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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) | |