Update app.py
Browse files
app.py
CHANGED
@@ -2,21 +2,32 @@ 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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# Load models once
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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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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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@@ -26,19 +37,30 @@ def compose_story_from_caption(caption_detail):
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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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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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@@ -56,5 +78,6 @@ def run_app():
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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()
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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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st.set_page_config(page_title="Image to Audio Story", page_icon="🦜")
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def extract_image_caption(image_data):
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"""
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利用预训练模型从图像中提取描述性文字。
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"""
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img_obj = Image.open(image_data)
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caption_pipeline = pipeline(
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"image-to-text",
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model="Salesforce/blip-image-captioning-base",
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)
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caption_results = caption_pipeline(img_obj)
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caption_text = caption_results[0]['generated_text']
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return caption_text
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def compose_story_from_caption(caption_detail):
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"""
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根据图像描述创作一篇充满创意的儿童故事。
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"""
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story_pipeline = pipeline(
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"text-generation",
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model="Qwen/Qwen2-1.5B",
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)
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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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)
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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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if "Story:" in story_text:
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story = story_text.split("Story:", 1)[1].strip()
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else:
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story = story_text.strip()
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return story
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def convert_text_to_audio(text_content, audio_path="output.mp3"):
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"""
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将文本转换为音频文件。
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"""
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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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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()
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