PaddleX/deploy/ultra-infer/ultra_infer/vision/common/processors/cast.cc

// 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.

#include "ultra_infer/vision/common/processors/cast.h"

#include "ultra_infer/vision/common/processors/utils.h"

namespace ultra_infer {
namespace vision {

bool Cast::ImplByOpenCV(Mat *mat) {
  cv::Mat *im = mat->GetOpenCVMat();
  int c = im->channels();
  if (dtype_ == "float") {
    if (im->type() != CV_32FC(c)) {
      im->convertTo(*im, CV_32FC(c));
    }
  } else if (dtype_ == "double") {
    if (im->type() != CV_64FC(c)) {
      im->convertTo(*im, CV_64FC(c));
    }
  } else {
    FDWARNING << "Cast not support for " << dtype_
              << " now! will skip this operation." << std::endl;
  }
  return true;
}

#ifdef ENABLE_FLYCV
bool Cast::ImplByFlyCV(Mat *mat) {
  fcv::Mat *im = mat->GetFlyCVMat();
  if (dtype_ == "float" && mat->Type() == FDDataType::FP32) {
    return true;
  }
  if (dtype_ == "double" && mat->Type() == FDDataType::FP64) {
    return true;
  }
  if (mat->layout != Layout::HWC) {
    FDERROR
        << "While using FlyCV to cast image, the image must be layout of HWC."
        << std::endl;
    return false;
  }
  if (dtype_ == "float") {
    fcv::Mat new_im;
    auto fcv_type = CreateFlyCVDataType(FDDataType::FP32, im->channels());
    im->convert_to(new_im, fcv_type);
    mat->SetMat(new_im);
  } else if (dtype_ == "double") {
    fcv::Mat new_im;
    auto fcv_type = CreateFlyCVDataType(FDDataType::FP64, im->channels());
    im->convert_to(new_im, fcv_type);
    mat->SetMat(new_im);
  } else {
    FDWARNING << "Cast not support for " << dtype_
              << " now! will skip this operation." << std::endl;
  }
  return true;
}
#endif

#ifdef ENABLE_CVCUDA
bool Cast::ImplByCvCuda(FDMat *mat) {
  FDDataType dst_dtype;
  if (dtype_ == "float") {
    dst_dtype = FDDataType::FP32;
  } else if (dtype_ == "double") {
    dst_dtype = FDDataType::FP64;
  } else {
    FDWARNING << "Cast not support for " << dtype_
              << " now! will skip this operation." << std::endl;
    return false;
  }
  if (mat->Type() == dst_dtype) {
    return true;
  }

  // Prepare input tensor
  FDTensor *src = CreateCachedGpuInputTensor(mat);
  auto src_tensor = CreateCvCudaTensorWrapData(*src);

  // Prepare output tensor
  mat->output_cache->Resize(src->Shape(), dst_dtype, "output_cache",
                            Device::GPU);
  auto dst_tensor =
      CreateCvCudaTensorWrapData(*(mat->output_cache), mat->layout);

  cvcuda_convert_op_(mat->Stream(), *src_tensor, *dst_tensor, 1.0f, 0.0f);

  mat->SetTensor(mat->output_cache);
  mat->mat_type = ProcLib::CVCUDA;
  return true;
}
#endif

bool Cast::Run(Mat *mat, const std::string &dtype, ProcLib lib) {
  auto c = Cast(dtype);
  return c(mat, lib);
}

} // namespace vision
} // namespace ultra_infer