# Import necessary libraries import streamlit as st from transformers import pipeline from gtts import gTTS import os # Function to convert image to text def img2text(url): image_to_text_model = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base") text = image_to_text_model(url)[0]["generated_text"] return text # Function to convert text to a story def text2story(text): # Initialize the text generation pipeline text_generator = pipeline("text-generation", model="distilbert/distilgpt2") # Generate the story directly from the input text story = text_generator(text, max_length=95, num_return_sequences=1)[0]['generated_text'] return story # Function to convert text to audio def text2audio(story_text): # Convert the story text to audio using gTTS tts = gTTS(text=story_text, lang='en') audio_file = "story_audio.mp3" tts.save(audio_file) return audio_file # Main application st.set_page_config(page_title="Your Image to Audio Story", page_icon="🦜") st.header("Turn Your Image into a Fun Audio Story!") uploaded_file = st.file_uploader("Select an Image...", type=["jpg", "jpeg", "png"]) if uploaded_file is not None: # Save the uploaded file bytes_data = uploaded_file.getvalue() with open(uploaded_file.name, "wb") as file: file.write(bytes_data) # Display the uploaded image st.image(uploaded_file, caption="Uploaded Image", use_column_width=True) # Stage 1: Image to Text st.text('Processing image to text...') scenario = img2text(uploaded_file.name) st.write("**Scenario:**", scenario) # Stage 2: Text to Story st.text('Generating a fun story for kids...') story = text2story(scenario) st.write("**Story:**", story) # Stage 3: Story to Audio st.text('Converting story to audio...') audio_file = text2audio(story) # Play button for the generated audio if st.button("Play Audio"): st.audio(audio_file, format="audio/mp3") # Clean up the generated audio file os.remove(audio_file)