yolov5seg.cc 2.7 KB

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  1. // Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
  2. //
  3. // Licensed under the Apache License, Version 2.0 (the "License");
  4. // you may not use this file except in compliance with the License.
  5. // You may obtain a copy of the License at
  6. //
  7. // http://www.apache.org/licenses/LICENSE-2.0
  8. //
  9. // Unless required by applicable law or agreed to in writing, software
  10. // distributed under the License is distributed on an "AS IS" BASIS,
  11. // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  12. // See the License for the specific language governing permissions and
  13. // limitations under the License.
  14. #include "ultra_infer/vision/detection/contrib/yolov5seg/yolov5seg.h"
  15. namespace ultra_infer {
  16. namespace vision {
  17. namespace detection {
  18. YOLOv5Seg::YOLOv5Seg(const std::string &model_file,
  19. const std::string &params_file,
  20. const RuntimeOption &custom_option,
  21. const ModelFormat &model_format) {
  22. if (model_format == ModelFormat::ONNX) {
  23. valid_cpu_backends = {Backend::OPENVINO, Backend::ORT};
  24. valid_gpu_backends = {Backend::ORT, Backend::TRT};
  25. } else {
  26. valid_cpu_backends = {Backend::PDINFER, Backend::ORT, Backend::LITE};
  27. valid_gpu_backends = {Backend::PDINFER, Backend::ORT, Backend::TRT};
  28. }
  29. runtime_option = custom_option;
  30. runtime_option.model_format = model_format;
  31. runtime_option.model_file = model_file;
  32. runtime_option.params_file = params_file;
  33. initialized = Initialize();
  34. }
  35. bool YOLOv5Seg::Initialize() {
  36. if (!InitRuntime()) {
  37. FDERROR << "Failed to initialize ultra_infer backend." << std::endl;
  38. return false;
  39. }
  40. return true;
  41. }
  42. bool YOLOv5Seg::Predict(const cv::Mat &im, DetectionResult *result) {
  43. std::vector<DetectionResult> results;
  44. if (!BatchPredict({im}, &results)) {
  45. return false;
  46. }
  47. *result = std::move(results[0]);
  48. return true;
  49. }
  50. bool YOLOv5Seg::BatchPredict(const std::vector<cv::Mat> &images,
  51. std::vector<DetectionResult> *results) {
  52. std::vector<std::map<std::string, std::array<float, 2>>> ims_info;
  53. std::vector<FDMat> fd_images = WrapMat(images);
  54. if (!preprocessor_.Run(&fd_images, &reused_input_tensors_, &ims_info)) {
  55. FDERROR << "Failed to preprocess the input image." << std::endl;
  56. return false;
  57. }
  58. reused_input_tensors_[0].name = InputInfoOfRuntime(0).name;
  59. if (!Infer(reused_input_tensors_, &reused_output_tensors_)) {
  60. FDERROR << "Failed to inference by runtime." << std::endl;
  61. return false;
  62. }
  63. if (!postprocessor_.Run(reused_output_tensors_, results, ims_info)) {
  64. FDERROR << "Failed to postprocess the inference results by runtime."
  65. << std::endl;
  66. return false;
  67. }
  68. return true;
  69. }
  70. } // namespace detection
  71. } // namespace vision
  72. } // namespace ultra_infer