#Augmentation
Showing 30 of 30 repositories tagged #augmentation, ranked by stars
Fabric is an open-source framework for augmenting humans using AI. It provides a modular system for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere.
An AI-powered Life Operating System for Magnifying Human Capabilities
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
Image augmentation for machine learning experiments.
🎛 🔊 A Python library for audio.
Keras model to generate HTML code from hand-drawn website mockups. Implements an image captioning architecture to drawn source images.
Image augmentation library in Python for machine learning.
Data augmentation for NLP
Medical imaging processing for AI applications.
A Python library for audio data augmentation. Useful for making audio ML models work well in the real world, not just in the lab.
Official Implementation of 'Fast AutoAugment' in PyTorch.
PyTorch extensions for fast R&D prototyping and Kaggle farming
Image Test Time Augmentation with PyTorch!
High-performance Vision library in Python. Scale your research, not boilerplate.
Unofficial PyTorch Reimplementation of RandAugment.
DeltaPy - Tabular Data Augmentation (by @firmai)
Efficient Learning of Augmentation Policy Schedules
Next-generation Albumentations: dual-licensed for open-source and commercial use
Long-Term Evolution Project of Reinforcement Learning
Benchmarking library for RAG
This is the official implementation of our neural-network-based fast diffuse room impulse response generator (FAST-RIR) for generating room impulse responses (RIRs) for a given acoustic environment.
Best Discord Moderation Bot Template 2026 with MongoDB Support
Pytorch implementation of CVPR2021 paper: SuperMix: Supervising the Mixing Data Augmentation
Custom image data generator for TF Keras that supports the modern augmentation module albumentations
:mega: Python library for audio augmentation
TF2.0 port for Augmix paper
SoundPy (alpha stage) is a research-based python package for speech and sound. Applications include deep-learning, filtering, speech-enhancement, audio augmentation, feature extraction and visualization, dataset and audio file conversion, and beyond.
📈 🐍 Multidimensional synthetic data generation with Copula and fPCA models in Python
TensorFlow (Keras) implementation of MobileNetV3 and its segmentation head
Augmented version of SQUAD 2.0 for Questions