Image augmentation extension for the image-dataset-converter library.
Examples can be found here:
https://github.com/waikato-datamining/image-dataset-converter-examples
Changelog
=========
0.0.10 (2025-07-11)
-------------------
- switched from `imgaug3` to `imaug` for numpy 2 support
- added `roi-images` filter for extracting sub-images based on object-detection bounding boxes
- the `find-contours` filter now works on any type of image data
- the `transfer_region` method (from `_sub_image_utils`) now initializes the labels of the
full image segmentation annotations with the labels of the sub-image(s) to ensure correct output
0.0.9 (2025-04-03)
------------------
- fixed `idc.imgaug.filter.transfer_region` method: image segmentation layers now use values (0,255)
- using underscores now instead of dashes in dependencies (`setup.py`)
- renamed `idc.imgaug.filter._sub_images_utils.process_image` to `extract_regions`
- added `crop-to-label` filter that crops the image to the bbox of the annotation with the specified label
- the `sub-images` and `meta-sub-images` filter now have options to generate a regions via predefined number
of rows/cols or row height/col width on the fly, useful when dealing with images of differing dimensions
(and the regions parameter is now optional)
0.0.8 (2025-03-14)
------------------
- added support for placeholders: `idc-combine-sub-images`
0.0.7 (2025-02-26)
------------------
- `idc-generate-regions` tool can take margins and overlaps (right/bottom) into account for its region calculations now
- `idc-combine-sub-images` tool now has more details in the exceptions when extraction of groups fail
and prunes the annotation after the merge as well
- `meta-sub-images` now outputs a logging message if there are no annotations after transferring
regions/pruning annotations
- method `transfer_region` now adds the sub-images rather than replacing the tile in the overall layer,
to allow for overlaps (for reducing edge effects)
0.0.6 (2025-01-13)
------------------
- requiring image_dataset_converter>=0.0.5 now
0.0.5 (2025-01-13)
------------------
- switched to underscores in project name
- switched to new methods from idc.api: `empty_image(...)` and `array_to_image(...)`
0.0.4 (2024-07-16)
------------------
- switched from unmaintained imgaug to imgaug3 library (https://github.com/nsetzer/imgaug)
0.0.3 (2024-07-02)
------------------
- added `find-contours` filter for turning blobs in image segmentation annotations into object detection polygons.
0.0.2 (2024-06-13)
------------------
- added `change-grayscale` filter for change pixel values of grayscale images by a factor of fixed value
- added `clip-grayscale` filter for replacing pixel values that go below or above thresholds
- added `enhance` filter for enhancing brightness, contrast, color, sharpness
0.0.1 (2024-05-06)
------------------
- initial release
Raw data
{
"_id": null,
"home_page": "https://github.com/waikato-datamining/image-dataset-converter-imgaug",
"name": "image-dataset-converter-imgaug",
"maintainer": null,
"docs_url": null,
"requires_python": null,
"maintainer_email": null,
"keywords": null,
"author": "Peter Reutemann",
"author_email": "fracpete@waikato.ac.nz",
"download_url": "https://files.pythonhosted.org/packages/00/8c/291bcb94d51ada0c4a1a7de2ca20852f2f090718f5bbc2a6fcd554050eb5/image_dataset_converter_imgaug-0.0.10.tar.gz",
"platform": null,
"description": "Image augmentation extension for the image-dataset-converter library.\n\nExamples can be found here:\n\nhttps://github.com/waikato-datamining/image-dataset-converter-examples\n\n\nChangelog\n=========\n\n0.0.10 (2025-07-11)\n-------------------\n\n- switched from `imgaug3` to `imaug` for numpy 2 support\n- added `roi-images` filter for extracting sub-images based on object-detection bounding boxes\n- the `find-contours` filter now works on any type of image data\n- the `transfer_region` method (from `_sub_image_utils`) now initializes the labels of the\n full image segmentation annotations with the labels of the sub-image(s) to ensure correct output\n\n\n0.0.9 (2025-04-03)\n------------------\n\n- fixed `idc.imgaug.filter.transfer_region` method: image segmentation layers now use values (0,255)\n- using underscores now instead of dashes in dependencies (`setup.py`)\n- renamed `idc.imgaug.filter._sub_images_utils.process_image` to `extract_regions`\n- added `crop-to-label` filter that crops the image to the bbox of the annotation with the specified label\n- the `sub-images` and `meta-sub-images` filter now have options to generate a regions via predefined number\n of rows/cols or row height/col width on the fly, useful when dealing with images of differing dimensions\n (and the regions parameter is now optional)\n\n\n0.0.8 (2025-03-14)\n------------------\n\n- added support for placeholders: `idc-combine-sub-images`\n\n\n0.0.7 (2025-02-26)\n------------------\n\n- `idc-generate-regions` tool can take margins and overlaps (right/bottom) into account for its region calculations now\n- `idc-combine-sub-images` tool now has more details in the exceptions when extraction of groups fail\n and prunes the annotation after the merge as well\n- `meta-sub-images` now outputs a logging message if there are no annotations after transferring\n regions/pruning annotations\n- method `transfer_region` now adds the sub-images rather than replacing the tile in the overall layer,\n to allow for overlaps (for reducing edge effects)\n\n\n0.0.6 (2025-01-13)\n------------------\n\n- requiring image_dataset_converter>=0.0.5 now\n\n\n0.0.5 (2025-01-13)\n------------------\n\n- switched to underscores in project name\n- switched to new methods from idc.api: `empty_image(...)` and `array_to_image(...)`\n\n\n0.0.4 (2024-07-16)\n------------------\n\n- switched from unmaintained imgaug to imgaug3 library (https://github.com/nsetzer/imgaug)\n\n\n0.0.3 (2024-07-02)\n------------------\n\n- added `find-contours` filter for turning blobs in image segmentation annotations into object detection polygons.\n\n\n0.0.2 (2024-06-13)\n------------------\n\n- added `change-grayscale` filter for change pixel values of grayscale images by a factor of fixed value\n- added `clip-grayscale` filter for replacing pixel values that go below or above thresholds\n- added `enhance` filter for enhancing brightness, contrast, color, sharpness\n\n\n0.0.1 (2024-05-06)\n------------------\n\n- initial release\n\n",
"bugtrack_url": null,
"license": "MIT License",
"summary": "Image augmentation extension for the image-dataset-converter library.",
"version": "0.0.10",
"project_urls": {
"Homepage": "https://github.com/waikato-datamining/image-dataset-converter-imgaug"
},
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "008c291bcb94d51ada0c4a1a7de2ca20852f2f090718f5bbc2a6fcd554050eb5",
"md5": "101fc4d5ed1f350bcbbee42ae417da95",
"sha256": "a0aca7c8c95c0460d36e694b6ab3701802a4c2c1da30581591c11644ad9da133"
},
"downloads": -1,
"filename": "image_dataset_converter_imgaug-0.0.10.tar.gz",
"has_sig": false,
"md5_digest": "101fc4d5ed1f350bcbbee42ae417da95",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 31660,
"upload_time": "2025-07-10T22:10:36",
"upload_time_iso_8601": "2025-07-10T22:10:36.569726Z",
"url": "https://files.pythonhosted.org/packages/00/8c/291bcb94d51ada0c4a1a7de2ca20852f2f090718f5bbc2a6fcd554050eb5/image_dataset_converter_imgaug-0.0.10.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-07-10 22:10:36",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "waikato-datamining",
"github_project": "image-dataset-converter-imgaug",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"lcname": "image-dataset-converter-imgaug"
}
JSON
