 additions and 1 deletions
--- a/fastdeploy/vision/detection/contrib/rknpu2/postprocessor.h
+++ b/fastdeploy/vision/detection/contrib/rknpu2/postprocessor.h
@@ -0,0 +1,105 @@
+// 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"
+#include "fastdeploy/vision/detection/contrib/rknpu2/utils.h"
+#include <array>
+namespace fastdeploy {
+namespace vision {
+namespace detection {
+/*! @brief Postprocessor object for YOLOv5 serials model.
+ */
+class FASTDEPLOY_DECL RKYOLOPostprocessor {
+ public:
+  /** \brief Create a postprocessor instance for YOLOv5 serials model
+   */
+  RKYOLOPostprocessor();
+
+  /** \brief Process the result of runtime and fill to DetectionResult structure
+   *
+   * \param[in] tensors The inference result from runtime
+   * \param[in] result The output result of detection
+   * \param[in] ims_info The shape info list, record input_shape and output_shape
+   * \return true if the postprocess successed, otherwise false
+   */
+  bool Run(const std::vector<FDTensor>& tensors,
+           std::vector<DetectionResult>* results);
+
+  /// Set nms_threshold, default 0.45
+  void SetNMSThreshold(const float& nms_threshold) {
+    nms_threshold_ = nms_threshold;
+  }
+
+  /// Set conf_threshold, default 0.25
+  void SetConfThreshold(const float& conf_threshold) {
+    conf_threshold_ = conf_threshold;
+  }
+
+  /// Get conf_threshold, default 0.25
+  float GetConfThreshold() const { return conf_threshold_; }
+
+  /// Get nms_threshold, default 0.45
+  float GetNMSThreshold() const { return nms_threshold_; }
+
+  // Set model_type
+  void SetModelType(ModelType model_type);
+
+  // Set height and weight
+  void SetHeightAndWeight(int& height, int& width) {
+    height_ = height;
+    width_ = width;
+  }
+
+  // Set pad_hw_values
+  void SetPadHWValues(std::vector<std::vector<int>> pad_hw_values) {
+    pad_hw_values_ = pad_hw_values;
+  }
+
+  // Set scale
+  void SetScale(std::vector<float> scale) { scale_ = scale; }
+
+ private:
+  ModelType model_type_ = ModelType::UNKNOWN;
+  std::vector<int> anchors_ = {10, 13, 16,  30,  33, 23,  30,  61,  62,
+                               45, 59, 119, 116, 90, 156, 198, 373, 326};
+  int strides_[3] = {8, 16, 32};
+  int height_ = 0;
+  int width_ = 0;
+  int anchor_per_branch_ = 0;
+
+  // Process Int8 Model
+  int ProcessInt8(int8_t* input, int* anchor, int grid_h, int grid_w,
+                  int stride, std::vector<float>& boxes,
+                  std::vector<float>& boxScores, std::vector<int>& classId,
+                  float threshold, int32_t zp, float scale);
+
+  // Model
+  int QuickSortIndiceInverse(std::vector<float>& input, int left, int right,
+                             std::vector<int>& indices);
+
+  // post_process values
+  std::vector<std::vector<int>> pad_hw_values_;
+  std::vector<float> scale_;
+  float nms_threshold_ = 0.45;
+  float conf_threshold_ = 0.25;
+  int prob_box_size = 85;
+  int obj_class_num = 80;
+  int obj_num_bbox_max_size = 200;
+};
+
+}  // namespace detection
+}  // namespace vision
+}  // namespace fastdeploy