Some Stuff

diffrence.py

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+import cv2
+import numpy as np
+
+def process_video(video_path, scale_factor=0.5, min_area=500):
+    """
+    Process video for motion detection.
+    
+    Args:
+        video_path: Path to input video
+        output_path: Path to save processed video
+        scale_factor: Factor to downscale the frames
+        min_area: Minimum contour area to be considered as motion
+    """
+    # Open video
+    cap = cv2.VideoCapture(video_path)
+    if not cap.isOpened():
+        raise ValueError("Error opening video file")
+    
+    # Get video properties
+    frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+    frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+    fps = int(cap.get(cv2.CAP_PROP_FPS))
+    
+    # Create video writer
+    # fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+    # out = cv2.VideoWriter(output_path, fourcc, fps, (frame_width, frame_height))
+    
+    # Read first frame
+    ret, prev_frame = cap.read()
+    if not ret:
+        raise ValueError("Error reading first frame")
+    
+    # Process first frame
+    prev_gray = cv2.cvtColor(prev_frame, cv2.COLOR_BGR2GRAY)
+    prev_small = cv2.resize(prev_gray, None, fx=scale_factor, fy=scale_factor)
+    
+    while True:
+        # Read current frame
+        ret, curr_frame = cap.read()
+        if not ret:
+            break
+            
+        # Convert to grayscale
+        curr_gray = cv2.cvtColor(curr_frame, cv2.COLOR_BGR2GRAY)
+        
+        # Downscale
+        curr_small = cv2.resize(curr_gray, None, fx=scale_factor, fy=scale_factor)
+        
+        # Calculate absolute difference
+        frame_diff = cv2.absdiff(curr_small, prev_small)
+        
+        # Apply threshold to difference
+        _, thresh = cv2.threshold(frame_diff, 50, 255, cv2.THRESH_BINARY)
+        
+        # Dilate to fill in holes
+        kernel = np.ones((3,3), np.uint8)
+        dilated = cv2.dilate(thresh, kernel, iterations=2)
+        
+        # Scale back up to original size
+        motion_mask = cv2.resize(dilated, (frame_width, frame_height))
+        
+        # Find contours
+        contours, _ = cv2.findContours(motion_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+        
+        # Draw motion areas on original frame
+        for contour in contours:
+            if cv2.contourArea(contour) > min_area:
+                x, y, w, h = cv2.boundingRect(contour)
+                cv2.rectangle(curr_frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
+        
+        # Write frame to output video
+        cv2.imshow("e",curr_frame)
+
+
+        # Exit if 'q' is pressed
+        if cv2.waitKey(30) & 0xFF == ord('q'):
+            break
+
+        # Update previous frame
+        prev_small = curr_small
+        
+    # Release resources
+    cap.release()
+    cv2.destroyAllWindows()
+
+def main():
+    # Example usage
+    input_video = 0
+    try:
+        process_video(input_video)
+        print("Motion detection completed successfully")
+    except Exception as e:
+        print(f"Error processing video: {str(e)}")
+
+if __name__ == "__main__":
+    main()