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  license: mit
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  license: mit
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+ # Conditional ViT - B/16 - Categories
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+
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+ - Introduced in [Weakly-Supervised Conditional Embedding for Referred Visual Search](https://arxiv.org/abs/2306.02928)
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+
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+ - [Training Data](https://huggingface.co/datasets/Slep/LAION-RVS-Fashion)
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+
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+ - [Training Code](https://github.com/Simon-Lepage/CondViT-LRVSF)
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+ - [Demo](https://huggingface.co/spaces/Slep/CondViT-LRVSF-Demo)
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+
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+ ## General Infos
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+
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+ Model finetuned from CLIP ViT-B/16 on LRVSF at 224x224. The conditioning categories are the following :
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+ - Bags
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+ - Feet
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+ - Hands
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+ - Head
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+ - Lower Body
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+ - Neck
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+ - Outwear
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+ - Upper Body
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+ - Waist
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+ - Whole Body
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+
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+ Research use only.
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+
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+ ## How to Use
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+ ```python
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+ from PIL import Image
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+ import requests
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+ from transformers import AutoProcessor, AutoModel
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+ import torch
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+
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+ model = AutoModel.from_pretrained("Slep/CondViT-B16-cat")
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+ processor = AutoProcessor.from_pretrained("Slep/CondViT-B16-cat")
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+
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+ url = "https://huggingface.co/datasets/Slep/LAION-RVS-Fashion/resolve/main/assets/108856.0.jpg"
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+ img = Image.open(requests.get(url, stream=True).raw)
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+ cat = "Bags"
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+
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+ inputs = processor(images=[img], categories=[cat])
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+ raw_embedding = model(**inputs)
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+ normalized_embedding = torch.nn.functional.normalize(raw_embedding, dim=-1)
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+ ```