# import part import streamlit as st from transformers import pipeline from gtts import gTTS import os # function part # img2text def img2text(url): try: 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 except Exception as e: st.error(f"Error in image to text conversion: {e}") return None # text2story def text2story(text): try: story_generator = pipeline("text-generation", model="gpt2") story = story_generator(text, max_length=100, num_return_sequences=1)[0]["generated_text"] return story except Exception as e: st.error(f"Error in story generation: {e}") return None # text2audio def text2audio(story_text): try: tts = gTTS(text=story_text, lang='en') audio_file = "story_audio.mp3" tts.save(audio_file) return audio_file except Exception as e: st.error(f"Error in text to audio conversion: {e}") return None # main part st.set_page_config(page_title="Your Image to Audio Story", page_icon="🦜") st.header("Turn Your Image to Audio Story") uploaded_file = st.file_uploader("Select an Image...", type=["jpg", "jpeg", "png"]) if uploaded_file is not None: bytes_data = uploaded_file.getvalue() with open(uploaded_file.name, "wb") as file: file.write(bytes_data) st.image(uploaded_file, caption="Uploaded Image", use_column_width=True) # Stage 1: Image to Text st.text('Processing img2text...') scenario = img2text(uploaded_file.name) if scenario: st.write("Image Caption:", scenario) # Stage 2: Text to Story st.text('Generating a story...') story = text2story(scenario) if story: st.write("Generated Story:", story) # Stage 3: Story to Audio data st.text('Generating audio data...') audio_file = text2audio(story) if audio_file: # Play button if st.button("Play Audio"): st.audio(audio_file, format="audio/mp3") # Clean up the audio file after playing os.remove(audio_file)