| import gradio as gr | |
| import asyncio | |
| from huggingface_hub import AsyncInferenceClient | |
| import os | |
| hf = os.getenv("HF") | |
| client = AsyncInferenceClient("openai/clip-vit-large-patch14", 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", "other"]), token=) | |
| c = {} | |
| c[r[0]["label"]] = r[0]["score"] | |
| c[r[1]["label"]] = 1 - r[0]["score"] | |
| return c | |
| demo = gr.Interface(fn=image_classifier, inputs=gr.Image(type="pil"), outputs="label") | |
| demo.launch(debug=True) | |