yolov5.h

// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.  //NOLINT
//
// 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/fastdeploy_model.h"
#include "fastdeploy/vision/detection/contrib/yolov5/preprocessor.h"
#include "fastdeploy/vision/detection/contrib/yolov5/postprocessor.h"

namespace fastdeploy {
namespace vision {
namespace detection {
class FASTDEPLOY_DECL YOLOv5 : public FastDeployModel {
 public:
  YOLOv5(const std::string& model_file, const std::string& params_file = "",
         const RuntimeOption& custom_option = RuntimeOption(),
         const ModelFormat& model_format = ModelFormat::ONNX);

  std::string ModelName() const { return "yolov5"; }

  virtual bool Predict(cv::Mat* im, DetectionResult* result,
                       float conf_threshold = 0.25,
                       float nms_threshold = 0.5);

  virtual bool Predict(const cv::Mat& img, DetectionResult* result);

  virtual bool BatchPredict(const std::vector<cv::Mat>& imgs,
                            std::vector<DetectionResult>* results);

  virtual YOLOv5Preprocessor& GetPreprocessor() {
    return preprocessor_;
  }

  virtual YOLOv5Postprocessor& GetPostprocessor() {
    return postprocessor_;
  }

 protected:
  bool Initialize();
  YOLOv5Preprocessor preprocessor_;
  YOLOv5Postprocessor postprocessor_;
};

}  // namespace detection
}  // namespace vision
}  // namespace fastdeploy