HTRMoPo is a schema and an implementation for an automatic text recognition model repository hosted on the Zenodo research data infrastructure. It is designed to enable discoverability of models across a wide number of software and ATR-related tasks and aid in model selection.
There are two versions of the schema: v0 and v1. v0 is the legacy kraken
model schema for the Zenodo repository that is fairly limited, in particular by
not supporting non-recognition models and providing limited ways of
incorporating model cards. v1 is intended for all kinds of machine learning
models involved in ATR independent of software.
v0 is conserved for historical interest mostly. Records in v0 format consist of a JSON metadata file and at most a single model file that is referenced in it.
Repository records following the v1 schema consist of a Markdown model card with a YAML metadata front matter and an arbitrary number of files in the record. There is an example for the model card that is inspired by the huggingface example template but in principle model cards are free form. The front matter can be validated against a JSON schema found here.
Install the python library and prepare a model card for your ATR model, no matter of segmentation, recognition, reading order, postcorrection, .... Afterwards you need to create an account on Zenodo and create an API access token as described here.
With the HTRMoPo reference implementation and the access token you can then create model deposits on Zenodo. Deposits will be immediately accessible to the whole world but won't be discoverable until the community inclusion request is manually approved by one of the repository administrators.
Using a research data infrastructure like Zenodo assures long-term accessibility of the deposited models while also enabling good scientific practices like reproducibility and crediting contributions.
Each model in the repository consists of the model card with metadata and one or more model files and is identified by two persistent and unique DOIs. One of the DOIs refers to the deposit, which means a single model, itself while the second one is called the concept DOI. An example is 10.5281/zenodo.7051646 with concept DOI 10.5281/zenodo.7051645. When a new version of a model is updated to the repository a new DOI is created, for example 10.5281/zenodo.14585602 for the above model but the concept DOI remains the same, aggregating all versions of a model under a single identifier. The concept DOI therefore aggregates all versions of the model and in addition will always link to the latest version of it.
A reference implementation to interact with the repository on Zenodo is in the htrmopo directory, containing both a python library and command line drivers.
The library can be installed using pip:
~> pip install htrmopo
The htrmopo command line tool is used to query the repository, download
existing models, and upload and update items to it.
To get a listing of all models:
~> htrmopo list
Retrieving model list ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ DOI ┃ summary ┃ model type ┃ keywords ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ 10.5281/zenodo.7547437 │ │ │ │
│ ├── 10.5281/zenodo.10800223 │ HTR model for documentary Latin, Old French and Spanish medieval manuscripts (11th-16th) │ recognition │ Handwritten text recognition; Handwritten text recognition for Medieval manuscripts; Digital Paleography │
│ └── 10.5281/zenodo.7547438 │ HTR model for documentary Latin and Old French medieval manuscripts (12th-15th) │ recognition │ Handwritten text recognition; Handwritten text recognition for Medieval manuscripts; Digital Paleography │
│ 10.5281/zenodo.7050269 │ │ │ │
│ └── 10.5281/zenodo.7050270 │ Printed Arabic-Script Base Model Trained on the OpenITI Corpus │ recognition │ kraken_pytorch │
│ 10.5281/zenodo.6542743 │ │ │ │
│ └── 10.5281/zenodo.6542744 │ LECTAUREP Contemporary French Model (Administration) │ recognition │ kraken_pytorch; HTR; transcription model; recognition model; French; Contemporary French │
│ 10.5281/zenodo.13814199 │ │ │ │
│ └── 10.5281/zenodo.13814200 │ Segmentation model for historical Samaritan Manuscripts for one column pages, model trained on 13 pentateuchal Samaritan manuscripts │ recognition │ kraken_pytorch │
│ 10.5281/zenodo.6891851 │ │ │ │
│ ├── 10.5281/zenodo.7933402 │ Fraktur model trained from enhanced Austrian Newspapers dataset │ recognition │ kraken_pytorch; Fraktur; Latin │
│ └── 10.5281/zenodo.6891852 │ Fraktur model trained from enhanced Austrian Newspapers dataset │ recognition │ kraken_pytorch │
│ 10.5281/zenodo.8193497 │ │ │ │
│ └── 10.5281/zenodo.8193498 │ Transcription model for Lucien Peraire's handwriting (French, 20th century) │ recognition │ kraken_pytorch; HTR; Peraire; Manu McFrench; contemporary handwriting; French │
│ 10.5281/zenodo.5468664 │ │ │ │
│ └── 10.5281/zenodo.5468665 │ Medieval Hebrew manuscripts in Sephardi bookhand version 1.0 │ recognition │ kraken_pytorch │
│ 10.5281/zenodo.10592715 │ │ │ │
│ └── 10.5281/zenodo.10592716 │ CATMuS-Print (Large, 2024-01-30) - Diachronic model for French prints and other languages │ recognition │ kraken_pytorch; optical text recognition │
│ 10.5281/zenodo.7051645 │ │ │ │
│ ├── 10.5281/zenodo.14585602 │ Printed Urdu Base Model Trained on the OpenITI Corpus │ recognition │ automatic-text-recognition │
│ ├── 10.5281/zenodo.14574660 │ Printed Urdu Base Model Trained on the OpenITI Corpus │ recognition │ kraken_pytorch │
│ └── 10.5281/zenodo.7051646 │ Printed Urdu Base Model Trained on the OpenITI Corpus │ recognition │ kraken_pytorch │
│ 10.5281/zenodo.5468285 │ │ │ │
│ └── 10.5281/zenodo.5468286 │ Medieval Hebrew manuscripts version 1.0 │ recognition │ kraken_pytorch │
│ 10.5281/zenodo.6657808 │ │ │ │
│ ├── 10.5281/zenodo.10886224 │ Model train on openly licensed data from HTR-United from the 17th century to the 21st were used. │ recognition │ kraken_pytorch │
│ ├── 10.5281/zenodo.6657809 │ Model train on openly licensed data from HTR-United. All French manuscript data from the 17th century to the 21st were used (72k lines). │ recognition │ kraken_pytorch │
│ └── 10.5281/zenodo.10874058 │ Model train on openly licensed data from HTR-United. All French manuscript data from the 17th century to the 21st were used. │ recognition │ kraken_pytorch │
│ 10.5281/zenodo.7234165 │ │ │ │
....
Records are represented in a tree structure in the left-most column. The DOI at the root of each tree is a concept DOI which always links to the most recent version of a model. The leaves of the tree are particular versions of the record ordered chronologically. Either type of DOI is acceptable as arguments for the functions below although it is recommended to reference a concrete version in contexts where reproducibility is desired.
To fetch the metadata for a single model (both v0 and v1 schema):
~> htrmopo show 10.5281/zenodo.10800223
HTR model for documentary Latin, Old French and Spanish medieval manuscripts (11th-16th)
┌──────────────────┬──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
│ DOI │ 10.5281/zenodo.10800223 │
│ concept DOI │ 10.5281/zenodo.7547437 │
│ publication date │ 2024-03-14T01:47:02+00:00 │
│ model type │ recognition │
│ script │ Latin │
│ alphabet │ ! " # $ % & ' ( ) * + , - . / 0 1 2 3 4 5 6 7 8 9 : ; = > ? @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z [ \ ] ^ _ a b c d e f g h i j k l m n o p │
│ │ q r s t u v w x y z { | } ~ ¡ £ § ª « ¬ ° ¶ º » ½ ¾ À Ä Ç È É Ë Ï Û Ü à á â ä æ ç è é ê ë ì í î ï ñ ò ó ô ö ù ú û ü ÿ ā ă ē ĕ ę ī ō ŏ œ ŭ ƒ ȩ ˀ ο а е о с ᗅ │
│ │ – — ‘ ’ ” „ † … ⁖ ₎ 〈 〉 ✳ ꝫ │
│ │ 0x9, SPACE, 0x92, 0x97, NO-BREAK SPACE, COMBINING MACRON, COMBINING LATIN SMALL LETTER A, COMBINING LATIN SMALL LETTER E, COMBINING LATIN SMALL LETTER O, │
│ │ COMBINING LATIN SMALL LETTER U, COMBINING LATIN SMALL LETTER C, WORD JOINER, 0xf2f7 │
│ keywords │ Handwritten text recognition │
│ │ Handwritten text recognition for Medieval manuscripts │
│ │ Digital Paleography │
│ metrics │ cer: 7.82 │
│ license │ MIT │
│ creators │ Torres Aguilar, Sergio (https://orcid.org/0000-0002-1801-3147) (University of Luxembourg) │
│ │ Jolivet, Vincent (École nationale des chartes) │
│ │ Sergio Torres Aguilar (University of Luxembourg) │
│ description │ The model was trained on diplomatic transcriptions of documentary manuscripts from the Late-medieval period (12-15th) and early modernity (16th). The │
│ │ training and evaluation sets entail 215k lines and 2.4M of tokens using open source corpora. │
│ │ │
└──────────────────┴──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘
Downloading a single model:
~> htrmopo get 10.5281/zenodo.7547437
Processing ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00
Model name: /home/mittagessen/.local/share/htrmopo/0ac39ba5-8f85-5ea1-913a-f84a13ca756f
Models are placed per default in reproducible locations in the application
state dir printed after the download is finished. The -o option allows
customization of that behavior:
~> htrmopo get -o manu 10.5281/zenodo.7547437
Processing ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00
Model name: /home/mittagessen/manu
There are two modes of publishing ATR models with the htrmopo command. The
first creates new stand-alone deposits while the second one creates a new
version of an existing record that will all be grouped under the same concept
DOI. Updating a model deposit is usually done when a prior model is retrained
with additional training data, the metadata has been refined, or additional
evaluation has been done.
The calls for both modes are very similar, the only difference being -d
option giving the DOI of an existing model deposit in the repository:
~> htrmopo publish -i model_card.md -a ${ACCESS_TOKEN} model_dir
Uploading ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00
model PID: 10.5072/zenodo.146629
~> htrmopo publish -d 10.5072/zenodo.146502 -i model_card.md -a ${ACCESS_TOKEN} model_dir
Uploading ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00
model PID: 10.5072/zenodo.146627
The tool is intended to work out of the box but sometimes it can be useful for testing purposes to point it to another instance of InvenioDRM such as the Zenodo sandbox in order not to pollute the main repository with spurious deposits.
You can set the OAI-PMH API endpoint (required for querying) and InvenioDRM
endpoint (needed for querying and publishing) with the MODEL_REPO_OAI_URL and
MODEL_REPO_URL environments, for example:
MODEL_REPO_URL=https://sandbox.zenodo.org/api/ htrmopo publish -i model_card.md -a ....
will upload a model to the sandbox instance of Zenodo.