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README.md
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# Digital Peter
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## Description
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Digital Peter is an educational task with a historical slant created on the basis of several AI technologies (Computer Vision, NLP, and knowledge graphs). The task was prepared jointly with the Saint Petersburg Institute of History (N.P.Lihachov mansion) of Russian Academy of Sciences, Federal Archival Agency of Russia and Russian State Archive of Ancient Acts.
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A detailed description of the problem (with an immersion in the problem) can be found in [detailed_description_of_the_task_en.pdf
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The dataset consists of 662 full page images and 9696 annotated text files. There are 265788 symbols and approximately 50998 words.
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<p align="center">
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<img src="pics/counts_hor.png" width="80%">
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</p>
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Here is an example of one line of text.
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<p align="center">
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<img src="pics/one_line.jpg" width="70%">
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</p>
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Here is an example of segmented document.
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<p align="center">
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<img src="pics/line_label.jpeg" width="60%">
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</p>
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## Annotation format
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The annotation is in COCO format. The `annotation.json` should have the following dictionaries:
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## Competition
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We held a competition based on Digital Peter dataset.
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Here is github [link](https://github.com/sberbank-ai/digital_peter_aij2020). Here is competition [page](https://ods.ai/tracks/aij2020) (need to register).
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Here is the final leaderboard for this competition. Scores are presented for the private set.
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<p align="center">
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<img src="pics/leaderboard.jpeg" width="70%">
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</p>
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# Digital Peter
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The Peter dataset can be used for reading texts from the manuscripts written by Peter the Great. The dataset annotation contain end-to-end markup for training detection and OCR models, as well as an end-to-end model for reading text from pages.
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Paper is available at http://arxiv.org/abs/2103.09354
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## Description
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Digital Peter is an educational task with a historical slant created on the basis of several AI technologies (Computer Vision, NLP, and knowledge graphs). The task was prepared jointly with the Saint Petersburg Institute of History (N.P.Lihachov mansion) of Russian Academy of Sciences, Federal Archival Agency of Russia and Russian State Archive of Ancient Acts.
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A detailed description of the problem (with an immersion in the problem) can be found in [detailed_description_of_the_task_en.pdf](https://github.com/sberbank-ai/digital_peter_aij2020/blob/master/desc/detailed_description_of_the_task_en.pdf)
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The dataset consists of 662 full page images and 9696 annotated text files. There are 265788 symbols and approximately 50998 words.
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## Annotation format
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The annotation is in COCO format. The `annotation.json` should have the following dictionaries:
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## Competition
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We held a competition based on Digital Peter dataset.
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Here is github [link](https://github.com/sberbank-ai/digital_peter_aij2020). Here is competition [page](https://ods.ai/tracks/aij2020) (need to register).
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