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import streamlit as st
from PIL import Image
from transformers import pipeline
from gtts import gTTS
import torch
st.set_page_config(page_title="Your Image to Audio Story", page_icon="🦜")
def generate_caption(image_file):
image = Image.open(image_file)
caption_generator = pipeline(
"image-to-text",
model="Salesforce/blip-image-captioning-base",
)
caption_results = caption_generator(image)
caption = caption_results[0]['generated_text']
return caption
def generate_story(caption):
story_generator = pipeline(
"text-generation",
model="Qwen/Qwen2.5-0.5B-Instruct",
)
prompt = (
"You are a highly imaginative children's story writer celebrated for your creativity and captivating narratives. "
"Using the image details provided below, please craft an enchanting tale tailored for children aged 3 to 10. "
"Rather than simply reiterating the image details, enhance your story with imaginative characters, quirky adventures, "
"and delightful surprises that ignite wonder in every young heart. Let your narrative flow naturally and kindle the magic of storytelling. "
"Please ensure that your story is engaging, coherent, and falls between 100 and 300 words in length.\n\n"
f"Image Details: {caption}\n\nStory:"
)
result = story_generator(
prompt,
max_length=300,
num_return_sequences=1,
do_sample=True,
temperature=1.0
)
full_text = result[0]['generated_text']
if "Story:" in full_text:
story = full_text.split("Story:", 1)[1].strip()
else:
story = full_text.strip()
return story
def text_to_speech(text, output_file="output.mp3"):
tts = gTTS(text=text, lang="en")
tts.save(output_file)
return output_file
def main():
st.markdown("<h1 style='text-align: center;'>Your Image to Audio Story 🦜</h1>", unsafe_allow_html=True)
st.write("Upload an image below and we will generate an engaging story from the picture, then convert the story into an audio playback!")
uploaded_file = st.file_uploader("Select Image", type=["png", "jpg", "jpeg"])
if uploaded_file is not None:
image = Image.open(uploaded_file)
st.image(image, caption="Uploaded image", use_container_width=True)
with st.spinner("Image caption being generated..."):
caption = generate_caption(uploaded_file)
st.write("**Image Caption:**", caption)
with st.spinner("Generating story..."):
story = generate_story(caption)
st.write("**Story:**")
st.write(story)
with st.spinner("Converting to voice..."):
audio_file = text_to_speech(story)
st.audio(audio_file, format="audio/mp3")
if __name__ == "__main__":
main() |