
# 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 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).

![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}
}
```

{"language": ["en"], "license": "apache-2.0", "tags": ["image-to-text"]}
pytorch image-to-text en license:apache-2.0 region:us
TAGS
#pytorch #image-to-text #en #license-apache-2.0 #region-us 


# PARSeq small v1.0

PARSeq model pre-trained on various real STR datasets 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).

!model image

## 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



# PARSeq small v1.0

PARSeq model pre-trained on various real STR datasets 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).

!model image ## 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
TAGS
#pytorch #image-to-text #en #license-apache-2.0 #region-us 
 # PARSeq small v1.0

PARSeq model pre-trained on various real STR datasets 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).

!model image ## 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
passage: TAGS
#pytorch #image-to-text #en #license-apache-2.0 #region-us 
# PARSeq small v1.0

PARSeq model pre-trained on various real STR datasets 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).

!model image## 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