apps/FastDeploy
1
0
Fork 0
mirror of https://github.com/PaddlePaddle/FastDeploy.git synced 2025-10-05 08:37:06 +08:00
Code Issues Actions 2 Packages Projects Releases Wiki Activity

[Backend] Add OCR、Seg、 KeypointDetection、Matting、 ernie-3.0 and adaface models for XPU Deploy (#960)

Browse Source 
* [FlyCV] Bump up FlyCV -> official release 1.0.0

* add seg models for XPU

* add ocr model for XPU

* add matting

* add matting python

* fix infer.cc

* add keypointdetection support for XPU

* Add adaface support for XPU

* add ernie-3.0

* fix doc

Co-authored-by: DefTruth <qiustudent_r@163.com>
Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
This commit is contained in:
yeliang2258
2022-12-26 15:02:58 +08:00
committed by GitHub
parent 3b29e86add
commit 7b15f72516
39 changed files with 304 additions and 25 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
examples/vision/keypointdetection/tiny_pose/cpp/README.md Normal file → Executable file
View File

@@ -32,6 +32,8 @@ wget https://bj.bcebos.com/paddlehub/fastdeploy/hrnet_demo.jpg
./infer_tinypose_demo PP_TinyPose_256x192_infer hrnet_demo.jpg 1
# GPU上TensorRT推理
./infer_tinypose_demo PP_TinyPose_256x192_infer hrnet_demo.jpg 2
# XPU推理
./infer_tinypose_demo PP_TinyPose_256x192_infer hrnet_demo.jpg 3
```
运行完成可视化结果如下图所示

38
examples/vision/keypointdetection/tiny_pose/cpp/pptinypose_infer.cc Normal file → Executable file
View File

@@ -53,6 +53,40 @@ void CpuInfer(const std::string& tinypose_model_dir,
<< std::endl;
}
void XpuInfer(const std::string& tinypose_model_dir,
const std::string& image_file) {
auto tinypose_model_file = tinypose_model_dir + sep + "model.pdmodel";
auto tinypose_params_file = tinypose_model_dir + sep + "model.pdiparams";
auto tinypose_config_file = tinypose_model_dir + sep + "infer_cfg.yml";
auto option = fastdeploy::RuntimeOption();
option.UseXpu();
auto tinypose_model = fastdeploy::vision::keypointdetection::PPTinyPose(
tinypose_model_file, tinypose_params_file, tinypose_config_file, option);
if (!tinypose_model.Initialized()) {
std::cerr << "TinyPose Model Failed to initialize." << std::endl;
return;
}
auto im = cv::imread(image_file);
fastdeploy::vision::KeyPointDetectionResult res;
if (!tinypose_model.Predict(&im, &res)) {
std::cerr << "TinyPose Prediction Failed." << std::endl;
return;
} else {
std::cout << "TinyPose Prediction Done!" << std::endl;
}
// 输出预测框结果
std::cout << res.Str() << std::endl;
// 可视化预测结果
auto tinypose_vis_im =
fastdeploy::vision::VisKeypointDetection(im, res, 0.5);
cv::imwrite("tinypose_vis_result.jpg", tinypose_vis_im);
std::cout << "TinyPose visualized result saved in ./tinypose_vis_result.jpg"
<< std::endl;
}
void GpuInfer(const std::string& tinypose_model_dir,
const std::string& image_file) {
auto option = fastdeploy::RuntimeOption();
@@ -129,7 +163,7 @@ int main(int argc, char* argv[]) {
"e.g ./infer_model ./pptinypose_model_dir ./test.jpeg 0"
<< std::endl;
std::cout << "The data type of run_option is int, 0: run with cpu; 1: run "
"with gpu; 2: run with gpu and use tensorrt backend."
"with gpu; 2: run with gpu and use tensorrt backend; 3: run with xpu."
<< std::endl;
return -1;
}
@@ -140,6 +174,8 @@ int main(int argc, char* argv[]) {
GpuInfer(argv[1], argv[2]);
} else if (std::atoi(argv[3]) == 2) {
TrtInfer(argv[1], argv[2]);
} else if (std::atoi(argv[3]) == 3) {
TrtInfer(argv[1], argv[2]);
}
return 0;
}