Update app.py

app.py

@@ -5,134 +5,138 @@ import requests
 import tempfile
 import mediapipe as mp
 import os
-import pickle
+import hashlib
+import io
+from PIL import Image
 from googleapiclient.discovery import build
 from googleapiclient.http import MediaFileUpload
-from PIL import Image
+from google_auth_oauthlib.flow import InstalledAppFlow
+from google.auth.transport.requests import Request
+import pickle
 
 # === CONFIGURATION ===
 API_KEY = "AIzaSyDojJrpauA0XZtCCDUuo9xeQHZQamYKsC4"
 CCTVFEED_IDS = ['1KJRkSf2SKEZ1mXS9_si65IwMBtjs6p4n']
 REG_FOLDER_ID = '1qkcR7nQTEtiMH9OFUv2bGxVn08E3dKjF'
 INTRUDER_FOLDER_ID = '1PPAUWU-wMx7fek73p-hqPqYQypYtG8Ob'
+SCOPES = ['https://www.googleapis.com/auth/drive.file']
 
+# === 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)
 
-# === INTRUDER UPLOAD ===
-def get_drive_service():
-    try:
-        with open("token.pickle", "rb") as token:
+# === AUTH FOR UPLOAD ===
+def get_drive_service_from_token():
+    creds = None
+    if os.path.exists('token.pickle'):
+        with open('token.pickle', 'rb') as token:
             creds = pickle.load(token)
-        return build("drive", "v3", credentials=creds)
-    except Exception as e:
-        print(f"❌ Drive auth failed: {e}")
-        return None
-
-def upload_intruder_face(image_path):
-    service = get_drive_service()
-    if service is None:
-        print("🔒 Upload skipped (auth failed)")
-        return
-
-    metadata = {"name": os.path.basename(image_path), "parents": [INTRUDER_FOLDER_ID]}
-    media = MediaFileUpload(image_path, mimetype="image/jpeg")
-    try:
-        service.files().create(body=metadata, media_body=media, fields="id").execute()
-        print(f"✅ Uploaded to INTRUDER folder: {image_path}")
-    except Exception as e:
-        print(f"❌ Upload failed: {e}")
-
-# === HELPERS ===
-def get_drive_files(folder_id, allowed_mime):
-    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)
-    files = response.json().get("files", [])
-    return [(f["name"], f["id"]) for f in files if f["mimeType"] in allowed_mime]
-
-def download_file(file_id, suffix):
-    url = f"https://drive.google.com/uc?id={file_id}&export=download"
+    if creds and creds.valid:
+        return build('drive', 'v3', credentials=creds)
+    return None
+
+def upload_to_drive_using_token(file_path, filename, folder_id):
+    service = get_drive_service_from_token()
+    if not service:
+        return False
+    file_metadata = {
+        'name': filename,
+        'parents': [folder_id]
+    }
+    media = MediaFileUpload(file_path, resumable=True)
+    service.files().create(body=file_metadata, media_body=media, fields='id').execute()
+    return True
+
+# === UTILITIES ===
+def get_drive_links(folder_id, mime_prefix="video/"):
+    api_url = f"https://www.googleapis.com/drive/v3/files?q='{folder_id}'+in+parents&key={API_KEY}&fields=files(id,name,mimeType)"
+    res = requests.get(api_url).json()
+    files = res.get("files", [])
+    return [(f["name"], f["id"]) for f in files if f["mimeType"].startswith(mime_prefix)]
+
+def get_file_download_url(file_id):
+    return f"https://drive.google.com/uc?id={file_id}&export=download"
+
+def download_file(url):
     response = requests.get(url, stream=True)
-    temp = tempfile.NamedTemporaryFile(delete=False, suffix=suffix)
+    temp = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4")
     for chunk in response.iter_content(chunk_size=1024 * 1024):
         temp.write(chunk)
     temp.close()
     return temp.name
 
-def extract_face_embedding(image):
-    rgb = cv2.cvtColor(image, 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, _ = image.shape
-            x1 = int(bbox.xmin * w)
-            y1 = int(bbox.ymin * h)
-            x2 = int((bbox.xmin + bbox.width) * w)
-            y2 = int((bbox.ymin + bbox.height) * h)
-            face_crop = image[y1:y2, x1:x2]
-            return cv2.resize(face_crop, (128, 128))
-    return None
-
-def is_match(face1, face2):
-    if face1 is None or face2 is None:
-        return False
-    diff = np.linalg.norm(face1.astype("float") - face2.astype("float"))
-    return diff < 30.0
+def list_registered_faces():
+    st.sidebar.markdown("### 🧑‍💼 Registered Faces")
+    images = get_drive_links(REG_FOLDER_ID, mime_prefix="image/")
+    for name, file_id in images:
+        img_url = get_file_download_url(file_id)
+        img = Image.open(requests.get(img_url, stream=True).raw)
+        st.sidebar.image(img, caption=name, width=120)
+
+# === FACE DETECTION ===
+def detect_faces_from_video(video_path, uploaded_hashes):
+    cap = cv2.VideoCapture(video_path)
+    detected = 0
+    displayed_faces = []
+
+    st.sidebar.markdown("### 🎥 Faces Detected from Video")
+
+    while cap.isOpened():
+        ret, frame = cap.read()
+        if not ret:
+            break
+
+        frame = cv2.resize(frame, (640, 480))
+        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
+                ih, iw, _ = frame.shape
+                x, y, w, h = int(bbox.xmin * iw), int(bbox.ymin * ih), int(bbox.width * iw), int(bbox.height * ih)
+                x, y = max(x, 0), max(y, 0)
+                face = frame[y:y + h, x:x + w]
+                gray = cv2.cvtColor(face, cv2.COLOR_BGR2GRAY)
+                resized = cv2.resize(gray, (100, 100))
+                hsh = hashlib.md5(resized.tobytes()).hexdigest()
+
+                if hsh not in uploaded_hashes:
+                    uploaded_hashes.add(hsh)
+                    tmp_path = os.path.join(tempfile.gettempdir(), f"intruder_{hsh}.jpg")
+                    cv2.imwrite(tmp_path, face)
+                    success = upload_to_drive_using_token(tmp_path, f"intruder_{hsh}.jpg", INTRUDER_FOLDER_ID)
+                    if success:
+                        st.sidebar.image(face, caption="🚨 Intruder", width=120)
+                    else:
+                        st.warning("❌ Upload failed.")
+                else:
+                    st.sidebar.image(face, caption="⛔ Duplicate", width=120)
+                detected += 1
+    cap.release()
+    return detected
 
 # === STREAMLIT UI ===
-st.set_page_config(page_title="Intruder Detection", layout="wide")
-st.title("🔐 Intruder Detection from CCTV Feed")
-st.write("Streaming videos from Google Drive, detecting and matching faces.")
-
-sidebar_faces = []
-
-with st.spinner("Loading registered faces..."):
-    registered = []
-    reg_images = get_drive_files(REG_FOLDER_ID, ["image/jpeg", "image/png"])
-    for name, fid in reg_images:
-        img_path = download_file(fid, ".jpg")
-        img = cv2.imread(img_path)
-        emb = extract_face_embedding(img)
-        if emb is not None:
-            registered.append((name, emb))
-
-with st.spinner("Scanning CCTV feed..."):
-    total_intruders = 0
+st.set_page_config(page_title="CCTV Face Detector", layout="wide")
+st.title("🔐 Intruder Detection from Google Drive CCTV Feed")
+
+list_registered_faces()
+uploaded_hashes = set()
+
+with st.spinner("Processing videos..."):
+    total_detected = 0
     for folder_id in CCTVFEED_IDS:
-        videos = get_drive_files(folder_id, ["video/mp4", "video/x-msvideo", "video/avi"])
-        for vname, fid in videos:
-            st.subheader(f"🎥 {vname}")
-            vid_path = download_file(fid, ".mp4")
-            cap = cv2.VideoCapture(vid_path)
-            frame_count = 0
-            matched_faces = 0
-            unmatched_faces = 0
-
-            while cap.isOpened():
-                ret, frame = cap.read()
-                if not ret:
-                    break
-                face_img = extract_face_embedding(frame)
-                if face_img is not None:
-                    match_found = any(is_match(face_img, emb) for _, emb in registered)
-                    if match_found:
-                        matched_faces += 1
-                    else:
-                        unmatched_faces += 1
-                        temp = tempfile.NamedTemporaryFile(delete=False, suffix=".jpg")
-                        cv2.imwrite(temp.name, face_img)
-                        upload_intruder_face(temp.name)
-                        sidebar_faces.append(temp.name)
-                frame_count += 1
-            cap.release()
-
-            st.success(f"🎯 Processed {frame_count} frames — Matched: {matched_faces}, Unmatched: {unmatched_faces}")
-            total_intruders += unmatched_faces
-
-st.info(f"🎯 Completed processing all videos. Intruders detected: {total_intruders}")
-
-with st.sidebar:
-    st.markdown("## 🚨 Intruder Snapshots")
-    for face_path in sidebar_faces:
-        st.image(face_path, width=160)
+        videos = get_drive_links(folder_id)
+        for name, vid_id in videos:
+            st.subheader(f"🎞️ {name}")
+            vpath = download_file(get_file_download_url(vid_id))
+            count = detect_faces_from_video(vpath, uploaded_hashes)
+            os.remove(vpath)
+            if count > 0:
+                st.success(f"✅ {count} faces detected in {name}")
+                total_detected += count
+            else:
+                st.warning(f"⚠️ No faces found in {name}")
+
+st.info(f"🎯 Completed processing all videos.")