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[P] Albumentations, an image augmentation library version 0.3 released. New weather augmentations, serialization support for reproducible machine learning pipelines, and speedup improvements

[P] Albumentations, an image augmentation library version 0.3 released. New weather augmentations, serialization support for reproducible machine learning pipelines, and speedup improvements

You can download the library from PyPI using pip install -U albumentations or clone the latest version from https://github.com/albu/albumentations

New features

Weather augmentations.

We’ve added weather augmentations such as RandomRain, RandomSnow, RandomSunFlare, RandomShadow, RandomFog.

https://i.redd.it/4x2y4nty5q731.jpg

Pipeline serialization.

Now we can define transformations in the code and serialize them in python dictionary, json and yaml files. A Jupyter notebook with examples.

New transformations.

Lambda, GaussianBlur, ChannelDropout, CoarseDropout.

The full release notes are available at https://github.com/albu/albumentations/releases/tag/0.3.0

submitted by /u/alexparinov
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.