CV backbones including GhostNet, TinyNet and TNT, developed by Huawei Noah's Ark Lab.

Overview

CV Backbones

including GhostNet, TinyNet, TNT (Transformer in Transformer) developed by Huawei Noah's Ark Lab.

News

2022/01/05 PyramidTNT: An improved TNT baseline is released.

2021/09/28 The paper of TNT (Transformer in Transformer) is accepted by NeurIPS 2021.

2021/09/18 The extended version of Versatile Filters is accepted by T-PAMI.

2021/08/30 GhostNet paper is selected as the Most Influential CVPR 2020 Papers.

2021/08/26 The codes of LegoNet and Versatile Filters has been merged into this repo.

2021/06/15 The code of TNT (Transformer in Transformer) has been released in this repo.

2020/10/31 GhostNet+TinyNet achieves better performance. See details in our NeurIPS 2020 paper: arXiv.

2020/06/10 GhostNet is included in PyTorch Hub.


GhostNet Code

This repo provides GhostNet pretrained models and inference code for TensorFlow and PyTorch:

For training, please refer to tinynet or timm.

TinyNet Code

This repo provides TinyNet pretrained models and inference code for PyTorch:

TNT Code

This repo provides training code and pretrained models of TNT (Transformer in Transformer) for PyTorch:

The code of PyramidTNT is also released:

LegoNet Code

This repo provides the implementation of paper LegoNet: Efficient Convolutional Neural Networks with Lego Filters (ICML 2019)

Versatile Filters Code

This repo provides the implementation of paper Learning Versatile Filters for Efficient Convolutional Neural Networks (NeurIPS 2018)

Citation

@inproceedings{ghostnet,
  title={GhostNet: More Features from Cheap Operations},
  author={Han, Kai and Wang, Yunhe and Tian, Qi and Guo, Jianyuan and Xu, Chunjing and Xu, Chang},
  booktitle={CVPR},
  year={2020}
}
@inproceedings{tinynet,
  title={Model Rubik’s Cube: Twisting Resolution, Depth and Width for TinyNets},
  author={Han, Kai and Wang, Yunhe and Zhang, Qiulin and Zhang, Wei and Xu, Chunjing and Zhang, Tong},
  booktitle={NeurIPS},
  year={2020}
}
@inproceedings{tnt,
  title={Transformer in transformer},
  author={Han, Kai and Xiao, An and Wu, Enhua and Guo, Jianyuan and Xu, Chunjing and Wang, Yunhe},
  booktitle={NeurIPS},
  year={2021}
}
@inproceedings{legonet,
    title={LegoNet: Efficient Convolutional Neural Networks with Lego Filters},
    author={Yang, Zhaohui and Wang, Yunhe and Liu, Chuanjian and Chen, Hanting and Xu, Chunjing and Shi, Boxin and Xu, Chao and Xu, Chang},
    booktitle={ICML},
    year={2019}
  }
@inproceedings{wang2018learning,
  title={Learning versatile filters for efficient convolutional neural networks},
  author={Wang, Yunhe and Xu, Chang and Chunjing, XU and Xu, Chao and Tao, Dacheng},
  booktitle={NeurIPS},
  year={2018}
}

Other versions of GhostNet

This repo provides the TensorFlow/PyTorch code of GhostNet. Other versions and applications can be found in the following:

  1. timm: code with pretrained model
  2. Darknet: cfg file, and description
  3. Gluon/Keras/Chainer: code
  4. Paddle: code
  5. Bolt inference framework: benckmark
  6. Human pose estimation: code
  7. YOLO with GhostNet backbone: code
  8. Face recognition: cavaface, FaceX-Zoo, TFace
Comments
  • TypeError: __init__() got an unexpected keyword argument 'bn_tf'

    TypeError: __init__() got an unexpected keyword argument 'bn_tf'

    Hello, I want to ask what caused the following error when running the train.py file? thank you “ TypeError: init() got an unexpected keyword argument 'bn_tf' ”

    opened by ModeSky 16
  • Counting ReLU vs HardSwish FLOPs

    Counting ReLU vs HardSwish FLOPs

    Thank you very much for sharing the source code. I have a question related to FLOPs counting for ReLU and HardSwish. I saw in the paper the flops are the same in ReLU and HardSwish. Can you explain this situation? image

    opened by jahongir7174 10
  • kernel size in primary convolution of Ghost module

    kernel size in primary convolution of Ghost module

    Hi, It is said in your paper that the primary convolution in Ghost module can have customized kernel size, which is a major difference from existing efficient convolution schemes. However, it seems that in this code all the kernel size of primary convolution in Ghost module are set to [1, 1], and the kernel set in _CONV_DEFS_0 are only used in blocks of stride=2. Is it set intentionally?

    opened by YUHAN666 9
  • 用GhostModule替换Conv2d,loss降的很慢?

    用GhostModule替换Conv2d,loss降的很慢?

    我直接将efficientnet里面的MBConvBlock中的Conv2d替换为GhostModule: Conv2d(in_channels=inp, out_channels=oup, kernel_size=1, bias=False) 替换为 GhostModule(inp, oup), 其他参数不变,为什么损失比以前收敛的更慢了,一直降不下来?请问需要修改其他什么参数吗?

    opened by yc-cui 8
  • Training hyperparams on ImageNet

    Training hyperparams on ImageNet

    Hi, thanks for sharing such a wonderful work, I'd like to reproduce your results on ImageNet, could you please specify training parameters such as initial learning rate, how to decay it, batch size, etc. It would be even better if you can provide tricks to train GhostNet, such as label smoothing and data augmentation. Thx!

    good first issue 
    opened by sean-zhuh 8
  • Why did you exclude EfficientNetB0 from Accuracy-Latency chart?

    Why did you exclude EfficientNetB0 from Accuracy-Latency chart?

    @iamhankai Hi,

    Great work!

    1. Why did you exclude EfficientNetB0 (0.390 BFlops - 76.3% Top1) from Accuracy-Latency chart?

    2. Also what mini_batch_size did you use for training GhostNet?

    flops_latency

    opened by AlexeyAB 8
  • VIG pretrained weights

    VIG pretrained weights

    @huawei-noah-admin cna you please share the VIG pretraiend model on google drive or one drive as baidu is not accessible from our end

    THank in advance

    opened by abhigoku10 7
  • The implementation of Isotropic architecture

    The implementation of Isotropic architecture

    Hi, thanks for sharing this impressive work. The paper mentioned two architectures, Isotropic one and pyramid one. I noticed that in the code, this is a reduce_ratios, and this reduce_ratios are used by a avg_pooling operation to calculate before building the graph. I am wondering whether all I need to do is setting this reduce_ratios to [1,1,1,1] if I want to implement the Isotropic architecture. Thanks.

    self.n_blocks = sum(blocks) channels = opt.channels reduce_ratios = [4, 2, 1, 1] dpr = [x.item() for x in torch.linspace(0, drop_path, self.n_blocks)] num_knn = [int(x.item()) for x in torch.linspace(k, k, self.n_blocks)]

    opened by buptxiaofeng 6
  • Gradient overflow occurs while training tnt-ti model

    Gradient overflow occurs while training tnt-ti model

    ^@^@Train: 41 [ 0/625 ( 0%)] Loss: 4.564162 (4.5642) Time: 96.744s, 21.17/s (96.744s, 21.17/s) LR: 8.284e-04 Data: 94.025 (94.025) ^@^@^@^@Train: 41 [ 50/625 ( 8%)] Loss: 4.395192 (4.4797) Time: 2.742s, 746.96/s (7.383s, 277.38/s) LR: 8.284e-04 Data: 0.057 (4.683) ^@^@^@^@Train: 41 [ 100/625 ( 16%)] Loss: 4.424296 (4.4612) Time: 2.741s, 747.15/s (6.529s, 313.66/s) LR: 8.284e-04 Data: 0.056 (3.831) Gradient overflow. Skipping step, loss scaler 0 reducing loss scale to 16384.0 Gradient overflow. Skipping step, loss scaler 0 reducing loss scale to 16384.0 Gradient overflow. Skipping step, loss scaler 0 reducing loss scale to 16384.0 Gradient overflow. Skipping step, loss scaler 0 reducing loss scale to 16384.0

    And the top-1 acc is only 0.2 after 40 epochs.

    Any tips available here, dear @iamhankai @yitongh

    opened by jimmyflycv 6
  • Bloated model

    Bloated model

    Hi, I am using Ghostnet backbone for training YoloV3 model in Tensorflow, but I am getting a bloated model. The checkpoint data size is approx. 68MB, but the checkpoint given here is of approx 20MB https://github.com/huawei-noah/ghostnet/blob/master/tensorflow/models/ghostnet_checkpoint.data-00000-of-00001

    I am also training EfficientNet model with YoloV3 and that seems to be working fine, without any bloated size.

    Could anyone or the author please confirm if this is the correct architecture or anything seems weird? I have attached the Ghostnet architecture file out of the code.

    Thanks. ghostnet_model_arch.txt

    opened by ghost 6
  • Replace Conv2d in my network, however it becomes slower, why?

    Replace Conv2d in my network, however it becomes slower, why?

    Above all, thanks for your great work! It really inspires me a lot! But now I have a question.

    I replace all the Conv2d operations in my network except the final ones, the model parameters really becomes much more less. However, when testing, I found that the average forward time decreases a lot by the replacement (from 428FPS down to 354FPS). So, is this a normal phenomenon? Or is this because of the concat operation?

    opened by FunkyKoki 6
  • VIG for segmenation

    VIG for segmenation

    @iamhankai thanks for open-sourcing the code base . Can you please let me knw how to use the pvig for segmentation related activities its really helpful

    THanks in advance

    opened by abhigoku10 0
  • higher performance of ViG

    higher performance of ViG

    I try to train ViG-S on ImageNet and get 80.54% top1 accuracy, which is higher than that in paper, 80.4%. I wonder if 80.4 is the average of multiple trainings? If yes, how many reps do you use?

    opened by tdzdog 9
Releases(GhostNetV2)
Owner
HUAWEI Noah's Ark Lab
Working with and contributing to the open source community in data mining, artificial intelligence, and related fields.
HUAWEI Noah's Ark Lab
audioLIME: Listenable Explanations Using Source Separation

audioLIME This repository contains the Python package audioLIME, a tool for creating listenable explanations for machine learning models in music info

Institute of Computational Perception 27 Dec 01, 2022
Road Crack Detection Using Deep Learning Methods

Road-Crack-Detection-Using-Deep-Learning-Methods This is my Diploma Thesis ¨Road Crack Detection Using Deep Learning Methods¨ under the supervision of

Aggelos Katsaliros 3 May 03, 2022
Implementation of "JOKR: Joint Keypoint Representation for Unsupervised Cross-Domain Motion Retargeting"

JOKR: Joint Keypoint Representation for Unsupervised Cross-Domain Motion Retargeting Pytorch implementation for the paper "JOKR: Joint Keypoint Repres

45 Dec 25, 2022
[CVPR 2019 Oral] Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation

SelectionGAN for Guided Image-to-Image Translation CVPR Paper | Extended Paper | Guided-I2I-Translation-Papers Citation If you use this code for your

Hao Tang 424 Dec 02, 2022
Anchor Retouching via Model Interaction for Robust Object Detection in Aerial Images

Anchor Retouching via Model Interaction for Robust Object Detection in Aerial Images In this paper, we present an effective Dynamic Enhancement Anchor

13 Dec 09, 2022
Code for ECCV 2020 paper "Contacts and Human Dynamics from Monocular Video".

Contact and Human Dynamics from Monocular Video This is the official implementation for the ECCV 2020 spotlight paper by Davis Rempe, Leonidas J. Guib

Davis Rempe 207 Jan 05, 2023
Neuralnetwork - Basic Multilayer Perceptron Neural Network for deep learning

Neural Network Just a basic Neural Network module Usage Example Importing Module

andreecy 0 Nov 01, 2022
Learned Token Pruning for Transformers

LTP: Learned Token Pruning for Transformers Check our paper for more details. Installation We follow the same installation procedure as the original H

Sehoon Kim 52 Dec 29, 2022
This MVP data web app uses the Streamlit framework and Facebook's Prophet forecasting package to generate a dynamic forecast from your own data.

📈 Automated Time Series Forecasting Background: This MVP data web app uses the Streamlit framework and Facebook's Prophet forecasting package to gene

Zach Renwick 42 Jan 04, 2023
Code for A Volumetric Transformer for Accurate 3D Tumor Segmentation

VT-UNet This repo contains the supported pytorch code and configuration files to reproduce 3D medical image segmentaion results of VT-UNet. Environmen

Himashi Amanda Peiris 114 Dec 20, 2022
👐OpenHands : Making Sign Language Recognition Accessible (WiP 🚧👷‍♂️🏗)

👐 OpenHands: Sign Language Recognition Library Making Sign Language Recognition Accessible Check the documentation on how to use the library: ReadThe

AI4Bhārat 69 Dec 12, 2022
The implementation of "Bootstrapping Semantic Segmentation with Regional Contrast".

ReCo - Regional Contrast This repository contains the source code of ReCo and baselines from the paper, Bootstrapping Semantic Segmentation with Regio

Shikun Liu 128 Dec 30, 2022
Code for "Human Pose Regression with Residual Log-likelihood Estimation", ICCV 2021 Oral

Human Pose Regression with Residual Log-likelihood Estimation [Paper] [arXiv] [Project Page] Human Pose Regression with Residual Log-likelihood Estima

JeffLi 347 Dec 24, 2022
Code for the AAAI-2022 paper: Imagine by Reasoning: A Reasoning-Based Implicit Semantic Data Augmentation for Long-Tailed Classification

Imagine by Reasoning: A Reasoning-Based Implicit Semantic Data Augmentation for Long-Tailed Classification (AAAI 2022) Prerequisite PyTorch = 1.2.0 P

16 Dec 14, 2022
Example of a Quantum LSTM

Example of a Quantum LSTM

Riccardo Di Sipio 36 Oct 31, 2022
Source code for the paper "Periodic Traveling Waves in an Integro-Difference Equation With Non-Monotonic Growth and Strong Allee Effect"

Source code for the paper "Periodic Traveling Waves in an Integro-Difference Equation With Non-Monotonic Growth and Strong Allee Effect" by Michael Ne

M Nestor 1 Apr 19, 2022
Learning cell communication from spatial graphs of cells

ncem Features Repository for the manuscript Fischer, D. S., Schaar, A. C. and Theis, F. Learning cell communication from spatial graphs of cells. 2021

Theis Lab 77 Dec 30, 2022
Real-Time Semantic Segmentation in Mobile device

Real-Time Semantic Segmentation in Mobile device This project is an example project of semantic segmentation for mobile real-time app. The architectur

708 Jan 01, 2023
OpenABC-D: A Large-Scale Dataset For Machine Learning Guided Integrated Circuit Synthesis

OpenABC-D: A Large-Scale Dataset For Machine Learning Guided Integrated Circuit Synthesis Overview OpenABC-D is a large-scale labeled dataset generate

NYU Machine-Learning guided Design Automation (MLDA) 31 Nov 22, 2022
Repository For Programmers Seeking a platform to show their skills

Programming-Nerds Repository For Programmers Seeking Pull Requests In hacktoberfest ❓ What's Hacktoberfest 2021? Hacktoberfest is the easiest way to g

42 Oct 29, 2022