Update app.py

app.py

@@ -1,49 +1,73 @@
-from streamlit_webrtc import webrtc_streamer, WebRtcMode, RTCConfiguration
-import streamlit as st
-import av
+import os
+import time
 import cv2
+import av
 import numpy as np
+import streamlit as st
 from deepface import DeepFace
-import time
+from streamlit_webrtc import webrtc_streamer, WebRtcMode, RTCConfiguration
 
+# ---------------------------------------------
+# 🌐 Streamlit Page Config
+# ---------------------------------------------
 st.set_page_config(page_title="AI Facial Interview Monitor", layout="wide")
-
 st.title(":blue[MOCKVIEWER - Face Monitoring System]")
 
-# Load Haar Cascade models
+# ---------------------------------------------
+# 📦 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
+# ---------------------------------------------
+# 🖼️ Upload Reference Image
+# ---------------------------------------------
 uploaded_image = st.file_uploader("Upload your reference face image", type=["jpg", "jpeg", "png"])
+user_ref_img = None
 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)
 
+# ---------------------------------------------
+# ⏱️ Global State Variables
+# ---------------------------------------------
 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
-
+# ---------------------------------------------
+# ⚙️ Configurations
+# ---------------------------------------------
+FACE_TIMEOUT = 60         # seconds of face absence before cancelling
+VERIFY_INTERVAL = 30      # seconds between identity checks
 
+# ---------------------------------------------
+# 👁️ Confidence Heuristic
+# ---------------------------------------------
 def is_confident_pose(face_roi):
-    """Very basic heuristic — head is upright, eyes are visible."""
+    """Check if eyes are visible and head is upright."""
     gray = cv2.cvtColor(face_roi, cv2.COLOR_BGR2GRAY)
     eyes = eye_cascade.detectMultiScale(gray, 1.1, 4)
     return len(eyes) >= 1
 
-
+# ---------------------------------------------
+# 🧬 Identity Verification
+# ---------------------------------------------
 def match_identity(live_face, ref_img):
     try:
-        result = DeepFace.verify(live_face, ref_img, enforce_detection=False, model_name='Facenet', detector_backend='opencv')
+        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
 
-
+# ---------------------------------------------
+# 📹 Streamlit Webcam Video Processor
+# ---------------------------------------------
 class VideoProcessor:
     def __init__(self):
         self.last_check = time.time()
@@ -51,7 +75,7 @@ class VideoProcessor:
         self.face_missing = False
 
     def recv(self, frame):
-        global face_detected_time, last_verified_time
+        global face_detected_time, last_verified_time, user_ref_img
         img = frame.to_ndarray(format="bgr24")
         gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
 
@@ -69,30 +93,32 @@ class VideoProcessor:
             for (x, y, w, h) in faces:
                 face_roi = img[y:y+h, x:x+w]
 
-                # Eye and posture check
+                # Eye/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:
+                # Identity Verification
+                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:
+                    if matched:
                         cv2.putText(img, "✅ Identity Verified", (x, y + h + 30),
                                     cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 0), 2)
+                    else:
+                        cv2.putText(img, "❌ Identity mismatch!", (x, y + h + 30),
+                                    cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 2)
 
         return av.VideoFrame.from_ndarray(img, format="bgr24")
 
-
+# ---------------------------------------------
+# 🔌 Activate Webcam Stream
+# ---------------------------------------------
 webrtc_streamer(
     key="monitor",
     video_processor_factory=VideoProcessor,
-    mode=WebRtcMode.RECVONLY,  # ✅ FIXED: Use enum, not string
-    rtc_configuration=RTCConfiguration(iceServers=[])  # Disable STUN
-)
+    mode=WebRtcMode.RECVONLY,
+    rtc_configuration=RTCConfiguration(iceServers=[])
+)