PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNet-V3/V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
-
Updated
May 7, 2024 - Python
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNet-V3/V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source data labeling tool for images, text, hypertext, audio, video and time-series data.
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.
Segmentation models with pretrained backbones. PyTorch.
A PyTorch implementation of EfficientNet
Deep Learning and Reinforcement Learning Library for Scientists and Engineers
Friendly machine learning for the web! 🤖
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
DAMO-YOLO: a fast and accurate object detection method with some new techs, including NAS backbones, efficient RepGFPN, ZeroHead, AlignedOTA, and distillation enhancement.
Sandbox for training deep learning networks
Implementation of EfficientNet model. Keras and TensorFlow Keras.
CVNets: A library for training computer vision networks
Official repository for the "Big Transfer (BiT): General Visual Representation Learning" paper.
EfficientViT is a new family of vision models for efficient high-resolution vision.
PyTorch implementation of image classification models for CIFAR-10/CIFAR-100/MNIST/FashionMNIST/Kuzushiji-MNIST/ImageNet
Caffe models (including classification, detection and segmentation) and deploy files for famouse networks
A coding-free framework built on PyTorch for reproducible deep learning studies. 🏆25 knowledge distillation methods presented at CVPR, ICLR, ECCV, NeurIPS, ICCV, etc are implemented so far. 🎁 Trained models, training logs and configurations are available for ensuring the reproducibiliy and benchmark.
Add a description, image, and links to the imagenet topic page so that developers can more easily learn about it.
To associate your repository with the imagenet topic, visit your repo's landing page and select "manage topics."