FastDeploy/examples/vision/classification/paddleclas/c/infer.c

// 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.

#include <stdio.h>
#include <stdlib.h>

#include "fastdeploy_capi/vision.h"

#ifdef WIN32
const char sep = '\\';
#else
const char sep = '/';
#endif

void CpuInfer(const char* model_dir, const char* image_file) {
  char model_file[100];
  char params_file[100];
  char config_file[100];
  int max_size = 99;
  snprintf(model_file, max_size, "%s%c%s", model_dir, sep, "inference.pdmodel");
  snprintf(params_file, max_size, "%s%c%s", model_dir, sep,
           "inference.pdiparams");
  snprintf(config_file, max_size, "%s%c%s", model_dir, sep,
           "inference_cls.yaml");

  FD_C_RuntimeOptionWrapper* option = FD_C_CreateRuntimeOptionWrapper();
  FD_C_RuntimeOptionWrapperUseCpu(option);

  FD_C_PaddleClasModelWrapper* model = FD_C_CreatePaddleClasModelWrapper(
      model_file, params_file, config_file, option, PADDLE);

  if (!FD_C_PaddleClasModelWrapperInitialized(model)) {
    printf("Failed to initialize.\n");
    FD_C_DestroyRuntimeOptionWrapper(option);
    FD_C_DestroyPaddleClasModelWrapper(model);
    return;
  }

  FD_C_Mat im = FD_C_Imread(image_file);

  FD_C_ClassifyResult* result =
      (FD_C_ClassifyResult*)malloc(sizeof(FD_C_ClassifyResult));

  if (!FD_C_PaddleClasModelWrapperPredict(model, im, result)) {
    printf("Failed to predict.\n");
    FD_C_DestroyRuntimeOptionWrapper(option);
    FD_C_DestroyPaddleClasModelWrapper(model);
    FD_C_DestroyMat(im);
    free(result);
    return;
  }

  // print res
  // You can directly access fields in FD_C_ClassifyResult and print it refer to
  // ClassifyResult API Doc Or you can wrap it using
  // FD_C_ClassifyResult_Wrapper, which containes C++ structure
  // fastdeploy::vision::ClassifyResult, and using C API
  // FD_C_ClassifyResultWrapperStr to call
  // fastdeploy::vision::ClassifyResult::Str() in it. For convenience, we choose
  // this method to print it.
  FD_C_ClassifyResultWrapper* result_wrapper =
      FD_C_CreateClassifyResultWrapperFromData(result);
  printf("%s", FD_C_ClassifyResultWrapperStr(result_wrapper));
  FD_C_DestroyRuntimeOptionWrapper(option);
  FD_C_DestroyPaddleClasModelWrapper(model);
  FD_C_DestroyClassifyResultWrapper(result_wrapper);
  FD_C_DestroyClassifyResult(result);
  FD_C_DestroyMat(im);
}

void GpuInfer(const char* model_dir, const char* image_file) {
  char model_file[100];
  char params_file[100];
  char config_file[100];
  int max_size = 99;
  snprintf(model_file, max_size, "%s%c%s", model_dir, sep, "inference.pdmodel");
  snprintf(params_file, max_size, "%s%c%s", model_dir, sep,
           "inference.pdiparams");
  snprintf(config_file, max_size, "%s%c%s", model_dir, sep,
           "inference_cls.yaml");

  FD_C_RuntimeOptionWrapper* option = FD_C_CreateRuntimeOptionWrapper();
  FD_C_RuntimeOptionWrapperUseGpu(option, 0);

  FD_C_PaddleClasModelWrapper* model = FD_C_CreatePaddleClasModelWrapper(
      model_file, params_file, config_file, option, PADDLE);

  if (!FD_C_PaddleClasModelWrapperInitialized(model)) {
    printf("Failed to initialize.\n");
    FD_C_DestroyRuntimeOptionWrapper(option);
    FD_C_DestroyPaddleClasModelWrapper(model);
    return;
  }

  FD_C_Mat im = FD_C_Imread(image_file);

  FD_C_ClassifyResult* result =
      (FD_C_ClassifyResult*)malloc(sizeof(FD_C_ClassifyResult));

  if (!FD_C_PaddleClasModelWrapperPredict(model, im, result)) {
    printf("Failed to predict.\n");
    FD_C_DestroyRuntimeOptionWrapper(option);
    FD_C_DestroyPaddleClasModelWrapper(model);
    FD_C_DestroyMat(im);
    free(result);
    return;
  }

  // print res
  // You can directly access fields in FD_C_ClassifyResult and print it refer to
  // ClassifyResult API Doc Or you can wrap it using
  // FD_C_ClassifyResult_Wrapper, which containes C++ structure
  // fastdeploy::vision::ClassifyResult, and using C API
  // FD_C_ClassifyResultWrapperStr to call
  // fastdeploy::vision::ClassifyResult::Str() in it. For convenience, we choose
  // this method to print it.
  FD_C_ClassifyResultWrapper* result_wrapper =
      FD_C_CreateClassifyResultWrapperFromData(result);
  printf("%s", FD_C_ClassifyResultWrapperStr(result_wrapper));
  FD_C_DestroyRuntimeOptionWrapper(option);
  FD_C_DestroyPaddleClasModelWrapper(model);
  FD_C_DestroyClassifyResultWrapper(result_wrapper);
  FD_C_DestroyClassifyResult(result);
  FD_C_DestroyMat(im);
}

int main(int argc, char* argv[]) {
  if (argc < 4) {
    printf(
        "Usage: infer_demo path/to/model_dir path/to/image run_option, "
        "e.g ./infer_model ./ppyoloe_model_dir ./test.jpeg 0"
        "\n");
    printf(
        "The data type of run_option is int, 0: run with cpu; 1: run with gpu"
        "\n");
    return -1;
  }

  if (atoi(argv[3]) == 0) {
    CpuInfer(argv[1], argv[2]);
  } else if (atoi(argv[3]) == 1) {
    GpuInfer(argv[1], argv[2]);
  }
  return 0;
}