Create app.py

app.py

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+import cv2
+import dlib
+import pyttsx3
+from scipy.spatial import distance
+import streamlit as st
+import numpy as np
+
+# INITIALIZING THE pyttsx3 SO THAT
+# ALERT AUDIO MESSAGE CAN BE DELIVERED
+engine = pyttsx3.init()
+
+# FACE DETECTION OR MAPPING THE FACE TO
+# GET THE Eye AND EYES DETECTED
+face_detector = dlib.get_frontal_face_detector()
+
+# PUT THE LOCATION OF .DAT FILE (FILE FOR
+# PREDICTING THE LANDMARKS ON FACE )
+dlib_facelandmark = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")
+
+# FUNCTION CALCULATING THE ASPECT RATIO FOR
+# THE Eye BY USING EUCLIDEAN DISTANCE FUNCTION
+def Detect_Eye(eye):
+    poi_A = distance.euclidean(eye[1], eye[5])
+    poi_B = distance.euclidean(eye[2], eye[4])
+    poi_C = distance.euclidean(eye[0], eye[3])
+    aspect_ratio_Eye = (poi_A + poi_B) / (2 * poi_C)
+    return aspect_ratio_Eye
+
+# Function to process each frame
+def process_frame(frame):
+    gray_scale = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+    faces = face_detector(gray_scale)
+
+    for face in faces:
+        face_landmarks = dlib_facelandmark(gray_scale, face)
+        leftEye = []
+        rightEye = []
+
+        # LEFT EYE points
+        for n in range(42, 48):
+            x = face_landmarks.part(n).x
+            y = face_landmarks.part(n).y
+            rightEye.append((x, y))
+            next_point = n + 1 if n < 47 else 42
+            x2 = face_landmarks.part(next_point).x
+            y2 = face_landmarks.part(next_point).y
+            cv2.line(frame, (x, y), (x2, y2), (0, 255, 0), 1)
+
+        # RIGHT EYE points
+        for n in range(36, 42):
+            x = face_landmarks.part(n).x
+            y = face_landmarks.part(n).y
+            leftEye.append((x, y))
+            next_point = n + 1 if n < 41 else 36
+            x2 = face_landmarks.part(next_point).x
+            y2 = face_landmarks.part(next_point).y
+            cv2.line(frame, (x, y), (x2, y2), (255, 255, 0), 1)
+
+        # ASPECT RATIO
+        right_Eye = Detect_Eye(rightEye)
+        left_Eye = Detect_Eye(leftEye)
+        Eye_Rat = (left_Eye + right_Eye) / 2
+
+        # DROWSINESS ALERT
+        if round(Eye_Rat, 2) < 0.25:
+            cv2.putText(frame, "DROWSINESS DETECTED", (50, 100),
+                        cv2.FONT_HERSHEY_PLAIN, 2, (21, 56, 210), 3)
+            cv2.putText(frame, "Alert!!!! WAKE UP DUDE", (50, 450),
+                        cv2.FONT_HERSHEY_PLAIN, 2, (21, 56, 212), 3)
+            engine.say("Alert!!!! WAKE UP DUDE")
+            engine.runAndWait()
+
+    return frame
+
+# Streamlit app
+st.title("Drowsiness Detection App")
+run = st.checkbox('Run Drowsiness Detection')
+
+# Open webcam
+cap = cv2.VideoCapture(0)
+
+while run:
+    ret, frame = cap.read()
+    if not ret:
+        st.write("Failed to grab frame")
+        break
+    
+    processed_frame = process_frame(frame)
+
+    # Convert BGR to RGB
+    processed_frame = cv2.cvtColor(processed_frame, cv2.COLOR_BGR2RGB)
+    st.image(processed_frame, channels="RGB", use_column_width=True)
+
+cap.release()