| import gradio as gr | |
| from huggingface_hub import AsyncInferenceClient | |
| client = AsyncInferenceClient() | |
| def image_classifier(inp): | |
| class_names = ["0", "1"] | |
| inp.save("why.png") | |
| sunflower_path = "why.png" | |
| r = await client.zero_shot_image_classification("why.png", labels=["mouth", "other"]) | |
| return r | |
| demo = gr.Interface(fn=image_classifier, inputs=gr.Image(type="pil"), outputs="label") | |
| demo.launch(debug=True) | |