Create backup.txt

backup.txt

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+import streamlit as st
+from transformers import BlipProcessor, BlipForConditionalGeneration
+from PIL import Image
+
+# 加载BLIP模型和处理器
+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。")
+
+# 使用Streamlit的camera_input来获取用户摄像头输入
+image_data = st.camera_input("请使用摄像头拍照")
+
+if image_data is not None:
+    # 将图像数据转换为PIL图像
+    image = Image.open(image_data)
+    
+    # 显示拍摄的图像
+    st.image(image, caption="拍摄的图像", use_column_width=True)
+
+    # 生成图像描述
+    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}")