import streamlit as st from transformers import pipeline from gtts import gTTS import io import os # function part # img2text def img2text(url): try: image_to_text_model = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base") text = image_to_text_model(url)[0]["generated_text"] return text except Exception as e: st.error(f"图像转文本出错: {e}") return None # text2story def text2story(text): try: story_generator = pipeline("text-generation", model="Qwen/QwQ-32B-Preview") # 生成故事文本 result = story_generator(text, max_length=200, num_return_sequences=1) story = result[0]['generated_text'] return story except Exception as e: st.error(f"文本生成故事出错: {e}") return None # text2audio def text2audio(story_text): try: # 创建 gTTS 对象,将文本转换为语音 tts = gTTS(text=story_text, lang='en') # 创建字节流对象用于存储音频数据 audio_file = io.BytesIO() # 将音频数据写入字节流 tts.write_to_fp(audio_file) # 移动文件指针到开头 audio_file.seek(0) return audio_file except Exception as e: st.error(f"文本转音频出错: {e}") return None st.set_page_config(page_title="Your Image to Audio Story", page_icon="🦜") st.header("Turn Your Image to Audio Story") uploaded_file = st.file_uploader("Select an Image...") if uploaded_file is not None: # 使用临时文件存储上传的图像 temp_file_path = "temp_image.jpg" bytes_data = uploaded_file.getvalue() with open(temp_file_path, "wb") as file: file.write(bytes_data) # 显示上传的图像,使用 use_container_width 避免弃用警告 st.image(uploaded_file, caption="Uploaded Image", use_container_width=True) # Stage 1: Image to Text st.text('Processing img2text...') scenario = img2text(temp_file_path) if scenario: st.write(scenario) # Stage 2: Text to Story st.text('Generating a story...') story = text2story(scenario) if story: st.write(story) # Stage 3: Story to Audio data st.text('Generating audio data...') audio_data = text2audio(story) if audio_data: # Play button if st.button("Play Audio"): st.audio(audio_data, format="audio/mpeg", start_time=0) # 删除临时文件 if os.path.exists(temp_file_path): os.remove(temp_file_path)