our objective is to create a reliable dataset by employing data augmentation algorithms. Using this improved GoEmotion dataset, we trained a transformer model with the ability to understand emotions from a given text.

UI to prepare training data for SmartTool inside Supervisely platform

This project focuses on optimizing overpass detection using YOLOv8. It involves training the model with a custom dataset created from synchronized dashcam footage and GPS data. The objective is to refine the model's accuracy in identifying overpasses, enabling precise determination of vehicle location and timing during these instances.

Simple image augmentation library

Local web application providing API and UI for image augmentation, based on the albumentations library

2D facial landmarks detection with neural networks

Explore and build ImgAug augmentations with Supervisely

State-of-the-art https://arxiv.org/abs/2302.09119 https://intranet.matematicas.uady.mx/journal/index.php?c=50

VAE learned on augmented data to improve generalization.

Augmentation yolo format txt and images

Aug Tool is a Python library available on PyPI that simplifies image data augmentation for machine learning tasks, compatible with TensorFlow, PyTorch, and the YOLO library.

Source code of top 3% solution for the Kaggle APTOS 2019 Blindness Detection challenge.

Runner Up Solution for the NeurIPS 2020 Competition - "Predicting Generalization in Deep Learning"

Repository for the paper "Exploring Image Augmentations for Siamese Representation Learning with Chest X-Rays"

Official implementation for "Pure Noise to the Rescue of Insufficient Data: Improving Imbalanced Classification by Training on Random Noise Images" https://arxiv.org/abs/2112.08810

RuTransform: python framework for adversarial attacks and text data augmentation for Russian

This repo contains full solution for the challenge: from datasets creation to training and creating submit file. Moreover it can be used as a universal high-quality baseline solution for any segmentation task.

⚡ Blazing fast audio augmentation in Python, powered by GPU for high-efficiency processing in machine learning and audio analysis tasks.

Repo for the paper "Extrapolating from a Single Image to a Thousand Classes using Distillation"