import streamlit as st from PIL import Image from transformers import pipeline from gtts import gTTS st.set_page_config(page_title="Image to Audio Story", page_icon="π¦") caption_pipeline = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base") story_pipeline = pipeline("text-generation", model="Qwen/Qwen2.5-0.5B-Instruct") def extract_image_caption(image_data): img_obj = Image.open(image_data) caption_results = caption_pipeline(img_obj) return caption_results[0]['generated_text'] def compose_story_from_caption(caption_detail): while True: prompt_text = ( "You are a talented and imaginative storyteller for children aged 3 to 10. " "Using the details derived from the image below, craft a complete and captivating tale that includes three main characters, " "an adventurous journey, and delightful surprises. " "Your story should have a clear beginning, middle, and end, and be between 80 and 100 words in length.\n\n" f"Image Details: {caption_detail}\n\nStory:" ) story_results = story_pipeline(prompt_text, num_return_sequences=1, max_new_tokens=150) story_text = story_results[0]['generated_text'] # ζεζ δΊ if "Story:" in story_text: story = story_text.split("Story:", 1)[1].strip() else: story = story_text.strip() return story def convert_text_to_audio(text_content, audio_path="output.mp3"): """ ε°ζζ¬θ½¬ζ’δΈΊι³ι’ζδ»Άγ """ tts_engine = gTTS(text=text_content, lang="en") tts_engine.save(audio_path) return audio_path def run_app(): st.markdown("