deep_learning/ultralytics
1
0
Fork 0
mirror of https://github.com/ultralytics/ultralytics.git synced 2025-09-15 15:48:41 +08:00
Code Issues Actions 2 Packages Projects Releases Wiki Activity

Update object tracking examples in docs (#19861)

Browse Source 
Co-authored-by: Muhammad Rizwan Munawar <muhammadrizwanmunawar123@gmail.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
This commit is contained in:
Ankan Ghosh 2025-03-29 00:53:58 +05:30 committed by GitHub
parent 3deb509b8b
commit 63b4f8844c
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
2 changed files with 25 additions and 21 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

33
docs/en/modes/track.md
View File

@ -231,29 +231,30 @@ In the following example, we demonstrate how to utilize YOLO11's tracking capabi
if success:
# Run YOLO11 tracking on the frame, persisting tracks between frames
results = model.track(frame, persist=True)
result = model.track(frame, persist=True)[0]
# Get the boxes and track IDs
boxes = results[0].boxes.xywh.cpu()
track_ids = results[0].boxes.id.int().cpu().tolist()
if result.boxes and result.boxes.id is not None:
boxes = result.boxes.xywh.cpu()
track_ids = result.boxes.id.int().cpu().tolist()
# Visualize the results on the frame
annotated_frame = results[0].plot()
# Visualize the result on the frame
frame = result.plot()
# Plot the tracks
for box, track_id in zip(boxes, track_ids):
x, y, w, h = box
track = track_history[track_id]
track.append((float(x), float(y))) # x, y center point
if len(track) > 30: # retain 30 tracks for 30 frames
track.pop(0)
# Plot the tracks
for box, track_id in zip(boxes, track_ids):
x, y, w, h = box
track = track_history[track_id]
track.append((float(x), float(y))) # x, y center point
if len(track) > 30: # retain 30 tracks for 30 frames
track.pop(0)
# Draw the tracking lines
points = np.hstack(track).astype(np.int32).reshape((-1, 1, 2))
cv2.polylines(annotated_frame, [points], isClosed=False, color=(230, 230, 230), thickness=10)
# Draw the tracking lines
points = np.hstack(track).astype(np.int32).reshape((-1, 1, 2))
cv2.polylines(frame, [points], isClosed=False, color=(230, 230, 230), thickness=10)
# Display the annotated frame
cv2.imshow("YOLO11 Tracking", annotated_frame)
cv2.imshow("YOLO11 Tracking", frame)
# Break the loop if 'q' is pressed
if cv2.waitKey(1) & 0xFF == ord("q"):

13
ultralytics/trackers/README.md
View File

@ -191,14 +191,17 @@ while cap.isOpened():
if success:
# Run YOLO11 tracking on the frame, persisting tracks between frames
results = model.track(frame, persist=True)
result = model.track(frame, persist=True)[0]
# Get the boxes and track IDs
boxes = results[0].boxes.xywh.cpu()
track_ids = results[0].boxes.id.int().cpu().tolist()
if result.boxes and result.boxes.id is not None:
boxes = result.boxes.xywh.cpu()
track_ids = result.boxes.id.int().cpu().tolist()
else:
pass
# Visualize the results on the frame
annotated_frame = results[0].plot()
# Visualize the result on the frame
annotated_frame = result.plot()
# Plot the tracks
for box, track_id in zip(boxes, track_ids):