snipplets.dev/projects/CV/Stream/__main__.py

import cv2
from ultralytics import YOLO

# https://docs.ultralytics.com/modes/predict/#streaming-source-for-loop

# Load the YOLOv8 model
model = YOLO('yolov8m.pt')

# Open the video file
video_path = 'run.mp4'
cap = cv2.VideoCapture(video_path)

fps = 0
prev_frame_time = 0
new_frame_time = 0

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

    # Set current frame time
    new_frame_time = time.time()

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

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

        # Calculate FPS
        fps = int(1 / (new_frame_time - prev_frame_time))
        prev_frame_time = new_frame_time

        # 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

    print(fps)

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