This repo is used to research large-scale image classification models for embedded systems. For this purpose, the repo contains (re)implementations of various classification models and scripts for training/evaluating/converting.
The following frameworks are used:
- MXNet/Gluon (info),
- PyTorch (info),
- Chainer (info),
- Keras with MXNet backend (info),
- TensorFlow (info).
For each supported framework, there is a PIP-package containing pure models without auxiliary scripts. List of packages:
- gluoncv2 for Gluon,
- pytorchcv for PyTorch,
- chainercv2 for Chainer,
- kerascv for Keras-MXNet,
- tensorflowcv for TensorFlow.
Currently, models are mostly implemented on Gluon and then ported to other frameworks. Some models are pretrained on ImageNet-1K and CIFAR-10/100 datasets. All pretrained weights are loaded automatically during use. See examples of such automatic loading of weights in the corresponding sections of the documentation dedicated to a particular package:
To use training/evaluating scripts as well as all models, you need to clone the repository and install dependencies:
git clone git@github.com:osmr/imgclsmob.git
pip install -r requirements.txt
Some remarks:
Repois an author repository, if it exists.A,B, andCmeans the implementation of a model for ImageNet-1K, CIFAR-10, and CIFAR-100, respectively.A+,B+, andC+means having a pre-trained model for ImageNet-1K, CIFAR-10, and CIFAR-100, respectively.
| Model | Gluon | PyTorch | Chainer | Keras | TensorFlow | Paper | Repo | Year |
|---|---|---|---|---|---|---|---|---|
| AlexNet | A+ | A+ | A+ | A+ | A+ | link | link | 2012 |
| ZFNet | A | A | A | - | - | link | - | 2013 |
| NIN | B+C+ | B+C+ | B+C+ | - | - | link | link | 2013 |
| VGG | A+ | A+ | A+ | A+ | A+ | link | - | 2014 |
| BN-VGG | A+ | A+ | A+ | A+ | A+ | link | - | 2015 |
| BN-Inception | A+ | A+ | A+ | - | - | link | - | 2015 |
| ResNet | A+B+C+ | A+B+C+ | A+B+C+ | A+ | A+ | link | link | 2015 |
| PreResNet | A+B+C+ | A+B+C+ | A+B+C+ | A+ | A+ | link | link | 2016 |
| ResNeXt | A+B+C+ | A+B+C+ | A+B+C+ | A+ | A+ | link | link | 2016 |
| SENet | A+ | A+ | A+ | A+ | A+ | link | link | 2017 |
| SE-ResNet | A+ | A+ | A+ | A+ | A+ | link | link | 2017 |
| SE-PreResNet | A | A | A | A | A | link | link | 2017 |
| SE-ResNeXt | A+ | A+ | A+ | A+ | A+ | link | link | 2017 |
| IBN-ResNet | A+ | A+ | - | - | - | link | link | 2018 |
| IBN-ResNeXt | A+ | A+ | - | - | - | link | link | 2018 |
| IBN-DenseNet | A+ | A+ | - | - | - | link | link | 2018 |
| AirNet | A+ | A+ | A+ | - | - | link | link | 2018 |
| AirNeXt | A+ | A+ | A+ | - | - | link | link | 2018 |
| BAM-ResNet | A+ | A+ | A+ | - | - | link | link | 2018 |
| CBAM-ResNet | A+ | A+ | A+ | - | - | link | link | 2018 |
| ResAttNet | A | A | A | - | - | link | link | 2017 |
| PyramidNet | A+B+C+ | A+B+C+ | A+B+C+ | - | - | link | link | 2016 |
| DiracNetV2 | A+ | A+ | A+ | - | - | link | link | 2017 |
| CRU-Net | A+ | - | - | - | - | link | link | 2018 |
| DenseNet | A+B+C+ | A+B+C+ | A+B+C+ | A+ | A+ | link | link | 2016 |
| CondenseNet | A+ | A+ | A+ | - | - | link | link | 2017 |
| SparseNet | A | A | A | - | - | link | link | 2018 |
| PeleeNet | A+ | A+ | A+ | - | - | link | link | 2018 |
| WRN | A+B+C+ | A+B+C+ | A+B+C+ | - | - | link | link | 2016 |
| DRN-C | A+ | A+ | A+ | - | - | link | link | 2017 |
| DRN-D | A+ | A+ | A+ | - | - | link | link | 2017 |
| DPN | A+ | A+ | A+ | - | - | link | link | 2017 |
| DarkNet Ref | A+ | A+ | A+ | A+ | A+ | link | link | - |
| DarkNet Tiny | A+ | A+ | A+ | A+ | A+ | link | link | - |
| DarkNet-19 | A | A | A | A | A | link | link | - |
| DarkNet-53 | A+ | A+ | A+ | A+ | A+ | link | link | 2018 |
| ChannelNet | A | A | A | - | A | link | link | 2018 |
| DLA | A+ | A+ | A+ | - | - | link | link | 2017 |
| MSDNet | A | AB | - | - | - | link | link | 2017 |
| FishNet | A+ | A+ | A+ | - | - | link | link | 2018 |
| SqueezeNet | A+ | A+ | A+ | A+ | A+ | link | link | 2016 |
| SqueezeResNet | A+ | A+ | A+ | A+ | A+ | link | - | 2016 |
| SqueezeNext | A+ | A+ | A+ | A+ | A+ | link | link | 2018 |
| ShuffleNet | A+ | A+ | A+ | A+ | A+ | link | - | 2017 |
| ShuffleNetV2 | A+ | A+ | A+ | A+ | A+ | link | - | 2018 |
| MENet | A+ | A+ | A+ | A+ | A+ | link | link | 2018 |
| MobileNet | A+ | A+ | A+ | A+ | A+ | link | link | 2017 |
| FD-MobileNet | A+ | A+ | A+ | A+ | A+ | link | link | 2018 |
| MobileNetV2 | A+ | A+ | A+ | A+ | A+ | link | link | 2018 |
| IGCV3 | A+ | A+ | A+ | A+ | A+ | link | link | 2018 |
| MnasNet | A+ | A+ | A+ | A+ | A+ | link | - | 2018 |
| DARTS | A+ | A+ | A+ | - | - | link | link | 2018 |
| Xception | A+ | A+ | A+ | - | - | link | link | 2016 |
| InceptionV3 | A+ | A+ | A+ | - | - | link | link | 2015 |
| InceptionV4 | A+ | A+ | A+ | - | - | link | link | 2016 |
| InceptionResNetV2 | A+ | A+ | A+ | - | - | link | link | 2016 |
| PolyNet | A+ | A+ | A+ | - | - | link | link | 2016 |
| NASNet-Large | A+ | A+ | A+ | - | - | link | link | 2017 |
| NASNet-Mobile | A+ | A+ | A+ | - | - | link | link | 2017 |
| PNASNet-Large | A+ | A+ | A+ | - | - | link | link | 2017 |