metadata
license: mit
Conditional ViT - B/16 - Categories
Introduced in Weakly-Supervised Conditional Embedding for Referred Visual Search, Lepage et al. 2023
Paper | Training Data | Training Code | Demo
General Infos
Model finetuned from CLIP ViT-B/16 on LRVSF at 224x224. The conditioning categories are the following :
- Bags
- Feet
- Hands
- Head
- Lower Body
- Neck
- Outwear
- Upper Body
- Waist
- Whole Body
Research use only.
How to Use
from PIL import Image
import requests
from transformers import AutoProcessor, AutoModel
import torch
model = AutoModel.from_pretrained("Slep/CondViT-B16-cat")
processor = AutoProcessor.from_pretrained("Slep/CondViT-B16-cat")
url = "https://huggingface.co/datasets/Slep/LAION-RVS-Fashion/resolve/main/assets/108856.0.jpg"
img = Image.open(requests.get(url, stream=True).raw)
cat = "Bags"
inputs = processor(images=[img], categories=[cat])
raw_embedding = model(**inputs)
normalized_embedding = torch.nn.functional.normalize(raw_embedding, dim=-1)