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Explorer Cleanup (#7364)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Muhammad Rizwan Munawar <chr043416@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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Glenn Jocher 2024-01-07 01:31:41 +01:00 • committed by GitHub
parent aca8eb1fd4
commit ed73c0fedc
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15 changed files with 585 additions and 63 deletions
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18
docs/en/guides/instance-segmentation-and-tracking.md
View file

@ -91,16 +91,18 @@ There are two types of instance segmentation tracking available in the Ultralyti
print("Video frame is empty or video processing has been successfully completed.")
break
results = model.track(im0, persist=True)
masks = results[0].masks.xy
track_ids = results[0].boxes.id.int().cpu().tolist()
annotator = Annotator(im0, line_width=2)
for mask, track_id in zip(masks, track_ids):
annotator.seg_bbox(mask=mask,
mask_color=colors(track_id, True),
track_label=str(track_id))
results = model.track(im0, persist=True)
if results[0].boxes.id is not None:
masks = results[0].masks.xy
track_ids = results[0].boxes.id.int().cpu().tolist()
for mask, track_id in zip(masks, track_ids):
annotator.seg_bbox(mask=mask,
mask_color=colors(track_id, True),
track_label=str(track_id))
out.write(im0)
cv2.imshow("instance-segmentation-object-tracking", im0)

16
docs/en/guides/vision-eye.md
View file

@ -81,15 +81,17 @@ keywords: Ultralytics, YOLOv8, Object Detection, Object Tracking, IDetection, Vi
print("Video frame is empty or video processing has been successfully completed.")
break
results = model.track(im0, persist=True)
boxes = results[0].boxes.xyxy.cpu()
track_ids = results[0].boxes.id.int().cpu().tolist()
annotator = Annotator(im0, line_width=2)
for box, track_id in zip(boxes, track_ids):
annotator.box_label(box, label=str(track_id), color=colors(int(track_id)))
annotator.visioneye(box, center_point)
results = model.track(im0, persist=True)
boxes = results[0].boxes.xyxy.cpu()
if results[0].boxes.id is not None:
track_ids = results[0].boxes.id.int().cpu().tolist()
for box, track_id in zip(boxes, track_ids):
annotator.box_label(box, label=str(track_id), color=colors(int(track_id)))
annotator.visioneye(box, center_point)
out.write(im0)
cv2.imshow("visioneye-pinpoint", im0)