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import streamlit as st
from PIL import Image
from transformers import pipeline
from gtts import gTTS
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="gpt2")
prompt = f"Please based on following image caption: '{caption}', generate a complete fairy tale story for children with at least 100 words. "
result = story_generator(prompt, max_length=300, num_return_sequences=1)
story = result[0]['generated_text']
if len(story.split()) < 100:
additional = story_generator(prompt, max_length=350, num_return_sequences=1)[0]['generated_text']
story += " " + additional
return story
# ----------------------------
# generate_illustration
# ----------------------------
@st.cache_resource
# def load_image_generator():
# device = "cuda" if torch.cuda.is_available() else "cpu"
# torch_dtype = torch.float16 if device == "cuda" else torch.float32
# pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5")
# pipe = pipe.to(device)
# return pipe
# def generate_illustration(prompt):
# pipe = load_image_generator()
# image_result = pipe(prompt)
# generated_image = image_result.images[0]
# return generated_image
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_prompt = f"Please generate a children's story based on this description: {caption}"
story = generate_story(story_prompt)
st.write("**Story:**")
st.write(story)
# with st.spinner("Generating illustration..."):
# illustration = generate_illustration(story[:200])
# st.write("### Story Illustrations：")
# st.image(illustration, caption="Story Illustrations", use_container_width=True)
with st.spinner("Converting to voice...."):
audio_file = text_to_speech(story)
st.audio(audio_file, format="audio/mp3")
if __name__ == "__main__":
main() |