A library for image augmentation in machine learning experiments, particularly convolutional neural networks. Supports the augmentation of images, keypoints/landmarks, bounding boxes, heatmaps and segmentation maps in a variety of different ways.
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Release files for pyimgaug 0.5.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pyimgaug-0.5.0.tar.gz | 952.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pyimgaug-0.5.0-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 1.9 MB
Release files / pyimgaug-0.5.0.tar.gz
| Download URL | pyimgaug-0.5.0.tar.gz |
|---|---|
| Size | 952.7 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.10.0
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Release files / pyimgaug-0.5.0-py2.py3-none-any.whl
| Download URL | pyimgaug-0.5.0-py2.py3-none-any.whl |
|---|---|
| Size | 961.1 kB |
| Tags | Python 2 Python 3 |
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SHA-256 checksum How to use checksums |
dc8b4bca8e9ffb9492026abe3479be55cc81986a85778396042d315cc9cb714a
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BLAKE2b-256 checksum How to use checksums |
bc8d155b7183155da6250e62f46959dcaefd265e2ba528f12f67a43bf64bdea0
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.10.0
|
