import gradio as gr
from transformers import pipeline

# 选择 Hugging Face 预训练模型
classifier = pipeline("image-classification", model="microsoft/beit-base-patch16-224")

# 定义分类函数
def classify_image(image):
    predictions = classifier(image)
    return {pred["label"]: float(pred["score"]) for pred in predictions}

# 创建 Gradio 界面
demo = gr.Interface(fn=classify_image, inputs="image", outputs="label", title="Image Classification Demo")
demo.launch()