model.h

// 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/fastdeploy_model.h"
#include "fastdeploy/vision/classification/ppcls/preprocessor.h"
#include "fastdeploy/vision/classification/ppcls/postprocessor.h"

namespace fastdeploy {
namespace vision {
namespace classification {
class FASTDEPLOY_DECL PaddleClasModel : public FastDeployModel {
 public:
  PaddleClasModel(const std::string& model_file, const std::string& params_file,
                  const std::string& config_file,
                  const RuntimeOption& custom_option = RuntimeOption(),
                  const ModelFormat& model_format = ModelFormat::PADDLE);

  virtual std::unique_ptr<PaddleClasModel> Clone() const;

  virtual std::string ModelName() const { return "PaddleClas/Model"; }

  virtual bool Predict(cv::Mat* im, ClassifyResult* result, int topk = 1);


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

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

  virtual bool Predict(const FDMat& mat, ClassifyResult* result);

  virtual bool BatchPredict(const std::vector<FDMat>& mats,
                            std::vector<ClassifyResult>* results);

  virtual PaddleClasPreprocessor& GetPreprocessor() {
    return preprocessor_;
  }

  virtual PaddleClasPostprocessor& GetPostprocessor() {
    return postprocessor_;
  }

 protected:
  bool Initialize();
  PaddleClasPreprocessor preprocessor_;
  PaddleClasPostprocessor postprocessor_;
};

typedef PaddleClasModel PPLCNet;
typedef PaddleClasModel PPLCNetv2;
typedef PaddleClasModel EfficientNet;
typedef PaddleClasModel GhostNet;
typedef PaddleClasModel MobileNetv1;
typedef PaddleClasModel MobileNetv2;
typedef PaddleClasModel MobileNetv3;
typedef PaddleClasModel ShuffleNetv2;
typedef PaddleClasModel SqueezeNet;
typedef PaddleClasModel Inceptionv3;
typedef PaddleClasModel PPHGNet;
typedef PaddleClasModel ResNet50vd;
typedef PaddleClasModel SwinTransformer;
}  // namespace classification
}  // namespace vision
}  // namespace fastdeploy