This tool is designed to help balance class distributions in datasets, which is particularly useful for enhancing the performance of machine learning models affected by class imbalance.

This model YOLOv5 🚀 is used to benchmark patch augmentation performance of patchmentation.

This datasets are used to benchmark patch augmentation performance of patchmentation.

A comprehensive toolkit for converting image classification datasets into object detection datasets and training them using YOLOv8. This project streamlines the process of dataset preparation, augmentation, and training, making it easier to leverage YOLOv8 for custom object detection tasks.

This repository contains PyTorch implementation of various architectures and some helper functions for data augmentation, custom dataset building etc...

University MS Thesis Project, Controlling an avatar in a Virtual Environment via EEG Motor Imagery

A python library to perform patch augmentation.

Custom pedestrian detection based on yolov3.

learnig synthetic dataset generation (data augmentation) with tensorflow lib for computer vision

First-Prize winner in the Core Track of the 2022 OpenCV AI Competition

Lightweight image converter and dataset augmentor

[Python] Additional works on Edward Choi's medGAN (generative adversarial network for electronic health records). In particular: boosting the prediction score using dataset augmentation.