Update app.py

app.py

@@ -5,121 +5,122 @@ import requests
 import tempfile
 import mediapipe as mp
 import os
-from PIL import Image
+import base64
 
 # === CONFIGURATION ===
 API_KEY = "AIzaSyDojJrpauA0XZtCCDUuo9xeQHZQamYKsC4"
 CCTVFEED_IDS = ['1KJRkSf2SKEZ1mXS9_si65IwMBtjs6p4n']
 REG_FOLDER_ID = '1qkcR7nQTEtiMH9OFUv2bGxVn08E3dKjF'
-INTRUDER_UPLOAD_URL = "https://upload.gdrive.com/your-anon-endpoint-if-any"  # You can change this if needed
+INTRUDER_FOLDER_ID = '1PPAUWU-wMx7fek73p-hqPqYQypYtG8Ob'
 
-# === 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)
 
-# === 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]
+# === FUNCTIONS ===
+def get_drive_image_links(folder_id):
+    url = f"https://www.googleapis.com/drive/v3/files?q='{folder_id}'+in+parents+and+mimeType='image/jpeg'&key={API_KEY}&fields=files(id,name)"
+    response = requests.get(url).json()
+    return [f"https://drive.google.com/uc?id={f['id']}&export=download" for f in response.get("files", [])]
 
-def download_file(file_id, suffix):
-    url = f"https://drive.google.com/uc?id={file_id}&export=download"
-    response = requests.get(url, stream=True)
+def get_drive_video_links(folder_id):
+    url = f"https://www.googleapis.com/drive/v3/files?q='{folder_id}'+in+parents&key={API_KEY}&fields=files(id,name,mimeType)"
+    files = requests.get(url).json().get("files", [])
+    return [(f["name"], f"https://drive.google.com/uc?id={f['id']}&export=download") 
+            for f in files if f["mimeType"] in ["video/mp4", "video/x-msvideo", "video/avi"]]
+
+def download_file(link, suffix=".mp4"):
+    response = requests.get(link, stream=True)
     temp = tempfile.NamedTemporaryFile(delete=False, suffix=suffix)
     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 embed_face(face_img):
+    face_img = cv2.resize(face_img, (100, 100))
+    return face_img.flatten()
 
-def mse(img1, img2):
-    if img1.shape != img2.shape:
-        return np.inf
-    return np.mean((img1.astype("float") - img2.astype("float")) ** 2)
+def load_known_faces():
+    known_faces = []
+    for link in get_drive_image_links(REG_FOLDER_ID):
+        path = download_file(link, suffix=".jpg")
+        img = cv2.imread(path, cv2.IMREAD_GRAYSCALE)
+        os.remove(path)
+        if img is not None:
+            known_faces.append(embed_face(img))
+    return known_faces
 
 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)
+    target = embed_face(cv2.cvtColor(face_img, cv2.COLOR_BGR2GRAY))
+    distances = [np.mean((target - kf) ** 2) for kf in known_faces]
+    return all(d > threshold for d in distances)
 
-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
+def upload_to_drive(folder_id, img_path):
+    metadata = {
+        'name': os.path.basename(img_path),
+        'parents': [folder_id]
+    }
+    headers = {"Authorization": f"Bearer {API_KEY}"}
+    with open(img_path, "rb") as f:
+        data = f.read()
+    multipart = {
+        "data": ('metadata', '{"name": "%s", "parents": ["%s"]}' % (os.path.basename(img_path), folder_id), 'application/json'),
+        "file": (os.path.basename(img_path), data, 'image/jpeg')
+    }
+    # Public API keys can't upload directly. This stub can be used with service-based token later.
+    st.warning("⚠️ Upload not supported using public API key. Simulated only.")
+    return True
 
-# === APP UI ===
+# === UI START ===
+st.set_page_config(layout="wide")
 st.title("🔐 Intruder Detection from CCTV Feed")
-st.write("Streaming videos from Google Drive, detecting faces using MediaPipe and flagging unknown individuals.")
-
-sidebar_faces = []
+st.write("✅ Using MediaPipe and Google Drive (Public). Only unmatched faces will be flagged.")
 
-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.")
+known_faces = load_known_faces()
+if not known_faces:
+    st.error("No registered faces found in REG folder.")
+    st.stop()
 
-with st.spinner("Processing CCTV videos..."):
+with st.spinner("Processing videos..."):
     intruder_count = 0
+    st.sidebar.title("📸 Faces Detected")
     for folder_id in CCTVFEED_IDS:
-        video_files = get_drive_file_links(folder_id, ["video/mp4", "video/x-msvideo", "video/avi"])
-        for vname, vid in video_files:
+        videos = get_drive_video_links(folder_id)
+        for vname, link in videos:
             st.subheader(f"🎥 {vname}")
-            video_path = download_file(vid, ".mp4")
+            video_path = download_file(link)
             cap = cv2.VideoCapture(video_path)
-            frame_id = 0
+            intruders = []
+
             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)
+                results = face_detector.process(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
                 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:
+                        h, w, _ = frame.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 = frame[y1:y2, x1:x2]
+                        if face.size == 0:
                             continue
-                        if is_intruder(face_crop, known_faces):
-                            sidebar_faces.append(face_crop)
+                        st.sidebar.image(face, caption="Detected Face", width=100)
+                        if is_intruder(face, known_faces):
                             intruder_count += 1
-                            upload_intruder(face_crop, f"intruder_{intruder_count}.jpg")
+                            temp_path = f"intruder_{intruder_count}.jpg"
+                            cv2.imwrite(temp_path, face)
+                            upload_to_drive(INTRUDER_FOLDER_ID, temp_path)
+                            intruders.append(temp_path)
+                            os.remove(temp_path)
             cap.release()
             os.remove(video_path)
+            if intruders:
+                st.success(f"🚨 {len(intruders)} intruder(s) found.")
+            else:
+                st.info("No intruders found.")
 
-    st.success(f"🎯 Intruders detected: {intruder_count}")
-
-# === 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)
+st.info(f"✅ Processed completed. Total intruders flagged: {intruder_count}")