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import streamlit as st
import cv2
import requests
import numpy as np
import tempfile
import time
import mediapipe as mp
# === CONFIGURATION ===
CCTVFEED_IDS = ['1KJRkSf2SKEZ1mXS9_si65IwMBtjs6p4n'] # List of folder IDs (Google Drive)
SUPPORTED_EXTENSIONS = ['.mp4', '.avi']
# === INITIALIZE FACE DETECTION ===
mp_face_detection = mp.solutions.face_detection
face_detection = mp_face_detection.FaceDetection(model_selection=0, min_detection_confidence=0.5)
# === HELPER FUNCTIONS ===
def list_gdrive_folder_files(folder_id):
"""Returns list of (filename, download_url) from public Google Drive folder."""
api_url = f"https://drive.google.com/embeddedfolderview?id={folder_id}#grid"
resp = requests.get(api_url)
file_lines = resp.text.splitlines()
links = []
for line in file_lines:
if 'data-id=' in line and any(ext in line for ext in SUPPORTED_EXTENSIONS):
try:
file_id = line.split('data-id="')[1].split('"')[0]
file_name = line.split('data-title="')[1].split('"')[0]
download_url = f"https://drive.google.com/uc?id={file_id}"
links.append((file_name, download_url))
except Exception:
continue
return links
def stream_and_process_video(video_url, filename):
"""Streams video frame-by-frame and runs face detection."""
st.markdown(f"### 🎥 Processing `{filename}`")
vid_bytes = requests.get(video_url, stream=True).content
tfile = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4")
tfile.write(vid_bytes)
cap = cv2.VideoCapture(tfile.name)
frame_count = 0
face_count = 0
frame_display = st.empty()
stats_display = st.empty()
while cap.isOpened():
ret, frame = cap.read()
if not ret:
break
frame_count += 1
# Convert BGR to RGB
image_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
results = face_detection.process(image_rgb)
# Draw faces
if results.detections:
for detection in results.detections:
bboxC = detection.location_data.relative_bounding_box
ih, iw, _ = frame.shape
x, y, w, h = int(bboxC.xmin * iw), int(bboxC.ymin * ih), int(bboxC.width * iw), int(bboxC.height * ih)
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
face_count += 1
# Resize for display
display_frame = cv2.resize(frame, (640, 360))
frame_display.image(display_frame, channels="BGR")
stats_display.markdown(f"**Frames Processed:** {frame_count} | **Faces Detected So Far:** {face_count}")
time.sleep(1 / 24.0) # Approx. 24 FPS
cap.release()
st.success(f"✅ Done! `{filename}`: {frame_count} frames, {face_count} faces detected.")
# === MAIN UI ===
st.title("🚨 CCTV Face Detection from Google Drive")
st.markdown("Detects faces in `.mp4` and `.avi` videos from your public Google Drive folder.")
for folder_id in CCTVFEED_IDS:
videos = list_gdrive_folder_files(folder_id)
if not videos:
st.warning(f"No valid videos found in folder ID: {folder_id}")
continue
for name, url in videos:
if st.button(f"▶️ Run Face Detection on `{name}`"):
stream_and_process_video(url, name)
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