Styleid

--- license: other library_name: transformers --- # StyleID — Stylization-Agnostic Identity Encoder [](https://arxiv.org/abs/2604.21689) [](https://kwanyun.github.io/StyleID_page/) StyleID is a CLIP-based image encoder trained to produce identity embeddings that are robust to stylization. It can be used for identity similarity, retrieval, evaluation, and conditioning in generative models. <img src="https://cdn-uploads.huggingface.co/production/uploads/639d445524af4747d8d2af52/1pTEZ88YvwnbDPlV_UqpM.jpeg" width="700"> --- ## Installation ```bash pip install pillow pip install transformers==4.52.0 ``` ## Usage #### Do not use for multiple faces or faces too small to recognize. ``` import torch from transformers import CLIPModel, CLIPProcessor from PIL import Image device = "cuda" if torch.cuda.is_available() else "cpu" model = CLIPModel.from_pretrained("kwanY/styleid").to(device) processor = CLIPProcessor.from_pretrained("kwanY/styleid") img = Image.open(img_path).convert("RGB") inputs = processor(images=img, return_tensors="pt").to(device) with torch.no_grad(): emb = model.get_image_features(**inputs) emb = emb / emb.norm(dim=-1, keepdim=True) ``` #### Open for non-commercial research. Do not use FFHQ for biometric human recognition

Source context: 817 downloads · 6 likes · Pipeline zero-shot-image-classification · Library transformers · Repo kwanY/styleid