Create app.py

streamlit
torch
transformers
pillow

app.py

@@ -0,0 +1,35 @@
+import streamlit as st
+from transformers import AutoProcessor, AutoModelForCausalLM
+from PIL import Image
+import torch
+
+# 设置模型和处理器
+model_id = "OpenFace-CQUPT/Human_LLaVA"
+processor = AutoProcessor.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id).to("cuda" if torch.cuda.is_available() else "cpu")
+
+# Streamlit 界面设置
+st.title("Visual Question Answering App")
+st.write("Upload an image and ask a question about it!")
+
+# 图片上传
+uploaded_image = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+question = st.text_input("Ask a question about the image:")
+
+# 处理输入并获取答案
+if uploaded_image is not None and question:
+    image = Image.open(uploaded_image)
+
+    # 显示图片和问题
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+    st.write("Question:", question)
+
+    # 使用模型生成答案
+    with st.spinner("Generating answer..."):
+        inputs = processor(images=image, text=question, return_tensors="pt").to("cuda" if torch.cuda.is_available() else "cpu")
+        with torch.no_grad():
+            output = model.generate(**inputs)
+        answer = processor.decode(output[0], skip_special_tokens=True)
+
+    # 显示答案
+    st.write("Answer:", answer)