update detection example

examples/vision/detection/nanodet_plus/python/infer.py

@@ -7,9 +7,9 @@ def parse_arguments():
     import ast
     parser = argparse.ArgumentParser()
     parser.add_argument(
-        "--model", required=True, help="Path of nanodet_plus onnx model.")
+        "--model", default=None, help="Path of nanodet_plus onnx model.")
     parser.add_argument(
-        "--image", required=True, help="Path of test image file.")
+        "--image", default=None, help="Path of test image file.")
     parser.add_argument(
         "--device",
         type=str,
@@ -37,13 +37,21 @@ def build_option(args):
 
 args = parse_arguments()
 
+if args.model is None:
+    model = fd.download_model(name='NanoDetPlus_320')
+else:
+    model = args.model
+
 # 配置runtime，加载模型
 runtime_option = build_option(args)
-model = fd.vision.detection.NanoDetPlus(
-    args.model, runtime_option=runtime_option)
+model = fd.vision.detection.NanoDetPlus(model, runtime_option=runtime_option)
 
 # 预测图片检测结果
-im = cv2.imread(args.image)
+if args.image is None:
+    image = fd.utils.get_detection_test_image()
+else:
+    image = args.image
+im = cv2.imread(image)
 result = model.predict(im.copy())
 print(result)
 

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

@@ -9,10 +9,10 @@ def parse_arguments():
     parser = argparse.ArgumentParser()
     parser.add_argument(
         "--model_dir",
-        required=True,
+        default=None,
         help="Path of PaddleDetection model directory")
     parser.add_argument(
-        "--image", required=True, help="Path of test image file.")
+        "--image", default=None, help="Path of test image file.")
     parser.add_argument(
         "--device",
         type=str,
@@ -41,17 +41,26 @@ def build_option(args):
 
 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")
+if args.model_dir is None:
+    model_dir = fd.download_model(name='faster_rcnn_r50_vd_fpn_2x_coco')
+else:
+    model_dir = args.model_dir
+
+model_file = os.path.join(model_dir, "model.pdmodel")
+params_file = os.path.join(model_dir, "model.pdiparams")
+config_file = os.path.join(model_dir, "infer_cfg.yml")
 
 # 配置runtime，加载模型
 runtime_option = build_option(args)
 model = fd.vision.detection.FasterRCNN(
     model_file, params_file, config_file, runtime_option=runtime_option)
 
 # 预测图片检测结果
-im = cv2.imread(args.image)
+if args.image is None:
+    image = fd.utils.get_detection_test_image()
+else:
+    image = args.image
+im = cv2.imread(image)
 result = model.predict(im.copy())
 print(result)
 

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

@@ -9,10 +9,10 @@ def parse_arguments():
     parser = argparse.ArgumentParser()
     parser.add_argument(
         "--model_dir",
-        required=True,
+        default=None,
         help="Path of PaddleDetection model directory")
     parser.add_argument(
-        "--image", required=True, help="Path of test image file.")
+        "--image", default=None, help="Path of test image file.")
     parser.add_argument(
         "--device",
         type=str,
@@ -48,17 +48,26 @@ def build_option(args):
 
 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")
+if args.model_dir is None:
+    model_dir = fd.download_model(name='mask_rcnn_r50_1x_coco')
+else:
+    model_dir = args.model_dir
+
+model_file = os.path.join(model_dir, "model.pdmodel")
+params_file = os.path.join(model_dir, "model.pdiparams")
+config_file = os.path.join(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)
+if args.image is None:
+    image = fd.utils.get_detection_test_image()
+else:
+    image = args.image
+im = cv2.imread(image)
 result = model.predict(im.copy())
 print(result)
 

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

@@ -9,10 +9,10 @@ def parse_arguments():
     parser = argparse.ArgumentParser()
     parser.add_argument(
         "--model_dir",
-        required=True,
+        default=None,
         help="Path of PaddleDetection model directory")
     parser.add_argument(
-        "--image", required=True, help="Path of test image file.")
+        "--image", default=None, help="Path of test image file.")
     parser.add_argument(
         "--device",
         type=str,
@@ -39,17 +39,26 @@ def build_option(args):
 
 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")
+if args.model_dir is None:
+    model_dir = fd.download_model(name='picodet_l_320_coco_lcnet')
+else:
+    model_dir = args.model_dir
+
+model_file = os.path.join(model_dir, "model.pdmodel")
+params_file = os.path.join(model_dir, "model.pdiparams")
+config_file = os.path.join(model_dir, "infer_cfg.yml")
 
 # 配置runtime，加载模型
 runtime_option = build_option(args)
 model = fd.vision.detection.PicoDet(
     model_file, params_file, config_file, runtime_option=runtime_option)
 
 # 预测图片检测结果
-im = cv2.imread(args.image)
+if args.image is None:
+    image = fd.utils.get_detection_test_image()
+else:
+    image = args.image
+im = cv2.imread(image)
 result = model.predict(im.copy())
 print(result)
 

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

@@ -9,10 +9,10 @@ def parse_arguments():
     parser = argparse.ArgumentParser()
     parser.add_argument(
         "--model_dir",
-        required=True,
+        default=None,
         help="Path of PaddleDetection model directory")
     parser.add_argument(
-        "--image", required=True, help="Path of test image file.")
+        "--image", default=None, help="Path of test image file.")
     parser.add_argument(
         "--device",
         type=str,
@@ -41,17 +41,26 @@ def build_option(args):
 
 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")
+if args.model_dir is None:
+    model_dir = fd.download_model(name='ppyolo_r50vd_dcn_1x_coco')
+else:
+    model_dir = args.model_dir
+
+model_file = os.path.join(model_dir, "model.pdmodel")
+params_file = os.path.join(model_dir, "model.pdiparams")
+config_file = os.path.join(model_dir, "infer_cfg.yml")
 
 # 配置runtime，加载模型
 runtime_option = build_option(args)
 model = fd.vision.detection.PPYOLO(
     model_file, params_file, config_file, runtime_option=runtime_option)
 
 # 预测图片检测结果
-im = cv2.imread(args.image)
+if args.image is None:
+    image = fd.utils.get_detection_test_image()
+else:
+    image = args.image
+im = cv2.imread(image)
 result = model.predict(im.copy())
 print(result)
 

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

@@ -2,7 +2,6 @@
 import os
 
 import fastdeploy as fd
-import fastdeploy.utils
 
 
 def parse_arguments():

examples/vision/detection/paddledetection/python/infer_yolov3.py

@@ -9,10 +9,10 @@ def parse_arguments():
     parser = argparse.ArgumentParser()
     parser.add_argument(
         "--model_dir",
-        required=True,
+        default=None,
         help="Path of PaddleDetection model directory")
     parser.add_argument(
-        "--image", required=True, help="Path of test image file.")
+        "--image", default=None, help="Path of test image file.")
     parser.add_argument(
         "--device",
         type=str,
@@ -39,17 +39,26 @@ def build_option(args):
 
 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")
+if args.model_dir is None:
+    model_dir = fd.download_model(name='yolov3_darknet53_270e_coco')
+else:
+    model_dir = args.model_dir
+
+model_file = os.path.join(model_dir, "model.pdmodel")
+params_file = os.path.join(model_dir, "model.pdiparams")
+config_file = os.path.join(model_dir, "infer_cfg.yml")
 
 # 配置runtime，加载模型
 runtime_option = build_option(args)
 model = fd.vision.detection.YOLOv3(
     model_file, params_file, config_file, runtime_option=runtime_option)
 
 # 预测图片检测结果
-im = cv2.imread(args.image)
+if args.image is None:
+    image = fd.utils.get_detection_test_image()
+else:
+    image = args.image
+im = cv2.imread(image)
 result = model.predict(im.copy())
 print(result)
 

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

@@ -9,10 +9,10 @@ def parse_arguments():
     parser = argparse.ArgumentParser()
     parser.add_argument(
         "--model_dir",
-        required=True,
+        default=None,
         help="Path of PaddleDetection model directory")
     parser.add_argument(
-        "--image", required=True, help="Path of test image file.")
+        "--image", default=None, help="Path of test image file.")
     parser.add_argument(
         "--device",
         type=str,
@@ -39,17 +39,26 @@ def build_option(args):
 
 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")
+if args.model_dir is None:
+    model_dir = fd.download_model(name='yolox_s_300e_coco')
+else:
+    model_dir = args.model_dir
+
+model_file = os.path.join(model_dir, "model.pdmodel")
+params_file = os.path.join(model_dir, "model.pdiparams")
+config_file = os.path.join(model_dir, "infer_cfg.yml")
 
 # 配置runtime，加载模型
 runtime_option = build_option(args)
 model = fd.vision.detection.PaddleYOLOX(
     model_file, params_file, config_file, runtime_option=runtime_option)
 
 # 预测图片检测结果
-im = cv2.imread(args.image)
+if args.image is None:
+    image = fd.utils.get_detection_test_image()
+else:
+    image = args.image
+im = cv2.imread(image)
 result = model.predict(im.copy())
 print(result)
 

examples/vision/detection/scaledyolov4/python/infer.py

@@ -7,9 +7,9 @@ def parse_arguments():
     import ast
     parser = argparse.ArgumentParser()
     parser.add_argument(
-        "--model", required=True, help="Path of scaledyolov4 onnx model.")
+        "--model", default=None, help="Path of scaledyolov4 onnx model.")
     parser.add_argument(
-        "--image", required=True, help="Path of test image file.")
+        "--image", default=None, help="Path of test image file.")
     parser.add_argument(
         "--device",
         type=str,
@@ -37,13 +37,21 @@ def build_option(args):
 
 args = parse_arguments()
 
+if args.model is None:
+    model = fd.download_model(name='ScaledYOLOv4-P5')
+else:
+    model = args.model
+
 # 配置runtime，加载模型
 runtime_option = build_option(args)
-model = fd.vision.detection.ScaledYOLOv4(
-    args.model, runtime_option=runtime_option)
+model = fd.vision.detection.ScaledYOLOv4(model, runtime_option=runtime_option)
 
 # 预测图片检测结果
-im = cv2.imread(args.image)
+if args.image is None:
+    image = fd.utils.get_detection_test_image()
+else:
+    image = args.image
+im = cv2.imread(image)
 result = model.predict(im.copy())
 print(result)
 

examples/vision/detection/yolor/python/infer.py

@@ -1,7 +1,6 @@
 import cv2
 
 import fastdeploy as fd
-import fastdeploy.utils
 
 
 def parse_arguments():

examples/vision/detection/yolov5/python/infer.py

@@ -7,9 +7,9 @@ def parse_arguments():
     import ast
     parser = argparse.ArgumentParser()
     parser.add_argument(
-        "--model", required=True, help="Path of yolov5 onnx model.")
+        "--model", default=None, help="Path of yolov5 onnx model.")
     parser.add_argument(
-        "--image", required=True, help="Path of test image file.")
+        "--image", default=None, help="Path of test image file.")
     parser.add_argument(
         "--device",
         type=str,
@@ -37,12 +37,21 @@ def build_option(args):
 
 args = parse_arguments()
 
+if args.model is None:
+    model = fd.download_model(name='YOLOv5s')
+else:
+    model = args.model
+
 # 配置runtime，加载模型
 runtime_option = build_option(args)
-model = fd.vision.detection.YOLOv5(args.model, runtime_option=runtime_option)
+model = fd.vision.detection.YOLOv5(model, runtime_option=runtime_option)
 
 # 预测图片检测结果
-im = cv2.imread(args.image)
+if args.image is None:
+    image = fd.utils.get_detection_test_image()
+else:
+    image = args.image
+im = cv2.imread(image)
 result = model.predict(im.copy())
 print(result)