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| import streamlit as st | |
| from transformers import pipeline | |
| from gtts import gTTS | |
| from PIL import Image | |
| import time | |
| from playsound import playsound | |
| def load_model(): | |
| """Retrieves the trained model""" | |
| model = pipeline('image-to-text') | |
| return model | |
| def main(): | |
| caption = load_model() | |
| st.title('Welcome to image to speech app') | |
| instructions = """Click an image using inbuilt camera or upload an image file""" | |
| st.write(instructions) | |
| img = None | |
| pictureCam = st.camera_input('Take a picture') | |
| pictureUpload = st.file_uploader('Upload An Image') | |
| if pictureCam : | |
| st.write('clicked image from webcam') | |
| st.image(pictureCam) | |
| img = Image.open(pictureCam) | |
| elif pictureUpload : | |
| st.write('uploaded image from device') | |
| st.image(pictureUpload) | |
| img = Image.open(pictureUpload) | |
| if img is not None : | |
| description = caption(img) | |
| generated_text = description[0]['generated_text'] | |
| st.write(generated_text) | |
| generated_audio = gTTS(generated_text) | |
| generated_audio.save('demo.mp3') | |
| audio_file = open('demo.mp3', 'rb') | |
| audio_bytes = audio_file.read() | |
| st.audio(audio_bytes, format='audio/ogg',start_time=0) | |
| if __name__ == '__main__' : | |
| main() |