| import torch | |
| from PIL import Image | |
| import open_clip | |
| model, _, preprocess = open_clip.create_model_and_transforms("hf-hub:yyupenn/whylesionclip") | |
| model.eval() | |
| tokenizer = open_clip.get_tokenizer("ViT-L-14") | |
| image = preprocess(Image.open("test_skin.jpg")).unsqueeze(0) | |
| text = tokenizer(["dark brown", "bleeding", "irregular shape"]) | |
| with torch.no_grad(), torch.cuda.amp.autocast(): | |
| image_features = model.encode_image(image) | |
| text_features = model.encode_text(text) | |
| image_features /= image_features.norm(dim=-1, keepdim=True) | |
| text_features /= text_features.norm(dim=-1, keepdim=True) | |
| text_probs = (100.0 * image_features @ text_features.T).softmax(dim=-1) | |
| print("Label probs:", text_probs) |