Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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Fastdup | 1,313 | 3 months ago | 284 | December 01, 2023 | 23 | other | Python | |||
fastdup is a powerful free tool designed to rapidly extract valuable insights from your image & video datasets. Assisting you to increase your dataset images & labels quality and reduce your data operations costs at an unparalleled scale. | ||||||||||
Random Erasing | 697 | 5 months ago | 11 | apache-2.0 | Python | |||||
Random Erasing Data Augmentation. Experiments on CIFAR10, CIFAR100 and Fashion-MNIST | ||||||||||
Pba | 400 | 4 years ago | 9 | apache-2.0 | Jupyter Notebook | |||||
Efficient Learning of Augmentation Policy Schedules | ||||||||||
Wb_color_augmenter | 147 | a year ago | mit | MATLAB | ||||||
WB color augmenter improves the accuracy of image classification and image semantic segmentation methods by emulating different WB effects (ICCV 2019) [Python & Matlab]. | ||||||||||
Pytorch Auto Augment | 82 | 4 years ago | 2 | mit | Python | |||||
PyTorch implementation of AutoAugment. | ||||||||||
Awesome Mixup | 76 | 3 months ago | apache-2.0 | |||||||
Awesome List of Mixup Augmentation Papers for Visual Representation Learning | ||||||||||
Self Kd Lib | 56 | a year ago | 1 | Python | ||||||
[ECCV-2022] Official implementation of MixSKD: Self-Knowledge Distillation from Mixup for Image Recognition && Pytorch Implementations of some Self-Knowledge Distillation and data augmentation methods | ||||||||||
Bird_species_classification | 34 | 4 years ago | mit | Python | ||||||
Supervised Classification of bird species :bird: in high resolution images, especially for, Himalayan birds, having diverse species with fairly low amount of labelled data | ||||||||||
Pytorch Ricap | 23 | 5 years ago | mit | Python | ||||||
PyTorch implementation of RICAP (Random Image Cropping And Patching) | ||||||||||
Recursivemix Pytorch | 20 | a year ago | Python | |||||||
Official Codes and Pretrained Models for RecursiveMix |