Update app.py

app.py

@@ -6,119 +6,120 @@ import tempfile
 import mediapipe as mp
 import os
 from PIL import Image
-from io import BytesIO
 
 # === CONFIGURATION ===
 API_KEY = "AIzaSyDojJrpauA0XZtCCDUuo9xeQHZQamYKsC4"
 CCTVFEED_IDS = ['1KJRkSf2SKEZ1mXS9_si65IwMBtjs6p4n']
 REG_FOLDER_ID = '1qkcR7nQTEtiMH9OFUv2bGxVn08E3dKjF'
-INTRUDER_FOLDER_ID = '1PPAUWU-wMx7fek73p-hqPqYQypYtG8Ob'
+INTRUDER_UPLOAD_URL = "https://upload.gdrive.com/your-anon-endpoint-if-any"  # You can change this if needed
 
 # === SETUP ===
 mp_face_detection = mp.solutions.face_detection
 mp_drawing = mp.solutions.drawing_utils
 face_detector = mp_face_detection.FaceDetection(model_selection=0, min_detection_confidence=0.5)
 
-# === FUNCTIONS ===
-def list_drive_files(folder_id):
-    url = f"https://www.googleapis.com/drive/v3/files?q='{folder_id}'+in+parents&key={API_KEY}&fields=files(id,name,mimeType)"
-    response = requests.get(url)
-    return response.json().get("files", [])
+# === UTILS ===
+def get_drive_file_links(folder_id, mime_types):
+    api_url = f"https://www.googleapis.com/drive/v3/files?q='{folder_id}'+in+parents&key={API_KEY}&fields=files(id,name,mimeType)"
+    response = requests.get(api_url)
+    files = response.json().get("files", [])
+    return [(f['name'], f['id']) for f in files if f['mimeType'] in mime_types]
 
-def stream_drive_file(file_id, suffix):
+def download_file(file_id, suffix):
     url = f"https://drive.google.com/uc?id={file_id}&export=download"
     response = requests.get(url, stream=True)
     temp = tempfile.NamedTemporaryFile(delete=False, suffix=suffix)
-    for chunk in response.iter_content(1024 * 1024):
+    for chunk in response.iter_content(chunk_size=1024 * 1024):
         temp.write(chunk)
     temp.close()
     return temp.name
 
+def extract_faces_from_image(img_path):
+    img = cv2.imread(img_path)
+    rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    results = face_detector.process(rgb)
+    faces = []
+    if results.detections:
+        for det in results.detections:
+            bbox = det.location_data.relative_bounding_box
+            h, w, _ = rgb.shape
+            x, y, bw, bh = int(bbox.xmin * w), int(bbox.ymin * h), int(bbox.width * w), int(bbox.height * h)
+            face_crop = rgb[y:y+bh, x:x+bw]
+            if face_crop.size > 0:
+                face_resized = cv2.resize(face_crop, (100, 100))
+                faces.append(face_resized)
+    return faces
+
 def mse(img1, img2):
     if img1.shape != img2.shape:
         return np.inf
-    return np.mean((img1 - img2) ** 2)
-
-def load_registered_faces():
-    reg_faces = []
-    files = list_drive_files(REG_FOLDER_ID)
-    for f in files:
-        if "image" in f['mimeType']:
-            path = stream_drive_file(f['id'], ".jpg")
-            img = cv2.imread(path, cv2.IMREAD_GRAYSCALE)
-            img = cv2.resize(img, (100, 100))
-            reg_faces.append(img)
-            os.remove(path)
-    return reg_faces
+    return np.mean((img1.astype("float") - img2.astype("float")) ** 2)
 
-def upload_intruder_image(img_np, intruder_name="intruder_face.jpg"):
-    # Convert image to JPEG in memory
-    img = Image.fromarray(cv2.cvtColor(img_np, cv2.COLOR_BGR2RGB))
-    buffer = BytesIO()
-    img.save(buffer, format="JPEG")
-    buffer.seek(0)
-    
-    # Upload to intruder folder using resumable upload
-    upload_url = f"https://www.googleapis.com/upload/drive/v3/files?uploadType=multipart&key={API_KEY}"
-    metadata = {
-        "name": intruder_name,
-        "parents": [INTRUDER_FOLDER_ID]
-    }
-    files = {
-        "metadata": ("metadata.json", BytesIO(str.encode(str(metadata).replace("'", '"'))), "application/json"),
-        "file": ("image.jpg", buffer, "image/jpeg")
-    }
-    response = requests.post(upload_url, files=files)
-    return response.ok
+def is_intruder(face_img, known_faces, threshold=5000):
+    face_gray = cv2.cvtColor(face_img, cv2.COLOR_RGB2GRAY)
+    face_gray = cv2.resize(face_gray, (100, 100))
+    return all(mse(face_gray, known) > threshold for known in known_faces)
 
-def detect_faces_from_video(video_path, reg_faces):
-    cap = cv2.VideoCapture(video_path)
-    detected, intruders, sidebar_faces = 0, 0, []
-
-    while cap.isOpened():
-        ret, frame = cap.read()
-        if not ret:
-            break
-        rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
-        results = face_detector.process(rgb)
-        if results.detections:
-            for det in results.detections:
-                bbox = det.location_data.relative_bounding_box
-                h, w, _ = frame.shape
-                x, y, bw, bh = int(bbox.xmin * w), int(bbox.ymin * h), int(bbox.width * w), int(bbox.height * h)
-                face = frame[y:y+bh, x:x+bw]
-                if face.size == 0:
-                    continue
-                face_gray = cv2.cvtColor(cv2.resize(face, (100, 100)), cv2.COLOR_BGR2GRAY)
-                sidebar_faces.append(face)
-                is_known = any(mse(face_gray, kf) < 2000 for kf in reg_faces)
-                if not is_known:
-                    upload_intruder_image(face, f"intruder_{intruders}.jpg")
-                    intruders += 1
-                    detected += 1
-    cap.release()
-    return detected, sidebar_faces
+def upload_intruder(img_array, name):
+    temp_img = tempfile.NamedTemporaryFile(delete=False, suffix=".jpg")
+    Image.fromarray(cv2.cvtColor(img_array, cv2.COLOR_RGB2BGR)).save(temp_img.name)
+    # Simulate upload – requires actual implementation if you want to use Google Forms or Apps Script
+    st.warning(f"Upload placeholder: {temp_img.name}")
+    return temp_img.name
 
-# === STREAMLIT UI ===
-st.set_page_config(layout="wide")
+# === APP UI ===
 st.title("🔐 Intruder Detection from CCTV Feed")
-st.write("Streams public videos from Google Drive, compares detected faces with registered images, and uploads unknown faces to the intruder folder.")
+st.write("Streaming videos from Google Drive, detecting faces using MediaPipe and flagging unknown individuals.")
 
-reg_faces = load_registered_faces()
-st.sidebar.markdown("### Faces Detected")
+sidebar_faces = []
 
-with st.spinner("Processing CCTV feed..."):
-    total_intruders = 0
+with st.spinner("Loading registered faces..."):
+    known_faces = []
+    for fname, fid in get_drive_file_links(REG_FOLDER_ID, ["image/jpeg", "image/png"]):
+        img_path = download_file(fid, ".jpg")
+        faces = extract_faces_from_image(img_path)
+        for face in faces:
+            gray = cv2.cvtColor(face, cv2.COLOR_RGB2GRAY)
+            known_faces.append(cv2.resize(gray, (100, 100)))
+        os.remove(img_path)
+    st.success(f"Loaded {len(known_faces)} registered faces.")
+
+with st.spinner("Processing CCTV videos..."):
+    intruder_count = 0
     for folder_id in CCTVFEED_IDS:
-        files = list_drive_files(folder_id)
-        for f in files:
-            if f['mimeType'].startswith('video/'):
-                st.subheader(f"🎥 {f['name']}")
-                path = stream_drive_file(f['id'], ".mp4")
-                intruders, detected_faces = detect_faces_from_video(path, reg_faces)
-                total_intruders += intruders
-                for face in detected_faces:
-                    st.sidebar.image(face, width=100)
-                os.remove(path)
+        video_files = get_drive_file_links(folder_id, ["video/mp4", "video/x-msvideo", "video/avi"])
+        for vname, vid in video_files:
+            st.subheader(f"🎥 {vname}")
+            video_path = download_file(vid, ".mp4")
+            cap = cv2.VideoCapture(video_path)
+            frame_id = 0
+            while cap.isOpened():
+                ret, frame = cap.read()
+                if not ret:
+                    break
+                frame_id += 1
+                if frame_id % 30 != 0:
+                    continue
+                rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+                results = face_detector.process(rgb)
+                if results.detections:
+                    for det in results.detections:
+                        bbox = det.location_data.relative_bounding_box
+                        h, w, _ = rgb.shape
+                        x, y, bw, bh = int(bbox.xmin * w), int(bbox.ymin * h), int(bbox.width * w), int(bbox.height * h)
+                        face_crop = rgb[y:y+bh, x:x+bw]
+                        if face_crop.size == 0:
+                            continue
+                        if is_intruder(face_crop, known_faces):
+                            sidebar_faces.append(face_crop)
+                            intruder_count += 1
+                            upload_intruder(face_crop, f"intruder_{intruder_count}.jpg")
+            cap.release()
+            os.remove(video_path)
+
+    st.success(f"🎯 Intruders detected: {intruder_count}")
 
-st.success(f"✅ Intruders found and uploaded: {total_intruders}")
+# === SIDEBAR ===
+st.sidebar.title("📸 Faces Detected as Intruders")
+for idx, face in enumerate(sidebar_faces):
+    st.sidebar.image(face, caption=f"Intruder #{idx + 1}", width=100)