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

* [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>

examples/vision/keypointdetection/det_keypoint_unite/cpp/README.md

@@ -33,6 +33,8 @@ wget https://bj.bcebos.com/paddlehub/fastdeploy/000000018491.jpg
 ./infer_demo PP_PicoDet_V2_S_Pedestrian_320x320_infer PP_TinyPose_256x192_infer 000000018491.jpg 1
 # GPU上TensorRT推理
 ./infer_demo PP_PicoDet_V2_S_Pedestrian_320x320_infer PP_TinyPose_256x192_infer 000000018491.jpg 2
+# XPU推理
+./infer_demo PP_PicoDet_V2_S_Pedestrian_320x320_infer PP_TinyPose_256x192_infer 000000018491.jpg 3
 ```
 
 运行完成可视化结果如下图所示

examples/vision/keypointdetection/det_keypoint_unite/cpp/det_keypoint_unite_infer.cc

@@ -66,6 +66,55 @@ void CpuInfer(const std::string& det_model_dir,
             << std::endl;
 }
 
+void XpuInfer(const std::string& det_model_dir,
+              const std::string& tinypose_model_dir,
+              const std::string& image_file) {
+  auto option = fastdeploy::RuntimeOption();
+  option.UseXpu();
+  auto det_model_file = det_model_dir + sep + "model.pdmodel";
+  auto det_params_file = det_model_dir + sep + "model.pdiparams";
+  auto det_config_file = det_model_dir + sep + "infer_cfg.yml";
+  auto det_model = fastdeploy::vision::detection::PicoDet(
+      det_model_file, det_params_file, det_config_file, option);
+  if (!det_model.Initialized()) {
+    std::cerr << "Detection Model Failed to initialize." << std::endl;
+    return;
+  }
+
+  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 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;
+
+  auto pipeline =
+      fastdeploy::pipeline::PPTinyPose(
+          &det_model, &tinypose_model);
+  pipeline.detection_model_score_threshold = 0.5;
+  if (!pipeline.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 vis_im =
+      fastdeploy::vision::VisKeypointDetection(im, res, 0.2);
+  cv::imwrite("vis_result.jpg", vis_im);
+  std::cout << "TinyPose visualized result saved in ./vis_result.jpg"
+            << std::endl;
+}
+
 void GpuInfer(const std::string& det_model_dir,
               const std::string& tinypose_model_dir,
               const std::string& image_file) {
@@ -180,7 +229,7 @@ int main(int argc, char* argv[]) {
                  "./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;
   }
@@ -191,6 +240,8 @@ int main(int argc, char* argv[]) {
     GpuInfer(argv[1], argv[2], argv[3]);
   } else if (std::atoi(argv[4]) == 2) {
     TrtInfer(argv[1], argv[2], argv[3]);
+  } else if (std::atoi(argv[4]) == 3) {
+    XpuInfer(argv[1], argv[2], argv[3]);
   }
   return 0;
 }