diff --git a/main.py b/main.py
index d86eff7..a74422e 100644
--- a/main.py
+++ b/main.py
@@ -1,54 +1,57 @@
+from picamera2 import Picamera2
 import cv2
-import requests
+import numpy as np
 import time
 
-# Set up camera
-cap = cv2.VideoCapture(0)
+# Initialize the camera
+picam2 = Picamera2()
+picam2.configure(picam2.create_preview_configuration(main={"format": "XRGB8888", "size": (640, 480)}))
+picam2.start()
 
-# Initialize variables for motion detection
-ret, frame1 = cap.read()
-ret, frame2 = cap.read()
+time.sleep(2)  # Give the camera some time to initialize
 
-# URL for ntfy.sh
-ntfy_url = "ntfy.sh/K3R3wHq4w9mwcwNd"
+# Read the initial frames
+frame1 = picam2.capture_array()
+frame2 = picam2.capture_array()
 
-def send_notification():
-    payload = {
-        'title': 'Motion Detected',
-        'message': 'Motion detected by Raspberry Pi camera!',
-        'priority': 'high'
-    }
-    try:
-        response = requests.post(ntfy_url, json=payload)
-        if response.status_code == 200:
-            print("Notification sent successfully.")
-        else:
-            print("Failed to send notification.")
-    except Exception as e:
-        print(f"An error occurred: {e}")
-
-while cap.isOpened():
-    # Compute difference between two frames
+while True:
+    # Calculate the absolute difference between the two frames
     diff = cv2.absdiff(frame1, frame2)
+    
+    # Convert the difference to grayscale
     gray = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY)
+
+    # Apply a Gaussian blur to the grayscale image
     blur = cv2.GaussianBlur(gray, (5, 5), 0)
+
+    # Threshold the blurred image to highlight the motion
     _, thresh = cv2.threshold(blur, 20, 255, cv2.THRESH_BINARY)
+
+    # Dilate the thresholded image to fill in holes
     dilated = cv2.dilate(thresh, None, iterations=3)
+
+    # Find contours (motion areas) in the dilated image
     contours, _ = cv2.findContours(dilated, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
 
+    # Draw bounding boxes around the contours
     for contour in contours:
-        if cv2.contourArea(contour) < 5000:
+        if cv2.contourArea(contour) < 500:
             continue
-        send_notification()
-        time.sleep(10)  # Wait for 10 seconds before sending another notification
+        x, y, w, h = cv2.boundingRect(contour)
+        cv2.rectangle(frame1, (x, y), (x + w, y + h), (0, 255, 0), 2)
 
+    # Display the result
+    cv2.imshow("Motion Detection", frame1)
+
+    # Update frames: frame1 becomes frame2, and a new frame is read as frame2
     frame1 = frame2
-    ret, frame2 = cap.read()
+    frame2 = picam2.capture_array()
 
     # Press 'q' to exit the loop
     if cv2.waitKey(10) & 0xFF == ord('q'):
         break
 
-cap.release()
+# Release resources and close all OpenCV windows
+picam2.stop()
 cv2.destroyAllWindows()