RepVGG: Making VGG-style ConvNets Great Again

Overview

RepVGG-openMMLab

This repository is the code that needs to be submitted for OpenMMLab Algorithm Ecological Challenge,the paper is RepVGG: Making VGG-style ConvNets Great Again

Result :)

  1. RepVGG-b2g4 top1 is 79.78
  2. RepVGG-b3g4 top1 is 80.31
  3. RepVGG-B3 top1 is 80.59

How TO Use?

What is MMCV?

MMCV is a foundational library for computer vision research and supports many research projects as below:

  • MMClassification:OpenMMLab image classification toolbox and benchmark.
  • MMDetection:OpenMMLab detection toolbox and benchmark.
  • MMDetection3D:OpenMMLab’s next-generation platform for general 3D object detection.
  • MMSegmentation:OpenMMLab semantic segmentation toolbox and benchmark.
  • MMAction2:OpenMMLab’s next-generation action understanding toolbox and benchmark.
  • MMTracking:OpenMMLab video perception toolbox and benchmark.
  • ...
Using MMCV for the first time??
  1. Install MMCV using MIM
pip install git+https://github.com/open-mmlab/mim.git

mim install mmcv-full

  1. clone MMClassification and install
git clone https://github.com/open-mmlab/mmclassification.git

cd mmclassification

pip install -e .
  1. Register RepVGG in MMclassification
cp RepVGG-openMMLab/backbones/RepVGG.py \
mmclassification/mmcls/models/backbones/

in mmclassification/mmcls/models/backbones/__init__.py

...
from .RepVGG import RepVGG

__all__ = [
    ..., 'RepVGG'
]
  1. copy config file to mmclassification/config

cp RepVGG-openMMLab/config/repvggb2g4_b32x8.py \
mmclassification/config/


  1. Train Model(If you downloaded Imagenet)
cd mmclassification
python tools/train.py config/repvggb2g4_b32x8.py 

Download && Unzip ImageNet
data/download_imagenet.sh ,This script can automatically build the file structure that Imagenet needs for mmcls

mkdir -p mmclassification/data
cp RepVGG-openMMLab/data/download_imagenet.sh mmclassification/data
cd mmclassification/data
bash download_imagenet.sh

Use the pre-trained model on Google Drive

pre-trained model

  • RepVGGB2g4.pth

  • RepVGGB3g4.pth

  • RepVGGB3.pth

Test Model
in mmclassification

python tools/test.py config/repvggb2g4_b32x8.py ${repvggb2g4 model file} --meterics accuracy

someting like this..
reference
  1. RepVGG:极简架构,SOTA性能,让VGG式模型再次伟大(CVPR-2021)
  2. RepVGG: Making VGG-style ConvNets Great Again (CVPR-2021) (PyTorch)
  3. MMClassification Docs
  4. ImageNet
  5. MMCV DOCs
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