FastDeploy/csharp/fastdeploy/vision/classification/ppcls/model.cs

// Copyright (c) 2023 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.

using System;
using System.IO;
using System.Runtime.InteropServices;
using System.Collections.Generic;
using OpenCvSharp;
using fastdeploy.types_internal_c;

namespace fastdeploy {
namespace vision {
namespace classification {

/*! @brief PaddleClas serials model object used when to load a PaddleClas model exported by PaddleClas repository
 */
public class PaddleClasModel {

  /** \brief Set path of model file and configuration file, and the configuration of runtime
   *
   * \param[in] model_file Path of model file, e.g resnet/model.pdmodel
   * \param[in] params_file Path of parameter file, e.g resnet/model.pdiparams, if the model format is ONNX, this parameter will be ignored
   * \param[in] config_file Path of configuration file for deployment, e.g resnet/infer_cfg.yml
   * \param[in] custom_option RuntimeOption for inference, the default will use cpu, and choose the backend defined in `valid_cpu_backends`
   * \param[in] model_format Model format of the loaded model, default is Paddle format
   */
  public PaddleClasModel(string model_file, string params_file,
                         string config_file, RuntimeOption custom_option = null,
                         ModelFormat model_format = ModelFormat.PADDLE) {
    if (custom_option == null) {
      custom_option = new RuntimeOption();
    }
    fd_paddleclas_model_wrapper = FD_C_CreatePaddleClasModelWrapper(
        model_file, params_file, config_file, custom_option.GetWrapperPtr(),
        model_format);
  }

  ~PaddleClasModel() {
    FD_C_DestroyPaddleClasModelWrapper(fd_paddleclas_model_wrapper);
  }

  /// Get model's name
  public string ModelName() {
    return "PaddleClas/Model";
  }

  /** \brief DEPRECATED Predict the classification result for an input image, remove at 1.0 version
   *
   * \param[in] im The input image data, comes from cv::imread()
   *  
   * \return ClassifyResult
   */
  public ClassifyResult Predict(Mat img) {
    FD_ClassifyResult fd_classify_result = new FD_ClassifyResult();
    if(! FD_C_PaddleClasModelWrapperPredict(
        fd_paddleclas_model_wrapper, img.CvPtr,
        ref fd_classify_result))
    {
      return null;
    } // predict
    ClassifyResult classify_result =
        ConvertResult.ConvertCResultToClassifyResult(fd_classify_result);
    FD_C_DestroyClassifyResult(ref fd_classify_result);
    return classify_result;
  }

  /** \brief Predict the classification results for a batch of input images
   *
   * \param[in] imgs, The input image list, each element comes from cv::imread()
   * 
   * \return List<ClassifyResult> 
   */
  public List<ClassifyResult> BatchPredict(List<Mat> imgs){
    FD_OneDimMat imgs_in = new FD_OneDimMat();
    imgs_in.size = (nuint)imgs.Count;
    // Copy data to unmanaged memory
    IntPtr[] mat_ptrs = new IntPtr[imgs_in.size];
    for(int i=0;i < (int)imgs.Count; i++){
      mat_ptrs[i] = imgs[i].CvPtr;
    }
    int size = Marshal.SizeOf(new IntPtr()) * (int)imgs_in.size;
    imgs_in.data = Marshal.AllocHGlobal(size);
    Marshal.Copy(mat_ptrs, 0, imgs_in.data,
                 mat_ptrs.Length);
    FD_OneDimClassifyResult fd_classify_result_array =  new FD_OneDimClassifyResult();
    if (!FD_C_PaddleClasModelWrapperBatchPredict(fd_paddleclas_model_wrapper, imgs_in, ref fd_classify_result_array)){
      return null;
    }
    List<ClassifyResult> results_out = new List<ClassifyResult>();
    for(int i=0;i < (int)imgs.Count; i++){
      FD_ClassifyResult fd_classify_result = (FD_ClassifyResult)Marshal.PtrToStructure(
          fd_classify_result_array.data + i * Marshal.SizeOf(new FD_ClassifyResult()),
          typeof(FD_ClassifyResult));
      results_out.Add(ConvertResult.ConvertCResultToClassifyResult(fd_classify_result));
      FD_C_DestroyClassifyResult(ref fd_classify_result);
    }
    return results_out;
  }

  /// Check whether model is initialized successfully
  public bool Initialized() {
    return FD_C_PaddleClasModelWrapperInitialized(fd_paddleclas_model_wrapper);
  }

  // below are underlying C api
  private IntPtr fd_paddleclas_model_wrapper;
  [DllImport("fastdeploy.dll",
             EntryPoint = "FD_C_CreatePaddleClasModelWrapper")]
  private static extern IntPtr FD_C_CreatePaddleClasModelWrapper(
      string model_file, string params_file, string config_file,
      IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
  [DllImport("fastdeploy.dll",
             EntryPoint = "FD_C_DestroyPaddleClasModelWrapper")]
  private static extern void
  FD_C_DestroyPaddleClasModelWrapper(IntPtr fd_paddleclas_model_wrapper);
  [DllImport("fastdeploy.dll",
             EntryPoint = "FD_C_PaddleClasModelWrapperPredict")]
  private static extern bool
  FD_C_PaddleClasModelWrapperPredict(IntPtr fd_paddleclas_model_wrapper,
                                     IntPtr img,
                                     ref FD_ClassifyResult fd_classify_result);
  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreateClassifyResultWrapper")]
  private static extern IntPtr FD_C_CreateClassifyResultWrapper();
  [DllImport("fastdeploy.dll",
             EntryPoint = "FD_C_DestroyClassifyResultWrapper")]
  private static extern void
  FD_C_DestroyClassifyResultWrapper(IntPtr fd_classify_result_wrapper);
  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyClassifyResult")]
  private static extern void
  FD_C_DestroyClassifyResult(ref FD_ClassifyResult fd_classify_result);
  [DllImport("fastdeploy.dll",
             EntryPoint = "FD_C_ClassifyResultWrapperToCResult")]
  private static extern void
  FD_C_ClassifyResultWrapperToCResult(IntPtr fd_classify_result_wrapper, ref FD_ClassifyResult fd_classify_result);
  [DllImport("fastdeploy.dll",
             EntryPoint = "FD_C_CreateClassifyResultWrapperFromCResult")]
  private static extern IntPtr
  FD_C_CreateClassifyResultWrapperFromCResult(ref FD_ClassifyResult fd_classify_result);

  [DllImport("fastdeploy.dll",
             EntryPoint = "FD_C_PaddleClasModelWrapperInitialized")]
  private static extern bool
  FD_C_PaddleClasModelWrapperInitialized(IntPtr fd_paddleclas_model_wrapper);
  [DllImport("fastdeploy.dll",
             EntryPoint = "FD_C_PaddleClasModelWrapperBatchPredict")]
  private static extern bool
  FD_C_PaddleClasModelWrapperBatchPredict(IntPtr fd_paddleclas_model_wrapper,
                                          FD_OneDimMat imgs,
                                          ref FD_OneDimClassifyResult results);

}

}
}
}