Hailo • Re: USB Compatibility

Code:

#!/usr/bin/env python3"""Example module for Hailo Detection using USB camera."""import argparseimport cv2from picamera2.devices import Hailoimport os# find USB cameracam1 = -1x = 0while cam1 == -1 and x < 42:    txt = "v4l2-ctl -d " + str(x) + " --list-ctrls > /run/shm/cam_ctrls.txt"    os.system(txt)    ctrls = []    with open("/run/shm/cam_ctrls.txt", "r") as file:        line = file.readline()        while line:            ctrls.append(line)            line = file.readline()    if 'User Controls\n' in ctrls and ('Camera Controls\n' in ctrls):        cam1 = x    else:        x +=1if cam1 == -1:    print(" No USB camera found !!")def extract_detections(hailo_output, w, h, class_names, threshold=0.5):    """Extract detections from the HailoRT-postprocess output."""    results = []    for class_id, detections in enumerate(hailo_output):        for detection in detections:            score = detection[4]            if score >= threshold:                y0, x0, y1, x1 = detection[:4]                bbox = (int(x0 * w), int(y0 * h), int(x1 * w), int(y1 * h))                results.append([class_names[class_id], bbox, score])    return resultsdef draw_objects(request):    current_detections = detections    if current_detections:        for class_name, bbox, score in current_detections:            x0, y0, x1, y1 = bbox            label = f"{class_name} %{int(score * 100)}"            cv2.rectangle(frame, (x0, y0), (x1, y1), (0, 255, 0, 0), 2)            cv2.putText(frame, label, (x0 + 5, y0 + 15),                        cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0, 0), 1, cv2.LINE_AA)if __name__ == "__main__":    # Parse command-line arguments.    parser = argparse.ArgumentParser(description="Detection Example")    parser.add_argument("-m", "--model", help="Path for the HEF model.",                        default="/usr/share/hailo-models/yolov8s_h8l.hef")    parser.add_argument("-l", "--labels", default="coco.txt",                        help="Path to a text file containing labels.")    parser.add_argument("-s", "--score_thresh", type=float, default=0.5,                        help="Score threshold, must be a float between 0 and 1.")    args = parser.parse_args()    # Get the Hailo model, the input size it wants, and the size of our preview stream.    with Hailo(args.model) as hailo:        model_h, model_w, _ = hailo.get_input_shape()        video_w, video_h = 640,640        # Load class names from the labels file        with open(args.labels, 'r', encoding="utf-8") as f:            class_names = f.read().splitlines()        # The list of detected objects to draw.        detections = None        # Configure and start CV2 Videocapture.        cap = cv2.VideoCapture(cam1)        if not cap.isOpened():            print("Cannot open camera")            exit()             # Process each low resolution camera frame.        while True:                # Capture frame-by-frame                ret, frame = cap.read()                frame = cv2.resize(frame, (model_h, model_w))                                # Run inference on the preprocessed frame                results = hailo.run(frame)                # Extract detections from the inference results                detections = extract_detections(results, video_w, video_h, class_names, args.score_thresh)                draw_objects(detections)                cv2.imshow('frame', frame)                if cv2.waitKey(1) == ord('q'):                    break