Code Monkey home page Code Monkey logo

core's Introduction

OCR-D/core

Python modules implementing OCR-D specs and related tools

image Docker Image CI Unit Test CI image image image

Gitter chat

Introduction

This repository contains the python packages that form the base for tools within the OCR-D ecosphere.

All packages are also published to PyPI.

Installation

NOTE Unless you want to contribute to OCR-D/core, we recommend installation as part of ocrd_all which installs a complete stack of OCR-D-related software.

The easiest way to install is via pip:

pip install ocrd

# or just the functionality you need, e.g.

pip install ocrd_modelfactory

All Python software released by OCR-D requires Python 3.8 or higher.

NOTE Some OCR-D-Tools (or even test cases) might reveal an unintended behavior if you have specific environment modifications, like:

  • using a custom build of ImageMagick, whose format delegates are different from what OCR-D supposes
  • custom Python logging configurations in your personal account

Command line tools

NOTE: All OCR-D CLI tools support a --help flag which shows usage and supported flags, options and arguments.

ocrd CLI

ocrd-dummy CLI

A minimal OCR-D processor that copies from -I/-input-file-grp to -O/-output-file-grp

Configuration

Almost all behaviour of the OCR-D/core software is configured via CLI options and flags, which can be listed with the --help flag that all CLI support.

Some parts of the software are configured via environment variables:

  • OCRD_METS_CACHING: If set to true, access to the METS file is cached, speeding in-memory search and modification.

  • OCRD_PROFILE: This variable configures the built-in CPU and memory profiling. If empty, no profiling is done. Otherwise expected to contain any of the following tokens:

    • CPU: Enable CPU profiling of processor runs
    • RSS: Enable RSS memory profiling
    • PSS: Enable proportionate memory profiling
  • OCRD_PROFILE_FILE: If set, then the CPU profile is written to this file for later peruse with a analysis tools like snakeviz

  • PATH: Search path for processor executables (affects ocrd process and ocrd resmgr).

  • HOME: Directory to look for ocrd_logging.conf, fallback for unset XDG variables (see below).

  • XDG_CONFIG_HOME: Directory to look for ./ocrd/resources.yml (i.e. ocrd resmgr user database) โ€“ defaults to $HOME/.config.

  • XDG_DATA_HOME: Directory to look for ./ocrd-resources/* (i.e. ocrd resmgr data location) โ€“ defaults to $HOME/.local/share.

  • OCRD_DOWNLOAD_RETRIES: Number of times to retry failed attempts for downloads of workspace files.

  • OCRD_DOWNLOAD_TIMEOUT: Timeout in seconds for connecting or reading (comma-separated) when downloading.

  • OCRD_METS_CACHING: Whether to enable in-memory storage of OcrdMets data structures for speedup during processing or workspace operations.

  • OCRD_MAX_PROCESSOR_CACHE: Maximum number of processor instances (for each set of parameters) to be kept in memory (including loaded models) for processing workers or processor servers.

  • OCRD_NETWORK_SERVER_ADDR_PROCESSING: Default address of Processing Server to connect to (for ocrd network client processing).

  • OCRD_NETWORK_SERVER_ADDR_WORKFLOW: Default address of Workflow Server to connect to (for ocrd network client workflow).

  • OCRD_NETWORK_SERVER_ADDR_WORKSPACE: Default address of Workspace Server to connect to (for ocrd network client workspace).

  • OCRD_NETWORK_RABBITMQ_CLIENT_CONNECT_ATTEMPTS: Number of attempts for a worker to create its queue. Helpful if the rabbitmq-server needs time to be fully started.

Packages

ocrd_utils

Contains utilities and constants, e.g. for logging, path normalization, coordinate calculation etc.

See README for ocrd_utils for further information.

ocrd_models

Contains file format wrappers for PAGE-XML, METS, EXIF metadata etc.

See README for ocrd_models for further information.

ocrd_modelfactory

Code to instantiate models from existing data.

See README for ocrd_modelfactory for further information.

ocrd_validators

Schemas and routines for validating BagIt, ocrd-tool.json, workspaces, METS, page, CLI parameters etc.

See README for ocrd_validators for further information.

ocrd_network

Components related to OCR-D Web API

See README for ocrd_network for further information.

ocrd

Depends on all of the above, also contains decorators and classes for creating OCR-D processors and CLIs.

Also contains the command line tool ocrd.

See README for ocrd for further information.

bash library

Builds a bash script that can be sourced by other bash scripts to create OCRD-compliant CLI.

See README for bashlib for further information.

Testing

Download assets (make assets)

Test with local files: make test

  • Test with remote assets:
    • make test OCRD_BASEURL='https://github.com/OCR-D/assets/raw/master/data/'

See Also

core's People

Contributors

kba avatar mehmedgit avatar bertsky avatar joschrew avatar m3ssman avatar stweil avatar wrznr avatar cneud avatar hnesk avatar tdoan2010 avatar mweidling avatar mikegerber avatar mexthecat avatar j23d avatar b2m avatar witiko avatar finkf avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.