There are 11 repositories under imagenet topic.
🖍️ LabelImg is a graphical image annotation tool and label object bounding boxes in images
Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
Powerful and efficient Computer Vision Annotation Tool (CVAT)
Deep Learning and Reinforcement Learning Library for Scientists and Engineers
A PyTorch implementation of EfficientNet and EfficientNetV2 (coming soon!)
Friendly machine learning for the web! 🤖
Segmentation models with pretrained backbones. PyTorch.
CV backbones including GhostNet, TinyNet and TNT, developed by Huawei Noah's Ark Lab.
Implementation of EfficientNet model. Keras and TensorFlow Keras.
Labelbox is the fastest way to annotate data to build and ship computer vision applications.
Classification with PyTorch.
Official repository for the "Big Transfer (BiT): General Visual Representation Learning" paper.
OpenMMLab Image Classification Toolbox and Benchmark
Caffe models (including classification, detection and segmentation) and deploy files for famouse networks
Caffe Implementation of Google's MobileNets (v1 and v2)
Keras implementation of "One pixel attack for fooling deep neural networks" using differential evolution on Cifar10 and ImageNet
Classification models trained on ImageNet. Keras.
PyTorch implementation of image classification models for CIFAR-10/CIFAR-100/MNIST/FashionMNIST/Kuzushiji-MNIST/ImageNet
Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"
Code for Switchable Normalization from "Differentiable Learning-to-Normalize via Switchable Normalization", https://arxiv.org/abs/1806.10779
Train the HRNet model on ImageNet
PyTorch to Keras model convertor
Evaluation of the CNN design choices performance on ImageNet-2012.
Corruption and Perturbation Robustness (ICLR 2019)
MobileNetV3 in pytorch and ImageNet pretrained models
Implementation of: "Exploring Randomly Wired Neural Networks for Image Recognition"
Unsupervised Feature Learning via Non-parametric Instance Discrimination
MEAL V2: Boosting Vanilla ResNet-50 to 80%+ Top-1 Accuracy on ImageNet without Tricks
A coding-free framework built on PyTorch for reproducible deep learning studies. 🏆20 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.
Implementation code of the paper: FishNet: A Versatile Backbone for Image, Region, and Pixel Level Prediction, NeurIPS 2018
Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet
Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019
Unofficial PyTorch Reimplementation of RandAugment.
Object Tracking in Tensorflow ( Localization Detection Classification ) developed to partecipate to ImageNET VID competition