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Create app.py
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app.py
ADDED
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# storygen_tts_final.py
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import streamlit as st
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from transformers import (
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BlipForConditionalGeneration,
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BlipProcessor,
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AutoProcessor,
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SpeechT5ForTextToSpeech,
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SpeechT5HifiGan,
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pipeline
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)
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from datasets import load_dataset
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import torch
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import numpy as np
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from PIL import Image
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# 初始化模型(CPU优化版)
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@st.cache_resource
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def load_models():
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"""加载所有需要的AI模型"""
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try:
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# 图像描述模型
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blip_processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
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blip_model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
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# 文本生成pipeline
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story_generator = pipeline(
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"text-generation",
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model="openai-community/gpt2",
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device_map="auto"
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)
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# 语音合成模型
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tts_processor = AutoProcessor.from_pretrained("microsoft/speecht5_tts")
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tts_model = SpeechT5ForTextToSpeech.from_pretrained("microsoft/speecht5_tts")
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vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan")
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# 加载说话者嵌入数据集
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embeddings_dataset = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation")
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return blip_processor, blip_model, story_generator, tts_processor, tts_model, vocoder, embeddings_dataset
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except Exception as e:
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st.error(f"模型加载失败: {str(e)}")
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raise
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def generate_story(image, blip_processor, blip_model, story_generator):
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"""生成高质量儿童故事"""
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inputs = blip_processor(image, return_tensors="pt")
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# 生成图像描述
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caption_ids = blip_model.generate(
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**inputs,
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max_new_tokens=100,
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num_beams=5,
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early_stopping=True,
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temperature=0.9
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)
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caption = blip_processor.decode(caption_ids[0], skip_special_tokens=True)
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# 构建故事生成提示词
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prompt = f"""Based on this image: {caption}
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Write a magical story for children with:
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1. Talking animals
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2. Happy ending
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3. Sound effects (*whoosh*, *giggle*)
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4. 50-100 words
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Story:"""
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# 使用GPT-2生成故事
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generated = story_generator(
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prompt,
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max_length=100,
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min_length=50,
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num_return_sequences=1,
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temperature=0.85,
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repetition_penalty=2.0
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)
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# 提取生成文本并清理
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full_text = generated[0]['generated_text']
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story = full_text.split("Story:")[-1].strip()
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return story[:600].replace(caption, "").strip()
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def text_to_speech(text, processor, model, vocoder, embeddings_dataset):
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"""文本转语音"""
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try:
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inputs = processor(
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text=text,
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return_tensors="pt",
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voice_preset=None
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)
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input_ids = inputs["input_ids"].to(torch.int64)
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# 随机选择一个说话者嵌入
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speaker_embeddings = torch.tensor(embeddings_dataset[7306]["xvector"]).unsqueeze(0)
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with torch.no_grad():
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speech = model.generate_speech(
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input_ids=input_ids,
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speaker_embeddings=speaker_embeddings,
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vocoder=vocoder
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)
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audio_array = speech.numpy()
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audio_array = audio_array / np.max(np.abs(audio_array))
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return audio_array, 16000
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except Exception as e:
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st.error(f"语音生成失败: {str(e)}")
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raise
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def main():
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# 界面配置
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st.set_page_config(
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page_title="Magic Story Box",
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page_icon="🧙",
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layout="centered"
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)
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st.title("🧚♀️ Magic Story Box")
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st.markdown("---")
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st.write("Upload an image to get your magical story!")
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# 初始化会话状态
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if 'generated' not in st.session_state:
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st.session_state.generated = False
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# 加载模型
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try:
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(blip_proc, blip_model, story_gen,
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tts_proc, tts_model, vocoder, embeddings) = load_models()
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except:
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return
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# 文件上传组件
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uploaded_file = st.file_uploader(
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"Choose your magic image",
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type=["jpg", "png", "jpeg"],
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help="Upload photos of pets, toys or adventures!",
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key="uploader"
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)
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# 处理上传文件
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if uploaded_file and not st.session_state.generated:
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try:
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image = Image.open(uploaded_file).convert("RGB")
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st.image(image, caption="Your Magic Picture ✨", use_container_width=True)
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with st.status("Creating Magic...", expanded=True) as status:
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# 生成故事
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st.write("🔍 Reading the image...")
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story = generate_story(image, blip_proc, blip_model, story_gen)
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# 生成语音
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st.write("🔊 Adding sounds...")
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audio_array, sr = text_to_speech(story, tts_proc, tts_model, vocoder, embeddings)
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# 保存结果
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st.session_state.story = story
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st.session_state.audio = (audio_array, sr)
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status.update(label="Ready!", state="complete", expanded=False)
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st.session_state.generated = True
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st.rerun()
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except Exception as e:
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st.error(f"Magic failed: {str(e)}")
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# 显示结果
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if st.session_state.generated:
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st.markdown("---")
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st.subheader("Your Story 📖")
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st.markdown(f'<div style="background:#fff3e6; padding:20px; border-radius:10px;">{st.session_state.story}</div>',
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unsafe_allow_html=True)
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st.markdown("---")
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st.subheader("Listen 🎧")
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audio_data, sr = st.session_state.audio
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st.audio(audio_data, sample_rate=sr)
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st.markdown("---")
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if st.button("Create New Story", use_container_width=True):
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st.session_state.generated = False
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st.session_state.uploader = None
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st.rerun()
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if __name__ == "__main__":
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main()
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