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import streamlit as st |
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from PIL import Image |
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from transformers import pipeline |
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from gtts import gTTS |
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import torch |
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st.set_page_config(page_title="Image to Audio Story", page_icon="🦜") |
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caption_pipeline = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base") |
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story_pipeline = pipeline("text-generation", model="Qwen/Qwen2-1.5B") |
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def extract_image_caption(image_data): |
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img_obj = Image.open(image_data) |
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caption_results = caption_pipeline(img_obj) |
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return caption_results[0]['generated_text'] |
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def compose_story_from_caption(caption_detail): |
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prompt_text = ( |
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"You are a talented and imaginative storyteller for children aged 3 to 10. " |
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"Using the details derived from the image below, craft a captivating tale that goes beyond merely describing the scene. " |
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"Let your creativity shine by introducing engaging characters, adventurous journeys, and delightful surprises. " |
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"Your story should be vivid, original, and between 100 and 300 words in length.\n\n" |
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f"Image Details: {caption_detail}\n\nStory:" |
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) |
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story_results = story_pipeline(prompt_text, num_return_sequences=1) |
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story_text = story_results[0]['generated_text'] |
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return story_text.split("Story:", 1)[1].strip() if "Story:" in story_text else story_text.strip() |
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def convert_text_to_audio(text_content, audio_path="output.mp3"): |
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tts_engine = gTTS(text=text_content, lang="en") |
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tts_engine.save(audio_path) |
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return audio_path |
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def run_app(): |
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st.markdown("<h1 style='text-align: center;'>Your Image to Audio Story 🦜</h1>", unsafe_allow_html=True) |
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st.write("Upload an image below and we will generate an engaging story from the picture, then convert the story into an audio playback!") |
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uploaded_image = st.file_uploader("Select an Image", type=["png", "jpg", "jpeg"]) |
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if uploaded_image is not None: |
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image_display = Image.open(uploaded_image) |
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st.image(image_display, caption="Uploaded Image", use_container_width=True) |
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with st.spinner("Generating caption for the image..."): |
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caption_text = extract_image_caption(uploaded_image) |
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st.write("**Generated Caption:**", caption_text) |
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with st.spinner("Composing story..."): |
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story_text = compose_story_from_caption(caption_text) |
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st.write("**Story:**") |
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st.write(story_text) |
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with st.spinner("Converting text to audio..."): |
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audio_file = convert_text_to_audio(story_text) |
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st.audio(audio_file, format="audio/mp3") |
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if __name__ == "__main__": |
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run_app() |
