Update app.py

app.py

@@ -5,7 +5,6 @@ import requests
 import tempfile
 import mediapipe as mp
 import os
-from PIL import Image
 
 # === CONFIGURATION ===
 API_KEY = "AIzaSyDojJrpauA0XZtCCDUuo9xeQHZQamYKsC4"
@@ -13,6 +12,7 @@ CCTVFEED_IDS = ['1KJRkSf2SKEZ1mXS9_si65IwMBtjs6p4n']
 REG_FOLDER_ID = '1qkcR7nQTEtiMH9OFUv2bGxVn08E3dKjF'
 INTRUDER_FOLDER_ID = '1PPAUWU-wMx7fek73p-hqPqYQypYtG8Ob'
 MATCH_THRESHOLD = 7000
+FRAME_SKIP = 30  # Show every 30th frame for debugging
 
 # === SETUP ===
 mp_face_detection = mp.solutions.face_detection
@@ -20,105 +20,106 @@ mp_drawing = mp.solutions.drawing_utils
 face_detector = mp_face_detection.FaceDetection(model_selection=1, min_detection_confidence=0.5)
 
 # === FUNCTIONS ===
-def get_drive_image_faces(folder_id):
-    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", [])
-    faces = []
+def get_drive_files(folder_id, mime_filter=None):
+    url = f"https://www.googleapis.com/drive/v3/files?q='{folder_id}'+in+parents&key={API_KEY}&fields=files(id,name,mimeType)"
+    resp = requests.get(url)
+    files = resp.json().get("files", [])
+    if mime_filter:
+        files = [f for f in files if f['mimeType'] in mime_filter]
+    return files
 
-    for f in files:
-        if "image" in f["mimeType"]:
-            link = f"https://drive.google.com/uc?id={f['id']}&export=download"
-            img = requests.get(link).content
-            temp = tempfile.NamedTemporaryFile(delete=False, suffix=".jpg")
-            temp.write(img)
-            temp.close()
-            gray = cv2.imread(temp.name, cv2.IMREAD_GRAYSCALE)
-            if gray is not None:
-                gray = cv2.resize(gray, (100, 100))
-                faces.append(gray)
-            os.remove(temp.name)
-    return faces
-
-def is_match(face_img, known_faces, threshold=MATCH_THRESHOLD):
-    face_img = cv2.resize(face_img, (100, 100))
-    errors = [np.mean((face_img - kf) ** 2) for kf in known_faces]
-    return any(err < threshold for err in errors)
-
-def get_drive_video_links(folder_id):
-    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", [])
-    video_links = []
-    for f in files:
-        if f["mimeType"] in ["video/mp4", "video/x-msvideo", "video/avi"]:
-            link = f"https://drive.google.com/uc?id={f['id']}&export=download"
-            video_links.append((f["name"], link))
-    return video_links
-
-def download_video(link):
-    response = requests.get(link, stream=True)
-    temp = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4")
-    for chunk in response.iter_content(chunk_size=1024*1024):
+def download_file(file_id, suffix=".tmp"):
+    url = f"https://drive.google.com/uc?id={file_id}&export=download"
+    r = requests.get(url, stream=True)
+    temp = tempfile.NamedTemporaryFile(delete=False, suffix=suffix)
+    for chunk in r.iter_content(chunk_size=1024*1024):
         temp.write(chunk)
     temp.close()
     return temp.name
 
-def detect_intruders(video_path, known_faces):
+def is_known_face(face_img, known_faces):
+    resized = cv2.resize(face_img, (100, 100))
+    errors = [np.mean((resized - kf) ** 2) for kf in known_faces]
+    return any(err < MATCH_THRESHOLD for err in errors)
+
+def load_registered_faces():
+    reg_files = get_drive_files(REG_FOLDER_ID, ['image/jpeg', 'image/jpg', 'image/png'])
+    known_faces = []
+    for f in reg_files:
+        path = download_file(f['id'], suffix=".jpg")
+        img = cv2.imread(path, cv2.IMREAD_GRAYSCALE)
+        if img is not None:
+            resized = cv2.resize(img, (100, 100))
+            known_faces.append(resized)
+        os.remove(path)
+    return known_faces
+
+def process_video_with_debug(video_path, known_faces):
     cap = cv2.VideoCapture(video_path)
-    intruder_frames = 0
-    faces_displayed = 0
+    frame_number = 0
+    intruder_count = 0
 
+    st.subheader("🔍 Detection Debug Log")
     while cap.isOpened():
         ret, frame = cap.read()
         if not ret:
             break
+        frame_number += 1
+
+        if frame_number % FRAME_SKIP != 0:
+            continue
+
         rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
         results = face_detector.process(rgb)
 
         if results.detections:
+            status = "✅ Face Detected"
+            color = (0, 255, 0)
+            intruder_found = False
             for det in results.detections:
                 bbox = det.location_data.relative_bounding_box
-                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)
+                h, w = frame.shape[:2]
+                x, y = int(bbox.xmin * w), int(bbox.ymin * h)
+                bw, bh = int(bbox.width * w), int(bbox.height * h)
+                face_crop = gray[max(0, y):y+bh, max(0, x):x+bw]
+                if face_crop.size > 0 and not is_known_face(face_crop, known_faces):
+                    intruder_count += 1
+                    intruder_found = True
+                    st.image(frame, caption=f"🚨 Intruder #{intruder_count} @ frame {frame_number}", channels="BGR")
+            if not intruder_found:
+                st.image(frame, caption=f"✅ Known face(s) @ frame {frame_number}", channels="BGR")
+        else:
+            status = "❌ No Face"
+            color = (0, 0, 255)
+            st.image(frame, caption=f"❌ No Face Detected @ frame {frame_number}", channels="BGR")
 
-                face_crop = frame[max(y1,0):y2, max(x1,0):x2]
-                gray_face = cv2.cvtColor(face_crop, cv2.COLOR_BGR2GRAY)
-
-                if not is_match(gray_face, known_faces):
-                    intruder_frames += 1
-                    faces_displayed += 1
-                    st.image(face_crop, caption=f"Unmatched face #{faces_displayed}", channels="BGR", use_column_width=True)
-        if faces_displayed >= 3:
-            break
     cap.release()
-    return intruder_frames
+    return intruder_count
 
-# === STREAMLIT UI ===
-st.title("🔐 Intruder Detection from CCTV Feed")
-st.write("Streaming videos from Google Drive, comparing with registered faces, and displaying unmatched intruders.")
+# === UI ===
+st.title("🔐 Intruder Detection with Visual Debug")
+st.write("Streaming videos from Google Drive. Displays detection status frame by frame.")
 
 with st.spinner("Loading registered faces..."):
-    registered_faces = get_drive_image_faces(REG_FOLDER_ID)
+    known_faces = load_registered_faces()
 
-if not registered_faces:
-    st.error("No registered face images found.")
+if not known_faces:
+    st.error("❌ No registered face images found.")
 else:
     with st.spinner("Processing videos..."):
         total_intruders = 0
         for folder_id in CCTVFEED_IDS:
-            videos = get_drive_video_links(folder_id)
-            for vname, link in videos:
-                st.subheader(f"🎥 {vname}")
-                video_file = download_video(link)
-                count = detect_intruders(video_file, registered_faces)
-                os.remove(video_file)
-                if count > 0:
-                    st.success(f"✅ {count} unmatched faces detected.")
-                    total_intruders += 1
+            vids = get_drive_files(folder_id, ['video/mp4', 'video/x-msvideo', 'video/avi'])
+            st.write(f"📁 Found {len(vids)} video(s) in CCTV folder.")
+            for v in vids:
+                st.subheader(f"🎥 {v['name']}")
+                vpath = download_file(v['id'], suffix=".mp4")
+                detected = process_video_with_debug(vpath, known_faces)
+                os.remove(vpath)
+                if detected > 0:
+                    st.success(f"✅ Detected {detected} intruder(s) in this video.")
+                    total_intruders += detected
                 else:
-                    st.warning("⚠️ No intruders detected.")
-        st.info(f"🔎 Completed. Total videos with intruders: {total_intruders}")
+                    st.info("No intruders detected.")
+        st.info(f"🔎 Completed. Total intruders across all videos: {total_intruders}")