Create app.py
Browse files
app.py
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import streamlit as st
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from transformers import AutoProcessor, AutoModelForCausalLM
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from PIL import Image
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import torch
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# 设置模型和处理器
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model_id = "OpenFace-CQUPT/Human_LLaVA"
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processor = AutoProcessor.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id).to("cuda" if torch.cuda.is_available() else "cpu")
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# Streamlit 界面设置
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st.title("Visual Question Answering App")
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st.write("Upload an image and ask a question about it!")
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# 图片上传
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uploaded_image = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
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question = st.text_input("Ask a question about the image:")
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# 处理输入并获取答案
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if uploaded_image is not None and question:
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image = Image.open(uploaded_image)
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# 显示图片和问题
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st.image(image, caption="Uploaded Image", use_column_width=True)
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st.write("Question:", question)
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# 使用模型生成答案
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with st.spinner("Generating answer..."):
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inputs = processor(images=image, text=question, return_tensors="pt").to("cuda" if torch.cuda.is_available() else "cpu")
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with torch.no_grad():
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output = model.generate(**inputs)
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answer = processor.decode(output[0], skip_special_tokens=True)
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# 显示答案
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st.write("Answer:", answer)
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