Added simple app.py

app.py

@@ -1,124 +1,36 @@
-import os
-import time
-import cv2
+from streamlit_webrtc import webrtc_streamer, RTCConfiguration
 import av
-import numpy as np
+import cv2
+import time
 import streamlit as st
-from deepface import DeepFace
-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
-# ---------------------------------------------
-face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml")
-eye_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_eye.xml")
+cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
 
-# ---------------------------------------------
-# 🖼️ 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)
+st.title(":violet[FACE DETECTION NOTIFIER]")
+a = st.button(":blue[PUSH NOTIFICATIONS]")
 
-# ---------------------------------------------
-# ⏱️ Global State Variables
-# ---------------------------------------------
-face_detected_time = time.time()
-last_verified_time = 0
 
-# ---------------------------------------------
-# ⚙️ 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):
-    """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'
-        )
-        return result["verified"]
-    except Exception as e:
-        print("Verification error:", e)
-        return False
-
-# ---------------------------------------------
-# 📹 Streamlit Webcam Video Processor
-# ---------------------------------------------
+if a:
+    st.toast("PUSH NOTIFICATION ENABLED")
+    time.sleep(5)
+    st.toast("WAKE UP!DON'T SLEEP")
+	
+	
 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, user_ref_img
-        img = frame.to_ndarray(format="bgr24")
-        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-
-        faces = face_cascade.detectMultiScale(gray, 1.1, 4)
+	def recv(self, frame):
+		frm = frame.to_ndarray(format="bgr24")
 
-        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]
+		faces = cascade.detectMultiScale(cv2.cvtColor(frm, cv2.COLOR_BGR2GRAY), 1.1, 3)
 
-                # 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)
+		for x,y,w,h in faces:
+			cv2.rectangle(frm, (x,y), (x+w, y+h), (0,255,0), 3)
 
-                # 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 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(frm, format='bgr24')
 
-        return av.VideoFrame.from_ndarray(img, format="bgr24")
+webrtc_streamer(key="key", video_processor_factory=VideoProcessor,
+				rtc_configuration=RTCConfiguration(
+					{"iceServers": [{"urls": ["stun:stun.l.google.com:19302"]}]}
+					)
+	)
 
-# ---------------------------------------------
-# 🔌 Activate Webcam Stream
-# ---------------------------------------------
-webrtc_streamer(
-    key="monitor",
-    video_processor_factory=VideoProcessor,
-    mode=WebRtcMode.RECVONLY,
-    rtc_configuration=RTCConfiguration(iceServers=[])
-)
+