hailo-CLIP: how can I create a bounding box around detected objects?

General
1

I am running the hailo-CLIP examples. Now I would like to mark detected objects with a bounding box, in a similar way as it is done in the hailo-rpi5-examples.

In the file clip_application.py the bounding box coordinates appear to be determined for every detection:

    # Parse the detections
    for detection in detections:
        track = detection.get_objects_typed(hailo.HAILO_UNIQUE_ID)
        track_id = None
        label = None
        confidence = 0.0
        for track_id_obj in track:
            track_id = track_id_obj.get_id()
        if track_id is not None:
            string_to_print += f'Track ID: {track_id} '
        classifications = detection.get_objects_typed(hailo.HAILO_CLASSIFICATION)
        if len(classifications) > 0:
            string_to_print += ' CLIP Classifications:'
            for classification in classifications:
                label = classification.get_label()
                confidence = classification.get_confidence()
                string_to_print += f'Label: {label} Confidence: {confidence:.2f} '
            string_to_print += '\n'
        if isinstance(detection, hailo.HailoDetection):
            label = detection.get_label()
            **bbox = detection.get_bbox()**
            confidence = detection.get_confidence()
            string_to_print += f"Detection: {label} {confidence:.2f}\n"
    if string_to_print:
        print(string_to_print)
    return Gst.PadProbeReturn.OK

how can I now draw the box with the retrieved coordinates for bbox?
Thanks for your support!

2

Hey @schiwo1,

You can try something like this:

label = detection.get_label()
bbox = detection.get_bbox()
confidence = detection.get_confidence()
string_to_print += f"Detection: {label} {confidence:.2f}\n"

# Draw the bounding box on the frame
x_min, y_min, x_max, y_max = [int(v) for v in bbox]
color = (0, 255, 0)  # Green box
thickness = 2

cv2.rectangle(frame, (x_min, y_min), (x_max, y_max), color, thickness)
if label:
    cv2.putText(frame, f"{label} {confidence:.2f}", (x_min, y_min - 10),
                cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)

Haven’t tested this exact code, but the idea is there—should get you started!