#image augmentation

Augmentor is a Python library for machine learning, offering independent image augmentation through a stochastic pipeline. It supports a variety of techniques like rotations and elastic distortions, useful for training neural networks. With multi-threading to boost performance and integration with Keras and PyTorch, it simplifies complex image processing.

imgaug is a Python library providing a comprehensive range of image augmentation techniques for machine learning. It enables transformation of images through methods such as affine transformations, noise addition, and cropping to improve model durability. The library efficiently handles diverse data types including images, heatmaps, and segmentation maps while optimizing performance. Features like automatic alignment of values and multicore augmentation ease complex operations. Compatible with Anaconda and pip, imgaug's detailed documentation and examples ensure smooth integration.

Python library with 70+ image augmentations for classification and detection, compatible with PyTorch/TensorFlow. Widely adopted in research and competitions for its speed and user-friendly API.