dermora-dinov2-vit-b-skin

from PIL import Image

images = [
    Image.open("sample1.jpg").convert("RGB"),
    Image.open("sample2.jpg").convert("RGB"),
    Image.open("sample3.jpg").convert("RGB"),
]

inputs = processor(images=images, return_tensors="pt")

with torch.no_grad():
    outputs = model(**inputs)

predicted_classes = outputs.logits.argmax(-1).tolist()
for idx, pred in enumerate(predicted_classes):
    print(f"Image {idx + 1}: {model.config.id2label[pred]}")

from transformers import AutoModel

feature_extractor = AutoModel.from_pretrained(
    "rachitgoyell/dermora-dinov2-vit-b-skin"
)

with torch.no_grad():
    features = feature_extractor(**inputs)

cls_embedding = features.last_hidden_state[:, 0, :]  # CLS token
print("Feature shape:", cls_embedding.shape)  # (batch, 768)