40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
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import cv2
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from ultralytics import YOLO
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# Load the YOLOv8 model
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# model = YOLO("../runs/detect/train3/weights/best.pt") # zhou
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# model = YOLO("../runs/detect/train4/weights/best.pt") # 1000 img, mine
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# model = YOLO("../runs/detect/train2/weights/best.pt") # 1000 img, based on 3000 img
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model = YOLO("../../../project/runs/detect/train3/weights/best.pt") # 3000 img, mine
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# Open the video file
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video_path = "./video/demo_video_no_detection.mp4"
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cap = cv2.VideoCapture(video_path)
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# Loop through the video frames
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while cap.isOpened():
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# Read a frame from the video
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success, frame = cap.read()
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if success:
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# Run YOLOv8 inference on the frame
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results = model(frame)
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# Visualize the results on the frame
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annotated_frame = results[0].plot()
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# Display the annotated frame
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cv2.imshow("YOLOv8 Inference", annotated_frame)
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# Break the loop if 'q' is pressed
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if cv2.waitKey(1) & 0xFF == ord("q"):
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break
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else:
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# Break the loop if the end of the video is reached
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break
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# Release the video capture object and close the display window
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cap.release()
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cv2.destroyAllWindows()
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