#!/usr/bin/env python3

import sys
import cv2
import numpy as np

def detect_motion(image_path):
    # Read the input image
    frame = cv2.imread(image_path)
    if frame is None:
        print("Error: Could not read image file")
        sys.exit(1)

    # Convert to grayscale
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    
    # Apply Gaussian blur to reduce noise
    blur = cv2.GaussianBlur(gray, (21, 21), 0)
    
    # Threshold the image to detect significant changes
    _, thresh = cv2.threshold(blur, 20, 255, cv2.THRESH_BINARY)
    
    # Find contours in the thresholded image
    contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    
    # Filter contours based on area to remove noise
    min_area = 500
    motion_detected = False
    
    for contour in contours:
        if cv2.contourArea(contour) > min_area:
            motion_detected = True
            # Draw rectangle around motion area
            (x, y, w, h) = cv2.boundingRect(contour)
            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
    
    # Save the output image with motion detection boxes
    output_path = image_path.replace('.jpg', '_motion.jpg')
    cv2.imwrite(output_path, frame)
    
    # Return result
    if motion_detected:
        print("Motion detected!")
        print(f"Output saved to: {output_path}")
    else:
        print("No motion detected")

if __name__ == "__main__":
    if len(sys.argv) != 2:
        print("Usage: python motion_detection.py <image_path>")
        sys.exit(1)
    
    detect_motion(sys.argv[1])