StyleID — Stylization-Agnostic Identity Encoder

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.

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Installation

pip install transformers pillow

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)  # optional but recommended

Open for non-commercial research. Do not use FFHQ for biometric human recognition