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| from streamlit_webrtc import webrtc_streamer, WebRtcMode, RTCConfiguration | |
| import streamlit as st | |
| import av | |
| import cv2 | |
| import numpy as np | |
| from deepface import DeepFace | |
| import time | |
| st.set_page_config(page_title="AI Facial Interview Monitor", layout="wide") | |
| st.title(":blue[MOCKVIEWER - Face Monitoring System]") | |
| # Load Haar Cascade models | |
| face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml") | |
| eye_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_eye.xml") | |
| # Upload reference image | |
| uploaded_image = st.file_uploader("Upload your reference face image", type=["jpg", "jpeg", "png"]) | |
| if uploaded_image: | |
| user_ref_img = cv2.imdecode(np.frombuffer(uploaded_image.read(), np.uint8), cv2.IMREAD_COLOR) | |
| st.image(user_ref_img, caption="Reference Image", use_column_width=True) | |
| face_detected_time = time.time() | |
| last_verified_time = 0 | |
| # Configs | |
| FACE_TIMEOUT = 60 # seconds of face absence before cancelling | |
| VERIFY_INTERVAL = 30 # seconds between face identity checks | |
| def is_confident_pose(face_roi): | |
| """Very basic heuristic — head is upright, eyes are visible.""" | |
| gray = cv2.cvtColor(face_roi, cv2.COLOR_BGR2GRAY) | |
| eyes = eye_cascade.detectMultiScale(gray, 1.1, 4) | |
| return len(eyes) >= 1 | |
| def match_identity(live_face, ref_img): | |
| try: | |
| result = DeepFace.verify(live_face, ref_img, enforce_detection=False, model_name='Facenet', detector_backend='opencv') | |
| return result["verified"] | |
| except Exception as e: | |
| print("Verification error:", e) | |
| return False | |
| class VideoProcessor: | |
| def __init__(self): | |
| self.last_check = time.time() | |
| self.last_verified = time.time() | |
| self.face_missing = False | |
| def recv(self, frame): | |
| global face_detected_time, last_verified_time | |
| img = frame.to_ndarray(format="bgr24") | |
| gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) | |
| faces = face_cascade.detectMultiScale(gray, 1.1, 4) | |
| if len(faces) == 0: | |
| if time.time() - face_detected_time > FACE_TIMEOUT: | |
| cv2.putText(img, "❌ Interview Cancelled: Face not visible!", (30, 30), | |
| cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 2) | |
| else: | |
| cv2.putText(img, "⚠️ Face not visible. You have 60 seconds.", (30, 30), | |
| cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 255), 2) | |
| else: | |
| face_detected_time = time.time() | |
| for (x, y, w, h) in faces: | |
| face_roi = img[y:y+h, x:x+w] | |
| # Eye and posture check | |
| confident = is_confident_pose(face_roi) | |
| status = "✅ Confident Pose" if confident else "⚠️ Look Straight!" | |
| color = (0, 255, 0) if confident else (0, 255, 255) | |
| cv2.putText(img, status, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.7, color, 2) | |
| cv2.rectangle(img, (x, y), (x + w, y + h), color, 2) | |
| # Identity check every VERIFY_INTERVAL seconds | |
| if uploaded_image and (time.time() - last_verified_time) > VERIFY_INTERVAL: | |
| matched = match_identity(face_roi, user_ref_img) | |
| last_verified_time = time.time() | |
| if not matched: | |
| cv2.putText(img, "❌ Identity mismatch!", (x, y + h + 30), | |
| cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 2) | |
| else: | |
| cv2.putText(img, "✅ Identity Verified", (x, y + h + 30), | |
| cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 0), 2) | |
| return av.VideoFrame.from_ndarray(img, format="bgr24") | |
| webrtc_streamer( | |
| key="monitor", | |
| video_processor_factory=VideoProcessor, | |
| mode=WebRtcMode.RECVONLY, # ✅ FIXED: Use enum, not string | |
| rtc_configuration=RTCConfiguration(iceServers=[]) # Disable STUN | |
| ) |