A fast library for increasing the number of training images by applying various transformations. Augmentor is a real-time image augmentation library designed to render the process of artificial dataset enlargement more convenient, less error prone, and easier to reproduce. It offers the user the ability to build a stochastic image-processing pipeline (or simply augmentation pipeline) using image operations as building blocks. In other words, an augmentation pipeline is little more but a sequence of operations for which the parameters can (but need not) be random variables, as the following code snippet demonstrates.
Features
- Augmentor.jl provides many augmentation operations such as rotations, flipping, blurring, and more
- Documentation available
- Examples available
- Augmentor.jl uses multiple heuristics to generate efficient tailor-made code for the concrete user-specified augmentation pipeline
- Augmentor tries to avoid the need for any intermediate images and aims to compute the output image directly from the input in one single pass
- Augmentor.jl is a fast Julia library designed to make the process of image augmentation more convenient
License
MIT LicenseFollow Augmentor.jl
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