| import gradio as gr | |
| import asyncio | |
| from huggingface_hub import AsyncInferenceClient | |
| import os | |
| hf = os.getenv("HF") | |
| client = AsyncInferenceClient("google/siglip-base-patch16-224", token=hf) | |
| def image_classifier(inp): | |
| class_names = ["0", "1"] | |
| inp.save("why.png") | |
| sunflower_path = "why.png" | |
| hf = os.getenv("HF") | |
| r = asyncio.run(client.zero_shot_image_classification("why.png", candidate_labels=["mouth or teeth", "not mouth"])) | |
| c = {} | |
| a = r[0]["score"] + r[1]["score"] | |
| c[r[0]["label"]] = r[0]["score"] / a | |
| c[r[1]["label"]] = r[1]["score"] / a | |
| return c | |
| demo = gr.Interface(fn=image_classifier, inputs=gr.Image(type="pil"), outputs="label") | |
| demo.launch(debug=True) | |