[vision] support PaddleDetection/MaskRCNN model (#218)

* [vision] support padddetection maskrcnn

* [vision] fixed instance mask visualize func

* [vision] optimize instance mask visualize func

* [docs] update ppdet/maskrcnn docs

* [vision] update maskrcnn implementation

Co-authored-by: Jason <jiangjiajun@baidu.com>

examples/vision/detection/paddledetection/python/infer_mask_rcnn.py

@@ -0,0 +1,69 @@
+import fastdeploy as fd
+import cv2
+import os
+
+
+def parse_arguments():
+    import argparse
+    import ast
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--model_dir",
+        required=True,
+        help="Path of PaddleDetection model directory")
+    parser.add_argument(
+        "--image", required=True, help="Path of test image file.")
+    parser.add_argument(
+        "--device",
+        type=str,
+        default='cpu',
+        help="Type of inference device, support 'cpu' or 'gpu'.")
+    parser.add_argument(
+        "--use_trt",
+        type=ast.literal_eval,
+        default=False,
+        help="Wether to use tensorrt.")
+    return parser.parse_args()
+
+
+def build_option(args):
+    option = fd.RuntimeOption()
+
+    if args.device.lower() == "gpu":
+        # option.use_gpu()
+        print(
+            """GPU inference with Backend::Paddle in python has not been supported yet. \
+          \nWill ignore this option.""")
+
+    if args.use_trt:
+        # TODO(qiuyanjun): may remove TRT option
+        # Backend::TRT has not been supported yet.
+        print(
+            """Backend::TRT has not been supported yet, will ignore this option.\
+              \nPaddleDetection/MaskRCNN has only support Backend::Paddle now."""
+        )
+
+    return option
+
+
+args = parse_arguments()
+
+model_file = os.path.join(args.model_dir, "model.pdmodel")
+params_file = os.path.join(args.model_dir, "model.pdiparams")
+config_file = os.path.join(args.model_dir, "infer_cfg.yml")
+
+# 配置runtime，加载模型
+runtime_option = build_option(args)
+model = fd.vision.detection.MaskRCNN(
+    model_file, params_file, config_file, runtime_option=runtime_option)
+
+# 预测图片检测结果
+im = cv2.imread(args.image)
+result = model.predict(im.copy())
+print(result)
+
+# 预测结果可视化
+vis_im = fd.vision.vis_detection(im, result, score_threshold=0.5)
+cv2.imwrite("visualized_result.jpg", vis_im)
+print("Visualized result save in ./visualized_result.jpg")
+print(runtime_option)