Metadata-Version: 2.1
Name: image-dataset-converter
Version: 0.0.5
Summary: Python3 library for converting between various image annotation dataset formats.
Home-page: https://github.com/waikato-datamining/image-dataset-converter
Author: Peter Reutemann
Author-email: fracpete@waikato.ac.nz
License: MIT License
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Image Processing
License-File: LICENSE

The **image-dataset-converter** library allows the conversion between
various dataset formats for image annotation datasets.
Filters can be supplied as well, e.g., for cleaning up the data.

Dataset formats:

- image classification: ADAMS (r/w), sub-dir (r/w)
- object detection: ADAMS (r/w), COCO (r/w), OPEX (r/w), ROI (r/w), VOC (r/w), YOLO (r/w)
- image segmentation: blue-channel (r/w), grayscale (r/w), indexed PNG (r/w), layer segments (r/w)


Changelog
=========

0.0.5 (2025-01-13)
------------------

- added `setuptools` as dependency
- switched to underscores in project name
- using 90% as default quality for JPEG images now, can be overridden with environment variable `IDC_JPEG_QUALITY`
- added methods to idc.api module: `jpeg_quality()`, `array_to_image(...)`, `empty_image(...)`


0.0.4 (2024-07-16)
------------------

- limiting numpy to <2.0.0 due to problems with imgaug library


0.0.3 (2024-07-02)
------------------

- switched to the `fast-opex` library
- helper method `from_indexedpng` was using incorrect label index (off by 1)
- `Data.save_image` method now ensures that source/target files exist before calling `os.path.samefile`
- requiring seppl>=0.2.6 now
- readers now support default globs, allowing the user to just specify directories as input
  (and the default glob gets appended)
- the `to-yolo-od` writer now has an option for predefined labels (for enforcing label order)
- the `to-yolo-od` writer now stores the labels/labels_cvs files in the respective output folders
  rather than using an absolute file name
- the bluechannel/grayscale/indexed-png image segmentation readers/writers can use a value other
  than 0 now for the background
- `split` filter has been renamed to `split-records`


0.0.2 (2024-06-13)
------------------

- added generic plugins that take user Python functions: `from-pyfunc`, `pyfunc-filter`, `to-pyfunc`
- added `idc-exec` tool that uses generator to produce variable/value pairs that are used to expand
  the provided pipeline template which then gets executed
- added `polygon-simplifier` filter for reducing number of points in polygons
- moved several geometry/image related functions from imgaug library into core library to avoid duplication
- added python-image-complete as dependency
- the `ImageData` class now uses the python-image-complete library to determine the file format rather than
  loading the image into memory in order to determine that
- the `convert-image-format` filter now correctly creates a new container with the converted image data
- the `to-coco-od` writer only allows sorting of categories when using predefined categories now
- the `from-opex-od` reader now handles absent meta-data correctly
- added the `AnnotationsOnlyWriter` mixin for writers that can skip the base image and just output the annotations


0.0.1 (2024-05-06)
------------------

- initial release

