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import os
import streamlit as st
import requests
from transformers import pipeline
from typing import Dict
from together import Together
from utils import img2txt, txt2story, txt2speech, get_user_preferences
# Main function
def main():
st.set_page_config(page_title="🎨 Image-to-Audio Story 🎧", page_icon="🖼️")
st.title("Turn the Image into Audio Story")
# Allows users to upload an image file
uploaded_file = st.file_uploader("# 📷 Upload an image...", type=["jpg", "jpeg", "png"])
# Parameters for LLM model (in the sidebar)
st.sidebar.markdown("# LLM Inference Configuration Parameters")
top_k = st.sidebar.number_input("Top-K", min_value=1, max_value=100, value=5)
top_p = st.sidebar.number_input("Top-P", min_value=0.0, max_value=1.0, value=0.8)
temperature = st.sidebar.number_input("Temperature", min_value=0.1, max_value=2.0, value=1.5)
# Get user preferences for the story
st.markdown("## Story Preferences")
preferences = get_user_preferences()
if uploaded_file is not None:
# Reads and saves uploaded image file
bytes_data = uploaded_file.read()
with open("uploaded_image.jpg", "wb") as file:
file.write(bytes_data)
st.image(uploaded_file, caption='🖼️ Uploaded Image', use_column_width=True)
# Initiates AI processing and story generation
with st.spinner("## 🤖 AI is at Work! "):
scenario = img2txt("uploaded_image.jpg") # Extracts text from the image
# Modify the prompt to include user preferences
prompt = f"Based on the image description: '{scenario}', create a {preferences['genre']} story set in {preferences['setting']} in {preferences['continent']}. " \
f"The story should have a {preferences['tone']} tone and explore the theme of {preferences['theme']}. " \
f"The main conflict should be {preferences['conflict']}. " \
f"The story should have a {preferences['twist']} and end with a {preferences['ending']} ending."
story = txt2story(prompt, top_k, top_p, temperature) # Generates a story based on the image text, LLM params, and user preferences
txt2speech(story) # Converts the story to audio
st.markdown("---")
st.markdown("## 📜 Image Caption")
st.write(scenario)
st.markdown("---")
st.markdown("## 📖 Story")
st.write(story)
st.markdown("---")
st.markdown("## 🎧 Audio Story")
st.audio("audio_story.wav")
if __name__ == '__main__':
main()
# Credits
st.markdown("### Credits")
st.caption('''
Made with ❤️ by @Aditya-Neural-Net-Ninja\n
Utilizes Image-to-Text, Text Generation, Text-to-Speech Transformer Models\n
Gratitude to Streamlit, 🤗 Spaces for Deployment & Hosting
''') |