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---
language:
- en
license: apache-2.0
tags:
- image-to-text
---
# PARSeq tiny v1.0
PARSeq model pre-trained on various real [STR datasets](https://github.com/baudm/parseq/blob/main/Datasets.md) at image size 128x32 with a patch size of 8x4.
## Model description
PARSeq (Permuted Autoregressive Sequence) models unify the prevailing modeling/decoding schemes in Scene Text Recognition (STR). In particular, with a single model, it allows for context-free non-autoregressive inference (like CRNN and ViTSTR), context-aware autoregressive inference (like TRBA), and bidirectional iterative refinement (like ABINet).
## Intended uses & limitations
You can use the model for STR on images containing Latin characters (62 case-sensitive alphanumeric + 32 punctuation marks).
### How to use
*TODO*
### BibTeX entry and citation info
```bibtex
@InProceedings{bautista2022parseq,
author={Bautista, Darwin and Atienza, Rowel},
title={Scene Text Recognition with Permuted Autoregressive Sequence Models},
booktitle={Proceedings of the 17th European Conference on Computer Vision (ECCV)},
month={10},
year={2022},
publisher={Springer International Publishing},
address={Cham}
}
```
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