TensorRT detect.py inference fix (#9581)

* Update

* Update ci-testing.yml

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Update ci-testing.yml

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Segment fix

* Segment fix

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

segment/predict.py

@@ -100,14 +100,15 @@ def run(
     imgsz = check_img_size(imgsz, s=stride)  # check image size
 
     # Dataloader
+    bs = 1  # batch_size
     if webcam:
         view_img = check_imshow()
         dataset = LoadStreams(source, img_size=imgsz, stride=stride, auto=pt, vid_stride=vid_stride)
+        bs = len(dataset)
     elif screenshot:
         dataset = LoadScreenshots(source, img_size=imgsz, stride=stride, auto=pt)
     else:
         dataset = LoadImages(source, img_size=imgsz, stride=stride, auto=pt, vid_stride=vid_stride)
-    bs = len(dataset)  # batch_size
     vid_path, vid_writer = [None] * bs, [None] * bs
 
     # Run inference
@@ -179,7 +180,7 @@ def run(
                         c = int(cls)  # integer class
                         label = None if hide_labels else (names[c] if hide_conf else f'{names[c]} {conf:.2f}')
                         annotator.box_label(xyxy, label, color=colors(c, True))
-                        annotator.draw.polygon(segments[j], outline=colors(c, True), width=3)
+                        # annotator.draw.polygon(segments[j], outline=colors(c, True), width=3)
                     if save_crop:
                         save_one_box(xyxy, imc, file=save_dir / 'crops' / names[c] / f'{p.stem}.jpg', BGR=True)