import cv2
from ultralytics import YOLO

# Load the YOLOv8 model
# model = YOLO("../runs/detect/train3/weights/best.pt")  # zhou
# model = YOLO("../runs/detect/train4/weights/best.pt")  # 1000 img, mine
# model = YOLO("../runs/detect/train2/weights/best.pt")  # 1000 img, based on 3000 img
model = YOLO("../../../project/runs/detect/train3/weights/best.pt")  # 3000 img, mine


# Open the video file
video_path = "./video/demo_video_no_detection.mp4"
cap = cv2.VideoCapture(video_path)

# Loop through the video frames
while cap.isOpened():
    # Read a frame from the video
    success, frame = cap.read()

    if success:
        # Run YOLOv8 inference on the frame
        results = model(frame)

        # Visualize the results on the frame
        annotated_frame = results[0].plot()

        # Display the annotated frame
        cv2.imshow("YOLOv8 Inference", annotated_frame)

        # Break the loop if 'q' is pressed
        if cv2.waitKey(1) & 0xFF == ord("q"):
            break
    else:
        # Break the loop if the end of the video is reached
        break

# Release the video capture object and close the display window
cap.release()
cv2.destroyAllWindows()