RZHD

import cv2

# Load pre-trained model for detecting people
person_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_fullbody.xml')

# Load pre-trained model for detecting phones
phone_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_mobilephone.xml')

# Variables for tracking phone usage time
phone_in_use = False
phone_use_start = 0
phone_use_end = 0

# Video capturing object
cap = cv2.VideoCapture('path_to_video_file.mp4')

while True:
    # Read each frame from the video
    ret, frame = cap.read()
    
    if ret:
        # Convert frame to grayscale
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        
        # Detect people in the frame
        people = person_cascade.detectMultiScale(gray, 1.1, 4)
        
        # Iterate over each detected person's bounding box
        for (x, y, w, h) in people:
            # Draw bounding box around the person
            cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
            
            # Get ROI (Region of Interest) for phone detection within person's bounding box
            roi_gray = gray[y:y+h, x:x+w]
            
            # Detect phones within ROI
            phones = phone_cascade.detectMultiScale(roi_gray)
            
            # Check if any phones are detected within person's bounding box
            if len(phones) > 0:
                # Phone is in use
                if not phone_in_use:
                    # Start tracking phone usage time
                    phone_use_start = cv2.getTickCount()
                    phone_in_use = True
            else:
                # Phone usage ended
                if phone_in_use:
                    # Calculate phone usage time in seconds
                    phone_use_end = cv2.getTickCount()
                    phone_usage_time = (phone_use_end - phone_use_start) / cv2.getTickFrequency()
                    
                    # Check if phone usage time is greater than or equal to 3 seconds
                    if phone_usage_time >= 3:
                        # Person was using the phone for more than 3 seconds
                        print("Phone usage detected for {:.2f} seconds".format(phone_usage_time))
                
                    phone_in_use = False
        
        # Display the resulting frame
        cv2.imshow('Video', frame)
        
        # Exit if 'q' is pressed
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
    else:
        break

# Release the capture and close windows
cap.release()
cv2.destroyAllWindows()