indexes = cv2.dnn.NMSBoxes(boxes, confidences, 0.5, 0.4)
video = cv2.VideoCapture('random_anna.mp4')
height, width, channels = frame.shape
font = cv2.FONT_HERSHEY_SIMPLEX colors = np.random.uniform(0, 255, size=(len(classes), 3)) for i in range(len(boxes)): if i in indexes: x, y, w, h = boxes[i] label = str(classes[class_ids[i]]) confidence = str(round(confidences[i], 2)) color = colors[i] cv2.rectangle(frame, (x, y), (x + w, y + h), color, 2) cv2.putText(frame, label + " " + confidence, (x, y + 20), font, 2, color, 2)
# Load YOLO net = cv2.dnn.readNet("yolov3.weights", "yolov3.cfg") classes = [] with open("coco.names", "r") as f: classes = [line.strip() for line in f.readlines()] random_anna.mp4
while video.isOpened(): ret, frame = video.read() if not ret: break
import cv2
cv2.imshow("Image", frame) if cv2.waitKey(1) & 0xFF == ord('q'): break