added main code.

main.py

@@ -0,0 +1,54 @@
+import cv2
+import requests
+import time
+
+# Set up camera
+cap = cv2.VideoCapture(0)
+
+# Initialize variables for motion detection
+ret, frame1 = cap.read()
+ret, frame2 = cap.read()
+
+# URL for ntfy.sh
+ntfy_url = "ntfy.sh/K3R3wHq4w9mwcwNd"
+
+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
+    diff = cv2.absdiff(frame1, frame2)
+    gray = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY)
+    blur = cv2.GaussianBlur(gray, (5, 5), 0)
+    _, thresh = cv2.threshold(blur, 20, 255, cv2.THRESH_BINARY)
+    dilated = cv2.dilate(thresh, None, iterations=3)
+    contours, _ = cv2.findContours(dilated, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+
+    for contour in contours:
+        if cv2.contourArea(contour) < 5000:
+            continue
+        send_notification()
+        time.sleep(10)  # Wait for 10 seconds before sending another notification
+
+    frame1 = frame2
+    ret, frame2 = cap.read()
+
+    # Press 'q' to exit the loop
+    if cv2.waitKey(10) & 0xFF == ord('q'):
+        break
+
+cap.release()
+cv2.destroyAllWindows()
+

motion_detection.py

@@ -0,0 +1,66 @@
+import cv2
+import numpy as np
+import os
+import time
+import requests
+
+# Function to send notification using notify.sh
+def send_notification():
+    url = "http://<YOUR_RASPBERRY_PI_IP>:<PORT>/notify"  # Replace with your Raspberry Pi's IP and port
+    payload = {
+        "title": "Motion Detected!",
+        "message": "Motion has been detected by the camera."
+    }
+    headers = {
+        "Authorization": "Bearer <YOUR_API_TOKEN>"  # Replace with your API token
+    }
+    
+    try:
+        response = requests.post(url, json=payload, headers=headers)
+        if response.status_code == 200:
+            print("Notification sent successfully!")
+        else:
+            print("Failed to send notification:", response.status_code, response.text)
+    except Exception as e:
+        print("Error sending notification:", e)
+
+# Initialize the camera
+cap = cv2.VideoCapture(0)
+
+# Read the first frame
+ret, frame1 = cap.read()
+ret, frame2 = cap.read()
+
+while True:
+    # Calculate the difference between the frames
+    diff = cv2.absdiff(frame1, frame2)
+    gray = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY)
+    blur = cv2.GaussianBlur(gray, (5, 5), 0)
+    _, thresh = cv2.threshold(blur, 20, 255, cv2.THRESH_BINARY)
+    dilated = cv2.dilate(thresh, None, iterations=3)
+
+    # Find contours
+    contours, _ = cv2.findContours(dilated, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+    # Check for motion
+    for contour in contours:
+        if cv2.contourArea(contour) < 500:  # Adjust the threshold as needed
+            continue
+        send_notification()
+        break  # Exit after sending notification
+
+    # Update frames
+    frame1 = frame2
+    ret, frame2 = cap.read()
+
+    # Display the video feed (optional)
+    cv2.imshow("Motion Detection", frame1)
+
+    # Break the loop on 'q' key press
+    if cv2.waitKey(1) == ord('q'):
+        break
+
+# Release the camera and close windows
+cap.release()
+cv2.destroyAllWindows()
+