code/detect_on_video_for_loop.py

import cv2
from ultralytics import YOLO
import re

# Load the YOLOv8 model
model = YOLO('runs/detect/train6/weights/best.pt')

# Open the video file
video_path = "your_path"
cap = cv2.VideoCapture(video_path)

# # Alternativly: use an rtsp-stream as input
# cap = cv2.VideoCapture("rtsp://user:password@ip_adress:8554/Streaming/Channels/101")

# # Alternativly: use your webcam as input
# cap = cv2.VideoCapture(0);

# 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)

        # Count the number of detections in the frame
        num_detections = len(results[0])

        # Print the number of detections in the frame
        print(f"Number of detections in frame: {num_detections}")
        
        # 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()