Shypd.aiThe largest open index of AI toolsimgaug is an open-source Python library for image augmentation in machine learning projects. It helps convert input images into a larger set of altered images, supporting various techniques to improve model generalization and performance.
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imgaug is a comprehensive Python library designed for image augmentation in machine learning experiments. It enables users to convert a set of input images into a much larger set of slightly altered images, which is crucial for improving model generalization and preventing overfitting. The library offers a wide array of augmentation techniques, including affine transformations, perspective transformations, contrast changes, Gaussian noise, dropout of regions, hue/saturation changes, cropping/padding, and blurring. It is optimized for high performance and supports various data types beyond just images, such as heatmaps, segmentation maps, keypoints, bounding boxes, polygons, and line strings. A key feature is its automatic alignment of sampled random values, ensuring consistency across augmented data types without extra code. imgaug also provides many helper functions for tasks like drawing heatmaps, scaling segmentation maps, and converting keypoints to distance maps, and supports augmentation on multiple CPU cores for efficiency.
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