ocrd_segment
This repository aims to provide a number of OCR-D compliant processors for layout analysis and evaluation.
Installation
In your Python virtual environment, run:
pip install ocrd_segment
Usage
Contains processors for various tasks:
- exporting segment images (including results from preprocessing like cropping/masking, deskewing, dewarping or binarization) along with polygon coordinates and metadata:
- ocrd-segment-extract-pages (for pages, also exports MS-COCO format and pageview plots)
- ocrd-segment-extract-regions (for regions, so exports MS-COCO format))
- ocrd-segment-extract-lines (for lines, also exports text and .xlsx)
- ocrd-segment-extract-words (for words, also exports text)
- ocrd-segment-extract-glyphs (for glyphs, also exports text)
- importing layout segmentations from other formats:
- ocrd-segment-from-masks (for mask/label images, i.e. semantic segmentation)
- ocrd-segment-from-coco (for MS-COCO annotation)
- post-processing or repairing layout segmentations:
- ocrd-segment-repair (validity and consistency of all coordinates; also, for regions, reduce overlaps/redundancy between neighbours, and/or simplify polygons, and/or shrink to the alpha shape of foreground contours)
- ocrd-segment-project (remake segment coordinates into the concave hull / alpha shape of their constituents)
- ocrd-segment-replace-original (rebase all segments on cropped+deskewed border frame as new full page)
- ocrd-segment-replace-page (2 input fileGrps; overwrite segmentation below page of first fileGrp by all segments of second fileGrp, rebasing all coordinates; "inverse" of
replace-original) - ocrd-segment-replace-text (insert text below page from single-segment text files; "inverse" of
extract-*)
- comparing different layout segmentations:
- ocrd-segment-evaluate 🚧 (2 input fileGrps; align, compare and evaluate page segmentations; early stage)
- page-segment-evaluate (same with standalone CLI)
- pattern-based segmentation (input file groups N=1, based on a PAGE template, e.g. from Aletheia, and some XSLT or Python to apply it to the input file group)
ocrd-segment-via-template🚧 (unpublished)
- data-driven segmentation (input file groups N=1, based on a statistical model, e.g. Neural Network)
ocrd-segment-via-model🚧 (unpublished)
For detailed behaviour, see --help on each processor CLI.
For detailed description on input/output and parameters, see ocrd-tool.json or --dump-json on each processor CLI.
Development
Prerequisities
Requires libgeos-dev library for building shapely binary requirement, see Shapely Installation from source. Please ensure it's available before trying to install local requirements.
Testing
None yet.
Release files for ocrd-segment 0.2.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ocrd_segment-0.2.2.tar.gz | 55.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ocrd_segment-0.2.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 117.4 kB
Release files / ocrd_segment-0.2.2.tar.gz
| Download URL | ocrd_segment-0.2.2.tar.gz |
|---|---|
| Size | 55.8 kB |
| Tags | Source |
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| Download URL | ocrd_segment-0.2.2-py3-none-any.whl |
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| Size | 61.6 kB |
| Tags | Python 3 |
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