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---
license: cc-by-nc-4.0
model-index:
- name: CondViT-B16-txt
results:
- dataset:
name: LAION - Referred Visual Search - Fashion
split: test
type: Slep/LAION-RVS-Fashion
metrics:
- name: R@1 +10K Dist.
type: recall_at_1|10000
value: 94.18 ± 0.86
- name: R@5 +10K Dist.
type: recall_at_5|10000
value: 98.78 ± 0.32
- name: R@10 +10K Dist.
type: recall_at_10|10000
value: 99.25 ± 0.30
- name: R@20 +10K Dist.
type: recall_at_20|10000
value: 99.71 ± 0.17
- name: R@50 +10K Dist.
type: recall_at_50|10000
value: 99.79 ± 0.13
- name: R@1 +100K Dist.
type: recall_at_1|100000
value: 87.07 ± 1.30
- name: R@5 +100K Dist.
type: recall_at_5|100000
value: 95.28 ± 0.61
- name: R@10 +100K Dist.
type: recall_at_10|100000
value: 96.99 ± 0.44
- name: R@20 +100K Dist.
type: recall_at_20|100000
value: 98.04 ± 0.36
- name: R@50 +100K Dist.
type: recall_at_50|100000
value: 98.98 ± 0.26
- name: R@1 +500K Dist.
type: recall_at_1|500000
value: 79.41 ± 1.02
- name: R@5 +500K Dist.
type: recall_at_5|500000
value: 89.65 ± 1.08
- name: R@10 +500K Dist.
type: recall_at_10|500000
value: 92.72 ± 0.87
- name: R@20 +500K Dist.
type: recall_at_20|500000
value: 94.88 ± 0.58
- name: R@50 +500K Dist.
type: recall_at_50|500000
value: 97.13 ± 0.48
- name: R@1 +1M Dist.
type: recall_at_1|1000000
value: 75.60 ± 1.40
- name: R@5 +1M Dist.
type: recall_at_5|1000000
value: 86.62 ± 1.42
- name: R@10 +1M Dist.
type: recall_at_10|1000000
value: 90.13 ± 1.06
- name: R@20 +1M Dist.
type: recall_at_20|1000000
value: 92.82 ± 0.76
- name: R@50 +1M Dist.
type: recall_at_50|1000000
value: 95.61 ± 0.62
- name: Available Dists.
type: n_dists
value: 2000014
- name: Embedding Dimension
type: embedding_dim
value: 512
- name: Conditioning
type: conditioning
value: text
source:
name: LRVSF Leaderboard
url: https://huggingface.co/spaces/Slep/LRVSF-Leaderboard
task:
type: Retrieval
tags:
- lrvsf-benchmark
---
# Conditional ViT - B/16 - Text
*Introduced in **Weakly-Supervised Conditional Embedding for Referred Visual Search**, Lepage et al. 2023*
[`Paper`](https://arxiv.org/abs/2306.02928) | [`Training Data`](https://huggingface.co/datasets/Slep/LAION-RVS-Fashion) | [`Training Code`](https://github.com/Simon-Lepage/CondViT-LRVSF) | [`Demo`](https://huggingface.co/spaces/Slep/CondViT-LRVSF-Demo)
## General Infos
Model finetuned from CLIP ViT-B/16 on LRVSF at 224x224. The conditioning text is preprocessed by a frozen [Sentence T5-XL](https://huggingface.co/sentence-transformers/sentence-t5-xl).
Research use only.
## How to Use
```python
from PIL import Image
import requests
from transformers import AutoProcessor, AutoModel
import torch
model = AutoModel.from_pretrained("Slep/CondViT-B16-txt")
processor = AutoProcessor.from_pretrained("Slep/CondViT-B16-txt")
url = "https://huggingface.co/datasets/Slep/LAION-RVS-Fashion/resolve/main/assets/108856.0.jpg"
img = Image.open(requests.get(url, stream=True).raw)
txt = "a brown bag"
inputs = processor(images=[img], texts=[txt])
raw_embedding = model(**inputs)
normalized_embedding = torch.nn.functional.normalize(raw_embedding, dim=-1)
``` |