| 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() | |