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README.md

Language grade: Python Total alerts

ocrd_cis

CIS OCR-D command line tools for the automatic post-correction of OCR-results.

Introduction

ocrd_cis contains different tools for the automatic post correction of OCR-results. It contains tools for the training, evaluation and execution of the post correction. Most of the tools are following the OCR-D cli conventions.

There is a helper tool to align multiple OCR results as well as a version of ocropy that works with python3.

Installation

There are multiple ways to install the ocrd_cis tools:

  • make install uses pip to install ocrd_cis (see below).
  • make install-devel uses pip -e to install ocrd_cis (see below).
  • pip install --upgrade pip ocrd_cis_dir
  • pip install -e --upgrade pip ocrd_cis_dir

It is possible to install ocrd_cis in a custom directory using virtualenv:

 python3 -m venv venv-dir
 source venv-dir/bin/activate
 make install # or any other command to install ocrd_cis (see above)
 # use ocrd_cis
 deactivate

Usage

Most tools follow the OCR-D cli conventions. They accept the --input-file-grp, --output-file-grp, --parameter, --mets, --log-level command line arguments (short and long). For some tools (most notably the alignment tool) expect a comma seperated list of multiple input file groups.

The ocrd-tool.json contains a schema description of the parameter config file for the different tools that accept the --parameter argument.

ocrd-cis-post-correct.sh

This bash script runs the post correction using a pre-trained model. If additional support OCRs should be used, models for these OCR steps are required and must be configured in an according configuration file (see ocrd-tool.json).

Arguments:

  • --parameter path to configuration file
  • --input-file-grp name of the master-OCR file group
  • --output-file-grp name of the post-correction file group
  • --log-level set log level
  • --mets path to METS file in workspace

ocrd-cis-align

Aligns tokens of multiple input file groups to one output file group. This tool is used to align the master OCR with any additional support OCRs. It accepts a comma-separated list of input file groups, which it aligns in order.

Arguments:

  • --parameter path to configuration file
  • --input-file-grp comma seperated list of the input file groups; first input file group is the master OCR
  • --output-file-grp name of the file group for the aligned result
  • --log-level set log level
  • --mets path to METS file in workspace

ocrd-cis-train.sh

Script to train a model from a list of ground-truth archives (see ocrd-tool.json) for the post correction. The tool somewhat mimics the behaviour of other ocrd tools:

  • --mets for the workspace
  • --log-level is passed to other tools
  • --parameter is used as configuration
  • --output-file-grp defines the output file group for the model

ocrd-cis-data

Helper tool to get the path of the installed data files. Usage: ocrd-cis-data [-jar|-3gs] to get the path of the jar library or the path to th default 3-grams language model file.

ocrd-cis-wer

Helper tool to calculate the word error rate aligned ocr files. It writes a simple JSON-formated stats file to the given output file group.

Arguments:

  • --input-file-grp input file group of aligned ocr results with their respective ground truth.
  • --output-file-grp name of the file group for the stats file
  • --log-level set log level
  • --mets path to METS file in workspace

ocrd-cis-profile

Run the profiler over the given files of the according the given input file grp and adds a gzipped JSON-formatted profile to the output file group of the workspace. This tools requires an installed language profiler.

Arguments:

  • --parameter path to configuration file
  • --input-file-grp name of the input file group to profile
  • --output-file-grp name of the output file group where the profile is stored
  • --log-level set log level
  • --mets path to METS file in the workspace

ocrd-cis-ocropy-train

The ocropy-train tool can be used to train LSTM models. It takes ground truth from the workspace and saves (image+text) snippets from the corresponding pages. Then a model is trained on all snippets for 1 million (or the given number of) randomized iterations from the parameter file.

ocrd-cis-ocropy-train \
  --input-file-grp OCR-D-GT-SEG-LINE \
  --mets mets.xml
  --parameter file:///path/to/config.json

ocrd-cis-ocropy-clip

The ocropy-clip tool can be used to remove intrusions of neighbouring segments in regions / lines of a workspace. It runs a (ad-hoc binarization and) connected component analysis on every text region / line of every PAGE in the input file group, as well as its overlapping neighbours, and for each binary object of conflict, determines whether it belongs to the neighbour, and can therefore be clipped to white. It references the resulting segment image files in the output PAGE (as AlternativeImage).

ocrd-cis-ocropy-clip \
  --input-file-grp OCR-D-SEG-LINE \
  --output-file-grp OCR-D-SEG-LINE-CLIP \
  --mets mets.xml
  --parameter file:///path/to/config.json

ocrd-cis-ocropy-resegment

The ocropy-resegment tool can be used to remove overlap between lines of a workspace. It runs a (ad-hoc binarization and) line segmentation on every text region of every PAGE in the input file group, and for each line already annotated, determines the label of largest extent within the original coordinates (polygon outline) in that line, and annotates the resulting coordinates in the output PAGE.

ocrd-cis-ocropy-resegment \
  --input-file-grp OCR-D-SEG-LINE \
  --output-file-grp OCR-D-SEG-LINE-RES \
  --mets mets.xml
  --parameter file:///path/to/config.json

ocrd-cis-ocropy-segment

The ocropy-segment tool can be used to segment regions into lines. It runs a (ad-hoc binarization and) line segmentation on every text region of every PAGE in the input file group, and adds a TextLine element with the resulting polygon outline to the annotation of the output PAGE.

ocrd-cis-ocropy-segment \
  --input-file-grp OCR-D-SEG-BLOCK \
  --output-file-grp OCR-D-SEG-LINE \
  --mets mets.xml
  --parameter file:///path/to/config.json

ocrd-cis-ocropy-deskew

The ocropy-deskew tool can be used to deskew pages / regions of a workspace. It runs the Ocropy thresholding and deskewing estimation on every segment of every PAGE in the input file group and annotates the orientation angle in the output PAGE.

ocrd-cis-ocropy-deskew \
  --input-file-grp OCR-D-SEG-LINE \
  --output-file-grp OCR-D-SEG-LINE-DES \
  --mets mets.xml
  --parameter file:///path/to/config.json

ocrd-cis-ocropy-denoise

The ocropy-denoise tool can be used to despeckle pages / regions / lines of a workspace. It runs the Ocropy "nlbin" denoising on every segment of every PAGE in the input file group and references the resulting segment image files in the output PAGE (as AlternativeImage).

ocrd-cis-ocropy-denoise \
  --input-file-grp OCR-D-SEG-LINE-DES \
  --output-file-grp OCR-D-SEG-LINE-DEN \
  --mets mets.xml
  --parameter file:///path/to/config.json

ocrd-cis-ocropy-binarize

The ocropy-binarize tool can be used to binarize, denoise and deskew pages / regions / lines of a workspace. It runs the Ocropy "nlbin" adaptive thresholding, deskewing estimation and denoising on every segment of every PAGE in the input file group and references the resulting segment image files in the output PAGE (as AlternativeImage). (If a deskewing angle has already been annotated in a region, the tool respects that and rotates accordingly.) Images can also be produced grayscale-normalized.

ocrd-cis-ocropy-binarize \
  --input-file-grp OCR-D-SEG-LINE-DES \
  --output-file-grp OCR-D-SEG-LINE-BIN \
  --mets mets.xml
  --parameter file:///path/to/config.json

ocrd-cis-ocropy-dewarp

The ocropy-dewarp tool can be used to dewarp text lines of a workspace. It runs the Ocropy baseline estimation and dewarping on every line in every text region of every PAGE in the input file group and references the resulting line image files in the output PAGE (as AlternativeImage).

ocrd-cis-ocropy-dewarp \
  --input-file-grp OCR-D-SEG-LINE-BIN \
  --output-file-grp OCR-D-SEG-LINE-DEW \
  --mets mets.xml
  --parameter file:///path/to/config.json

ocrd-cis-ocropy-recognize

The ocropy-recognize tool can be used to recognize lines / words / glyphs from pages of a workspace. It runs the Ocropy optical character recognition on every line in every text region of every PAGE in the input file group and adds the resulting text annotation in the output PAGE.

ocrd-cis-ocropy-recognize \
  --input-file-grp OCR-D-SEG-LINE-DEW \
  --output-file-grp OCR-D-OCR-OCRO \
  --mets mets.xml
  --parameter file:///path/to/config.json

Tesserocr

Install essential system packages for Tesserocr

sudo apt-get install python3-tk \
  tesseract-ocr libtesseract-dev libleptonica-dev \
  libimage-exiftool-perl libxml2-utils

Then install Tesserocr from: https://github.com/OCR-D/ocrd_tesserocr

pip install -r requirements.txt
pip install .

Download and move tesseract models from: https://github.com/tesseract-ocr/tesseract/wiki/Data-Files or use your own models and place them into: /usr/share/tesseract-ocr/4.00/tessdata

Workflow configuration

A decent pipeline might look like this:

  1. page-level cropping
  2. page-level binarization
  3. page-level deskewing
  4. page-level dewarping
  5. region segmentation
  6. region-level clipping
  7. region-level deskewing
  8. line segmentation
  9. line-level clipping or resegmentation
  10. line-level dewarping
  11. line-level recognition
  12. line-level alignment

If GT is used, steps 1, 5 and 8 can be omitted. Else if a segmentation is used in 5 and 8 which does not produce overlapping sections, steps 6 and 9 can be omitted.

Testing

To run a few basic tests type make test (ocrd_cis has to be installed in order to run any tests).

OCR-D workspace

  • Create a new (empty) workspace: ocrd workspace init workspace-dir
  • cd into workspace-dir
  • Add new file to workspace: ocrd workspace add file -G group -i id -m mimetype

OCR-D links

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