| import streamlit as st |
| from transformers import BlipProcessor, BlipForConditionalGeneration |
| from PIL import Image |
| from gtts import gTTS |
| import tempfile |
| import os |
|
|
| |
| processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-large") |
| model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-large") |
|
|
| st.title("图像描述生成器") |
| st.write("使用摄像头拍照并生成图像的描述。") |
|
|
| |
| image_data = st.camera_input("请使用摄像头拍照") |
|
|
| if image_data is not None: |
| |
| image = Image.open(image_data) |
| |
| |
| st.image(image, caption="拍摄的图像", use_column_width=True) |
|
|
| |
| inputs = processor(image, return_tensors="pt") |
| out = model.generate(**inputs) |
| caption = processor.decode(out[0], skip_special_tokens=True) |
| |
| st.write(f"图像描述: {caption}") |
| |
| |
| tts = gTTS(text=caption, lang='en') |
| |
| |
| with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as fp: |
| tts.save(fp.name) |
| audio_file = fp.name |
| |
| |
| st.audio(audio_file) |
|
|
| |
| os.remove(audio_file) |
|
|
