State-of-the-art data augmentation search algorithms in PyTorch

Last update: Dec 12, 2022

Related tags

Deep Learning MuarAugment

Overview

MuarAugment

Description

MuarAugment is a package providing the easiest way to a state-of-the-art data augmentation pipeline.

How to use

You can install MuarAugment via PIP:

!pip install muaraugment

Example (temp: tutorials and working examples coming soon)

from muar.augmentations import BatchRandAugment, MuAugment

# muar augmentations
rand_augment = BatchRandAugment(N_TFMS=3, MAGN=4)
mu_augment = MuAugment(rand_augment, N_COMPS=4, SELECTED=2)

# model
model = LitClassifier(mu_augment)

# data
train, val, test = mnist()

# train
trainer = Trainer()
trainer.fit(model, train, val)

Tutorials

Overview of data augmentation policy search algorithms

Owner

GitHub Repository

A Traffic Sign Recognition Project which can help the driver recognise the signs via text as well as audio. Can be used at Night also.

Traffic-Sign-Recognition In this report, we propose a Convolutional Neural Network(CNN) for traffic sign classification that achieves outstanding perf

64 Nov 19, 2022

Incremental Transformer Structure Enhanced Image Inpainting with Masking Positional Encoding (CVPR2022)

Incremental Transformer Structure Enhanced Image Inpainting with Masking Positional Encoding by Qiaole Dong*, Chenjie Cao*, Yanwei Fu Paper and Supple

190 Dec 27, 2022

Code for our WACV 2022 paper "Hyper-Convolution Networks for Biomedical Image Segmentation"

Hyper-Convolution Networks for Biomedical Image Segmentation Code for our WACV 2022 paper "Hyper-Convolution Networks for Biomedical Image Segmentatio

17 Nov 02, 2022

Discord bot for notifying on github events

Git-Observer Discord bot for notifying on github events ⚠️ This bot is meant to write messages to only one channel (implementing this for multiple pro

0 Apr 19, 2022

PyTorch implementations of algorithms for density estimation

pytorch-flows A PyTorch implementations of Masked Autoregressive Flow and some other invertible transformations from Glow: Generative Flow with Invert

546 Dec 05, 2022

Semantic graph parser based on Categorial grammars

Lambekseq "Everyone who failed Greek or Latin hates it." This package is for proving theorems in Categorial grammars (CG) and constructing semantic gr

10 Aug 19, 2022

Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation (ACM MM 2020)

Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation (ACM MM 2020) Official implementation of: Forest R-CNN: Large-Vo

54 Jan 06, 2023

Pytorch implementation of face attention network

Face Attention Network Pytorch implementation of face attention network as described in Face Attention Network: An Effective Face Detector for the Occ

312 Dec 09, 2022

Measures input lag without dedicated hardware, performing motion detection on recorded or live video

What is InputLagTimer? This tool can measure input lag by analyzing a video where both the game controller and the game screen can be seen on a webcam

4 Aug 18, 2022

STBP is a way to train SNN with datasets by Backward propagation.

Spiking neural network (SNN), compared with depth neural network (DNN), has faster processing speed, lower energy consumption and more biological interpretability, which is expected to approach Stron

18 Dec 09, 2022

Official implementation of "Can You Spot the Chameleon? Adversarially Camouflaging Images from Co-Salient Object Detection" in CVPR 2022.

Jadena Official implementation of "Can You Spot the Chameleon? Adversarially Camouflaging Images from Co-Salient Object Detection" in CVPR 2022. arXiv

13 Nov 29, 2022

[2021][ICCV][FSNet] Full-Duplex Strategy for Video Object Segmentation

Full-Duplex Strategy for Video Object Segmentation (ICCV, 2021) Authors: Ge-Peng Ji, Keren Fu, Zhe Wu, Deng-Ping Fan*, Jianbing Shen, & Ling Shao This

55 Dec 22, 2022

Weakly Supervised Dense Event Captioning in Videos, i.e. generating multiple sentence descriptions for a video in a weakly-supervised manner.

WSDEC This is the official repo for our NeurIPS paper Weakly Supervised Dense Event Captioning in Videos. Description Repo directories ./: global conf

96 Nov 01, 2022

Angora is a mutation-based fuzzer. The main goal of Angora is to increase branch coverage by solving path constraints without symbolic execution.

Angora Angora is a mutation-based coverage guided fuzzer. The main goal of Angora is to increase branch coverage by solving path constraints without s

833 Jan 07, 2023