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Introducing the scores to the outputs #301

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7226e5e
introducing the calculation of confidences in the output
matteocacciola May 15, 2024
628e16a
update README
matteocacciola May 15, 2024
7bff758
minor changes
matteocacciola May 15, 2024
9fd5e1b
cumulative changes (#1)
matteocacciola May 15, 2024
5c12dc1
Update setup.py
matteocacciola May 20, 2024
b2f94e0
removing opencv from dependencies
matteocacciola May 21, 2024
8ca41d1
improving the model and adding a temporary print
matteocacciola May 22, 2024
fdb5e5d
improvements
matteocacciola May 27, 2024
7628c2b
updating the setup
matteocacciola May 30, 2024
541fa5a
Update train.py
matteocacciola Jun 10, 2024
6827417
including https://github.com/clovaai/donut/pull/268
matteocacciola Jul 11, 2024
106e92a
including changes in the util
matteocacciola Jul 11, 2024
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3 changes: 3 additions & 0 deletions .gitignore
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Expand Up @@ -137,3 +137,6 @@ dmypy.json

# Pyre type checker
.pyre/

.idea
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15 changes: 9 additions & 6 deletions README.md
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Expand Up @@ -34,12 +34,12 @@ Gradio web demos are available! [![Demo](https://img.shields.io/badge/Demo-Gradi
- Web demos are available from the links in the following table.
- Note: We have updated the Google Colab demo (as of June 15, 2023) to ensure its proper working.

|Task|Sec/Img|Score|Trained Model|<div id="demo">Demo</div>|
|---|---|---|---|---|
| [CORD](https://github.com/clovaai/cord) (Document Parsing) | 0.7 /<br> 0.7 /<br> 1.2 | 91.3 /<br> 91.1 /<br> 90.9 | [donut-base-finetuned-cord-v2](https://huggingface.co/naver-clova-ix/donut-base-finetuned-cord-v2/tree/official) (1280) /<br> [donut-base-finetuned-cord-v1](https://huggingface.co/naver-clova-ix/donut-base-finetuned-cord-v1/tree/official) (1280) /<br> [donut-base-finetuned-cord-v1-2560](https://huggingface.co/naver-clova-ix/donut-base-finetuned-cord-v1-2560/tree/official) | [gradio space web demo](https://huggingface.co/spaces/naver-clova-ix/donut-base-finetuned-cord-v2),<br>[google colab demo (updated at 23.06.15)](https://colab.research.google.com/drive/1NMSqoIZ_l39wyRD7yVjw2FIuU2aglzJi?usp=sharing) |
| [Train Ticket](https://github.com/beacandler/EATEN) (Document Parsing) | 0.6 | 98.7 | [donut-base-finetuned-zhtrainticket](https://huggingface.co/naver-clova-ix/donut-base-finetuned-zhtrainticket/tree/official) | [google colab demo (updated at 23.06.15)](https://colab.research.google.com/drive/1YJBjllahdqNktXaBlq5ugPh1BCm8OsxI?usp=sharing) |
| [RVL-CDIP](https://www.cs.cmu.edu/~aharley/rvl-cdip) (Document Classification) | 0.75 | 95.3 | [donut-base-finetuned-rvlcdip](https://huggingface.co/naver-clova-ix/donut-base-finetuned-rvlcdip/tree/official) | [gradio space web demo](https://huggingface.co/spaces/nielsr/donut-rvlcdip),<br>[google colab demo (updated at 23.06.15)](https://colab.research.google.com/drive/1iWOZHvao1W5xva53upcri5V6oaWT-P0O?usp=sharing) |
| [DocVQA Task1](https://rrc.cvc.uab.es/?ch=17) (Document VQA) | 0.78 | 67.5 | [donut-base-finetuned-docvqa](https://huggingface.co/naver-clova-ix/donut-base-finetuned-docvqa/tree/official) | [gradio space web demo](https://huggingface.co/spaces/nielsr/donut-docvqa),<br>[google colab demo (updated at 23.06.15)](https://colab.research.google.com/drive/1oKieslZCulFiquequ62eMGc-ZWgay4X3?usp=sharing) |
| Task | Sec/Img | Score | Trained Model | <div id="demo">Demo</div> |
|--------------------------------------------------------------------------------|-------------------------|----------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| [CORD](https://github.com/clovaai/cord) (Document Parsing) | 0.7 /<br> 0.7 /<br> 1.2 | 91.3 /<br> 91.1 /<br> 90.9 | [donut-base-finetuned-cord-v2](https://huggingface.co/naver-clova-ix/donut-base-finetuned-cord-v2/tree/official) (1280) /<br> [donut-base-finetuned-cord-v1](https://huggingface.co/naver-clova-ix/donut-base-finetuned-cord-v1/tree/official) (1280) /<br> [donut-base-finetuned-cord-v1-2560](https://huggingface.co/naver-clova-ix/donut-base-finetuned-cord-v1-2560/tree/official) | [gradio space web demo](https://huggingface.co/spaces/naver-clova-ix/donut-base-finetuned-cord-v2),<br>[google colab demo (updated at 23.06.15)](https://colab.research.google.com/drive/1NMSqoIZ_l39wyRD7yVjw2FIuU2aglzJi?usp=sharing) |
| [Train Ticket](https://github.com/beacandler/EATEN) (Document Parsing) | 0.6 | 98.7 | [donut-base-finetuned-zhtrainticket](https://huggingface.co/naver-clova-ix/donut-base-finetuned-zhtrainticket/tree/official) | [google colab demo (updated at 23.06.15)](https://colab.research.google.com/drive/1YJBjllahdqNktXaBlq5ugPh1BCm8OsxI?usp=sharing) |
| [RVL-CDIP](https://www.cs.cmu.edu/~aharley/rvl-cdip) (Document Classification) | 0.75 | 95.3 | [donut-base-finetuned-rvlcdip](https://huggingface.co/naver-clova-ix/donut-base-finetuned-rvlcdip/tree/official) | [gradio space web demo](https://huggingface.co/spaces/nielsr/donut-rvlcdip),<br>[google colab demo (updated at 23.06.15)](https://colab.research.google.com/drive/1iWOZHvao1W5xva53upcri5V6oaWT-P0O?usp=sharing) |
| [DocVQA Task1](https://rrc.cvc.uab.es/?ch=17) (Document VQA) | 0.78 | 67.5 | [donut-base-finetuned-docvqa](https://huggingface.co/naver-clova-ix/donut-base-finetuned-docvqa/tree/official) | [gradio space web demo](https://huggingface.co/spaces/nielsr/donut-docvqa),<br>[google colab demo (updated at 23.06.15)](https://colab.research.google.com/drive/1oKieslZCulFiquequ62eMGc-ZWgay4X3?usp=sharing) |

The links to the pre-trained backbones are here:
- [`donut-base`](https://huggingface.co/naver-clova-ix/donut-base/tree/official): trained with 64 A100 GPUs (~2.5 days), number of layers (encoder: {2,2,14,2}, decoder: 4), input size 2560x1920, swin window size 10, IIT-CDIP (11M) and SynthDoG (English, Chinese, Japanese, Korean, 0.5M x 4).
Expand All @@ -62,6 +62,9 @@ To generate synthetic datasets with our SynthDoG, please see `./synthdog/README.

## Updates

**_2024-05-15_** We have introduced the opportunity to retrieve the scores with the extracted items with the usual
`DonutModel`. The `inference` method has the `return_confs` to return the scores of the predicted items. The parameter
is set to `True` by default. If you don't want the scores, please set `return_confs` to `False`.<br>
**_2023-06-15_** We have updated all Google Colab demos to ensure its proper working.<br>
**_2022-11-14_** New version 1.0.9 is released (`pip install donut-python --upgrade`). See [1.0.9 Release Notes](https://github.com/clovaai/donut/releases/tag/1.0.9).<br>
**_2022-08-12_** Donut 🍩 is also available at [huggingface/transformers 🤗](https://huggingface.co/docs/transformers/main/en/model_doc/donut) (contributed by [@NielsRogge](https://github.com/NielsRogge)). `donut-python` loads the pre-trained weights from the `official` branch of the model repositories. See [1.0.5 Release Notes](https://github.com/clovaai/donut/releases/tag/1.0.5).<br>
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