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import streamlit as st |
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from transformers import pipeline |
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from gtts import gTTS |
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import io |
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import os |
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def img2text(url): |
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try: |
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image_to_text_model = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base") |
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text = image_to_text_model(url)[0]["generated_text"] |
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return text |
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except Exception as e: |
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st.error(f"图像转文本出错: {e}") |
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return None |
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def text2story(text): |
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try: |
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story_generator = pipeline("text-generation", model="Qwen/QwQ-32B-Preview") |
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result = story_generator(text, max_length=200, num_return_sequences=1) |
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story = result[0]['generated_text'] |
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return story |
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except Exception as e: |
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st.error(f"文本生成故事出错: {e}") |
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return None |
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def text2audio(story_text): |
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try: |
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tts = gTTS(text=story_text, lang='en') |
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audio_file = io.BytesIO() |
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tts.write_to_fp(audio_file) |
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audio_file.seek(0) |
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return audio_file |
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except Exception as e: |
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st.error(f"文本转音频出错: {e}") |
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return None |
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st.set_page_config(page_title="Your Image to Audio Story", |
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page_icon="🦜") |
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st.header("Turn Your Image to Audio Story") |
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uploaded_file = st.file_uploader("Select an Image...") |
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if uploaded_file is not None: |
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temp_file_path = "temp_image.jpg" |
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bytes_data = uploaded_file.getvalue() |
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with open(temp_file_path, "wb") as file: |
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file.write(bytes_data) |
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st.image(uploaded_file, caption="Uploaded Image", use_container_width=True) |
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st.text('Processing img2text...') |
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scenario = img2text(temp_file_path) |
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if scenario: |
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st.write(scenario) |
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st.text('Generating a story...') |
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story = text2story(scenario) |
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if story: |
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st.write(story) |
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st.text('Generating audio data...') |
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audio_data = text2audio(story) |
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if audio_data: |
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if st.button("Play Audio"): |
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st.audio(audio_data, format="audio/mpeg", start_time=0) |
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if os.path.exists(temp_file_path): |
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os.remove(temp_file_path) |