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README.md
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license: mit
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---
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---
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license: mit
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---
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# Conditional ViT - B/16 - Categories
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- Introduced in [Weakly-Supervised Conditional Embedding for Referred Visual Search](https://arxiv.org/abs/2306.02928)
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- [Training Data](https://huggingface.co/datasets/Slep/LAION-RVS-Fashion)
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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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## General Infos
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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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Research use only.
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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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model = AutoModel.from_pretrained("Slep/CondViT-B16-cat")
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processor = AutoProcessor.from_pretrained("Slep/CondViT-B16-cat")
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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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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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```
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