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Display object tracking IDs and labels on video frames if object tracking is enabled #30

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Jun 24, 2025
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Display object tracking IDs and labels on video frames if object tracking is enabled #30

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19 changes: 19 additions & 0 deletions examples/image/classify-video.py
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Original file line number Diff line number Diff line change
Expand Up @@ -92,6 +92,25 @@ def getFrame(sec):
print('\t%s (%.2f): x=%d y=%d w=%d h=%d' % (bb['label'], bb['value'], bb['x'], bb['y'], bb['width'], bb['height']))
img = cv2.rectangle(cropped, (bb['x'], bb['y']), (bb['x'] + bb['width'], bb['y'] + bb['height']), (255, 0, 0), 1)

# Object tracking output
if "object_tracking" in res["result"].keys():
print('Found %d tracked objects' % (len(res["result"]["object_tracking"])))
for obj in res["result"]["object_tracking"]:
print('\tID=%s, label=%s, value=%.2f, x=%d, y=%d, w=%d, h=%d' % (
obj['object_id'], obj['label'], obj['value'], obj['x'], obj['y'], obj['width'], obj['height']))
# Draw bounding box
x = obj['x']
y = obj['y']
w = obj['width']
h = obj['height']
img = cv2.rectangle(cropped, (x, y), (x + w, y + h), (0, 255, 0), 2)
# Draw label and ID
label_id_text = f"ID={obj['object_id']}, {obj['label']}"
text_x = x
text_y = y - 10 if y - 10 > 10 else y + 20
img = cv2.putText(img, label_id_text, (text_x, text_y),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)

if "visual_anomaly_grid" in res["result"].keys():
print('Found %d visual anomalies (%d ms.)' % (len(res["result"]["visual_anomaly_grid"]), res['timing']['dsp'] +
res['timing']['classification'] +
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