readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - image-to-text
  ---
  
  # PARSeq small v1.0
  
  PARSeq model pre-trained on various real [STR datasets](https://github.com/baudm/parseq/blob/main/Datasets.md) at image size 224x224 with a patch size of 16x16.
  
  ## 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).
  
  ![model image](https://github.com/baudm/parseq/raw/main/.github/system.png)
  
  ## 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}
  }
  ```
  