The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

A treasure chest for visual classification and recognition powered by PaddlePaddle

Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"

face recognition training project(pytorch)

Optimize RandAugment with differentiable operations

Applying RandAugment on PointNet++

[Re-implementation] FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence

FastClassification is a tensorflow toolbox for class classification. It provides a training module with various backbones and training tricks towards state-of-the-art class classification.

Unofficial PyTorch Reimplementation of UniformAugment.

Full experimentation notebook for my Keras Example on using RandAugment.

A simple template for classifying things

Image Classification Using Swin Transformer With RandAugment, CutMix, and MixUp

Collection of deep learning modules

EfficientNet with Robust Training: MICCAI Skin Cancer Analysis Challenge

SSL Methods integrated into the official implementation of the ECCV"22 Paper "CoMER: Modeling Coverage for Transformer-based Handwritten Mathematical Expression Recognition"

This project includes multiple models, loss functions, optimizers and image augmentations for image classification task

Prediction of MNIST data with only 100 labels

RandAugment with Keypoints Annotation Support.

This repository contains the code and the report for the coursework of INFR11031 Advanced Vision, a postgraduate course offered at The University of Edinburgh. The task was to train on limited and improve the accuracy of the ResNet-50 classifier on a small subset of the ImageNet dataset containing 50K training images and 50K test images. Achieve…

MobileNetV3 implementation using PyTorch