Update app.py

app.py

@@ -4,16 +4,8 @@ import pandas as pd
 import tensorflow as tf
 from tensorflow import keras
 import time
+from playsound import playsound
 import streamlit as st
-import pygame
-
-# Initialize Pygame mixer
-pygame.mixer.init()
-
-# Function to play the alert sound
-def play_alert_sound():
-    pygame.mixer.music.load(pygame.mixer.Sound(pygame.mixer.get_init()))  # Load a simple beep sound
-    pygame.mixer.music.play()
 
 # Using Har-cascade classifier from OpenCV
 face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
@@ -23,41 +15,36 @@ model = keras.models.load_model('my_model (1).h5')
 
 # Title for GUI
 st.title('Drowsiness Detection')
+img = []
 
 # Navigation Bar
 nav_choice = st.sidebar.radio('Navigation', ('Home', 'Sleep Detection', 'Help Us Improve'), index=0)
 
 # Home page
 if nav_choice == 'Home':
-    st.header('Prevents sleep deprivation road accidents, by alerting drowsy drivers.')
+    st.header('Preventing Sleep Deprivation Road Accidents')
     st.image('ISHN0619_C3_pic.jpg')
-    st.markdown('<b>In accordance with the survey taken by the Times Of India, about 40 % of road </b>'
-                '<b>accidents are caused</b> '
-                '<b>due to sleep deprivation & fatigued drivers. In order to address this issue, this app will </b>'
-                '<b>alert such drivers with the help of deep learning models and computer vision.</b>'
-                '', unsafe_allow_html=True)
+    st.markdown("""
+        In accordance with a survey by the Times Of India, approximately 40% of road accidents are caused by sleep deprivation and fatigued drivers. 
+        This app aims to address this issue by alerting drowsy drivers using deep learning models and computer vision.
+        """)
     st.image('sleep.jfif', width=300)
-    st.markdown('<h1>How to use?<br></h1>'
-                '<b>1. Go to Sleep Detection page from the Navigation Side-Bar.</b><br>'
-                '<b>2. Make sure that, you have sufficient amount of light, in your room.</b><br>'
-                '<b>3. Align yourself such that, you are clearly visible in the web-cam and '
-                'stay closer to the web-cam. </b><br>'
-                '<b>4. Web-cam will take 3 pictures of you, so keep your eyes in the same state'
-                ' (open or closed) for about 5 seconds.</b><br>'
-                '<b>5. If your eyes are closed, the model will make a beep sound to alert you.</b><br>'
-                '<b>6. Otherwise, the model will continue taking your pictures at regular intervals of time.</b><br>'
-                '<font color="red"><br><b>For the purpose of the training process of the model, '
-                'dataset used is available <a href="https://www.kaggle.com/kutaykutlu/drowsiness-detection", '
-                'target="_blank">here</a></font></b>'
-                , unsafe_allow_html=True)
-    
+    st.markdown("""
+        ### How to Use?
+        1. Go to the Sleep Detection page from the Navigation Sidebar.
+        2. Ensure you have sufficient lighting in your room.
+        3. Position yourself so that you are clearly visible in the webcam and stay close to it.
+        4. Keep your eyes in the same state (open or closed) for about 5 seconds while the webcam captures three pictures.
+        5. If your eyes are closed, the model will trigger a custom sound alert.
+        6. Otherwise, the model will continue monitoring your eyes at regular intervals.
+        **Note:** The dataset used for training the model is available [here](https://www.kaggle.com/kutaykutlu/drowsiness-detection).
+        """)
+
 # Sleep Detection page
 elif nav_choice == 'Sleep Detection':
     st.header('Image Prediction')
-    cap = 0
-    st.success('Please look at your web-cam, while following all the instructions given on the Home page.')
-    st.warning(
-        'Keeping the eyes in the same state is important but you can obviously blink your eyes, if they are open!!!')
+    st.success('Please look at your webcam and follow the instructions provided on the Home page.')
+    st.warning('Keeping your eyes in the same state is crucial. You can blink if your eyes are open!')
     b = st.progress(0)
     for i in range(100):
         time.sleep(0.0001)
@@ -67,7 +54,7 @@ elif nav_choice == 'Sleep Detection':
 
     if start == 'Start':
         decision = 0
-        st.markdown('<font face="Comic sans MS"><b>Detected Facial Region of Interest(ROI)&emsp;&emsp;&emsp;&emsp;&emsp;Extractd'
+        st.markdown('<font face="Comic sans MS"><b>Detected Facial Region of Interest (ROI) &emsp;&emsp;&emsp;&emsp;&emsp;Extracted'
                     ' Eye Features from the ROI</b></font>', unsafe_allow_html=True)
         
         # Best of 3 mechanism for drowsiness detection
@@ -76,6 +63,7 @@ elif nav_choice == 'Sleep Detection':
             ret, frame = cap.read()
             gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
             faces = face_cascade.detectMultiScale(gray, 1.3, 5)
+            
             # Proposal of face region by the har cascade classifier
             for (x, y, w, h) in faces:
                 cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 5)
@@ -84,7 +72,7 @@ elif nav_choice == 'Sleep Detection':
             frame1 = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
 
             try:
-                # Cenentroid method for extraction of eye-patch 
+                # Centroid method for extraction of eye-patch 
                 centx, centy = roi_color.shape[:2]
                 centx //= 2
                 centy //= 2
@@ -124,10 +112,10 @@ elif nav_choice == 'Sleep Detection':
             finally:
                 cap.release()
 
-        # If found drowsy, then make a beep sound to alert the driver
+        # If eyes are closed, play custom sound alert
         if decision == 0:
             st.error('Eye(s) are closed')
-            play_alert_sound()
+            playsound("232857-84052cf6-66a1-4c60-ad86-9ebc19eaab52.mp3")
 
         else:
             st.success('Eyes are Opened')
@@ -137,14 +125,12 @@ elif nav_choice == 'Sleep Detection':
 else:
     st.header('Help Us Improve')
     st.success('We would appreciate your Help!!!')
-    st.markdown(
-        '<font face="Comic sans MS">To make this app better, we would appreciate your small amount of time.</font>'
-        '<font face="Comic sans MS">Let me take you through, some of the basic statistical analysis of this </font>'
-        '<font face="Comic sans MS">model. <br><b>Accuracy with naked eyes = 99.5%<br>Accuracy with spectacles = 96.8%</b><br></font> '
-        '<font face="Comic sans MS">As we can see here, accuracy with spectacles is not at all spectacular, and hence to make this app </font>'
-        '<font face="Comic sans MS">better, and to use it in real-time situations, we require as much data as we can gather.</font> '
-        , unsafe_allow_html=True)
-    st.warning('NOTE: Your identity will be kept anonymous, and only your eye-patch will be extracted!!!')
+    st.markdown("""
+        To improve this app, we need your feedback and contributions. 
+        As part of our efforts, we would like to gather more data.
+        This will help us enhance the accuracy and usability of the app.
+        Your identity will remain anonymous, and only your eye-patch will be extracted for analysis.
+        """)
     # Image upload
     img_upload = st.file_uploader('Upload Image Here', ['png', 'jpg', 'jpeg'])
     if img_upload is not None: