Update app.py
Browse files
app.py
CHANGED
@@ -7,16 +7,6 @@ import time
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import streamlit as st
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import pygame
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# Setting up config for GPU usage
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physical_devices = tf.config.list_physical_devices("GPU")
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tf.config.experimental.set_memory_growth(physical_devices[0], True)
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# Using Har-cascade classifier from OpenCV
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face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
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# Loading the trained model for prediction purpose
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model = keras.models.load_model('my_model (1).h5')
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# Initialize Pygame mixer
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pygame.mixer.init()
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@@ -25,6 +15,12 @@ def play_alert_sound():
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pygame.mixer.music.load(pygame.mixer.Sound(pygame.mixer.get_init())) # Load a simple beep sound
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pygame.mixer.music.play()
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# Title for GUI
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st.title('Drowsiness Detection')
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@@ -54,10 +50,11 @@ if nav_choice == 'Home':
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'dataset used is available <a href="https://www.kaggle.com/kutaykutlu/drowsiness-detection", '
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'target="_blank">here</a></font></b>'
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, unsafe_allow_html=True)
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# Sleep Detection page
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elif nav_choice == 'Sleep Detection':
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st.header('Image Prediction')
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st.success('Please look at your web-cam, while following all the instructions given on the Home page.')
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st.warning(
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'Keeping the eyes in the same state is important but you can obviously blink your eyes, if they are open!!!')
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@@ -106,6 +103,7 @@ elif nav_choice == 'Sleep Detection':
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img_container[0].image(frame1, width=250)
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img_container[2].image(cv2.cvtColor(eye_1, cv2.COLOR_BGR2RGB), width=150)
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img_container[3].image(cv2.cvtColor(eye_2, cv2.COLOR_BGR2RGB), width=150)
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# Decision variable for prediction
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if e1 == 1 or e2 == 1:
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@@ -126,10 +124,11 @@ elif nav_choice == 'Sleep Detection':
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finally:
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cap.release()
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# If found drowsy,
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if decision == 0:
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st.error('Eye(s) are closed')
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play_alert_sound()
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else:
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st.success('Eyes are Opened')
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st.warning('Please select "Stop" and then "Start" to try again')
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import streamlit as st
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import pygame
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# Initialize Pygame mixer
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pygame.mixer.init()
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pygame.mixer.music.load(pygame.mixer.Sound(pygame.mixer.get_init())) # Load a simple beep sound
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pygame.mixer.music.play()
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# Using Har-cascade classifier from OpenCV
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face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
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# Loading the trained model for prediction purpose
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model = keras.models.load_model('my_model (1).h5')
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# Title for GUI
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st.title('Drowsiness Detection')
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'dataset used is available <a href="https://www.kaggle.com/kutaykutlu/drowsiness-detection", '
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'target="_blank">here</a></font></b>'
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, unsafe_allow_html=True)
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# Sleep Detection page
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elif nav_choice == 'Sleep Detection':
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st.header('Image Prediction')
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cap = 0
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st.success('Please look at your web-cam, while following all the instructions given on the Home page.')
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st.warning(
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'Keeping the eyes in the same state is important but you can obviously blink your eyes, if they are open!!!')
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img_container[0].image(frame1, width=250)
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img_container[2].image(cv2.cvtColor(eye_1, cv2.COLOR_BGR2RGB), width=150)
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img_container[3].image(cv2.cvtColor(eye_2, cv2.COLOR_BGR2RGB), width=150)
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print(e1, e2)
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# Decision variable for prediction
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if e1 == 1 or e2 == 1:
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finally:
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cap.release()
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# If found drowsy, then make a beep sound to alert the driver
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if decision == 0:
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st.error('Eye(s) are closed')
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play_alert_sound()
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else:
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st.success('Eyes are Opened')
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st.warning('Please select "Stop" and then "Start" to try again')
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