[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/tiny_pose/cpp/README.md

@@ -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

examples/vision/keypointdetection/tiny_pose/cpp/pptinypose_infer.cc

@@ -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;
 }

examples/vision/keypointdetection/tiny_pose/python/README.md

@@ -25,6 +25,8 @@ python pptinypose_infer.py --tinypose_model_dir PP_TinyPose_256x192_infer --imag
 python pptinypose_infer.py --tinypose_model_dir PP_TinyPose_256x192_infer --image hrnet_demo.jpg --device gpu
 # GPU上使用TensorRT推理 （注意：TensorRT推理第一次运行，有序列化模型的操作，有一定耗时，需要耐心等待）
 python pptinypose_infer.py --tinypose_model_dir PP_TinyPose_256x192_infer --image hrnet_demo.jpg --device gpu --use_trt True
+# XPU推理
+python pptinypose_infer.py --tinypose_model_dir PP_TinyPose_256x192_infer --image hrnet_demo.jpg --device xpu
 ```
 
 运行完成可视化结果如下图所示

examples/vision/keypointdetection/tiny_pose/python/pptinypose_infer.py

@@ -17,7 +17,7 @@ def parse_arguments():
         "--device",
         type=str,
         default='cpu',
-        help="type of inference device, support 'cpu' or 'gpu'.")
+        help="type of inference device, support 'cpu', 'xpu' or 'gpu'.")
     parser.add_argument(
         "--use_trt",
         type=ast.literal_eval,
@@ -32,6 +32,9 @@ def build_tinypose_option(args):
     if args.device.lower() == "gpu":
         option.use_gpu()
 
+    if args.device.lower() == "xpu":
+        option.use_xpu()
+
     if args.use_trt:
         option.use_trt_backend()
         option.set_trt_input_shape("image", [1, 3, 256, 192])