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MMDetection For Remote Sensing

News: This project is base on mmdetection to reimplement RRPN and use the model Faster R-CNN OBB

Introduction

The master branch works with PyTorch 1.1 or higher.

mmdetection is an open source object detection toolbox based on PyTorch. It is a part of the open-mmlab project developed by Multimedia Laboratory, CUHK.

demo image

Benchmark and model zoo

Supported methods and backbones are shown in the below table. Results and models are available in the Model zoo.

ResNetResNeXtSENetVGGHRNet
RPN
Fast R-CNN
Faster R-CNN
Mask R-CNN
Cascade R-CNN
Cascade Mask R-CNN
SSD
RetinaNet
GHM
Mask Scoring R-CNN
FCOS
Double-Head R-CNN
Grid R-CNN (Plus)
Hybrid Task Cascade
Libra R-CNN
Guided Anchoring

Other features

Installation

  1. Please refer to INSTALL.md for installation and dataset preparation.
  2. Before install, you should make sure the configuration is correct
vim ~/.condarc
channels:
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch/
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/msys2/
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
show_channel_urls: true
vim ~/.bashrc
export GCCPATH=/mnt/lustre/share/gcc/gcc-5.3.0
export PATH=$GCCPATH/bin:$PATH
export CC=$GCCPATH/bin/gcc
export CXX=$GCCPATH/bin/g++
export LD_LIBRARY_PATH=$GCCPATH/lib64:$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=/mnt/lustre/share/gcc/gmp-4.3.2/lib:$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=/mnt/lustre/share/gcc/mpc-0.8.1/lib:$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=/mnt/lustre/share/gcc/mpfr-2.4.2/lib:$LD_LIBRARY_PATH
export CUDA_HOME=/mnt/lustre/share/cuda-9.0
export PATH=$CUDA_HOME/bin:$PATH
export PATH=/mnt/lustre/share/cuda-9.0/lib64/libcudnn.so.7.0.4::$PATH
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CUDA_HOME/lib64
export LIBRARY_PATH=$LIBRARY_PATH:$CUDA_HOME/lib64
  1. You can install directly from the script below
export INSTALL_DIR=$PWD
conda create -n open-mmlab python=3.7 -y
source activate open-mmlab
conda install pytorch torchvision==0.2.2 cuda90 cudatoolkit=9.0 -y
conda install cython -y
cd $INSTALL_DIR
git clone https://github.com/NVIDIA/apex.git
cd apex
python setup.py install --cuda_ext --cpp_ext
cd $INSTALL_DIR
git clone git@gitlab.bj.sensetime.com:yanhongchang/mmdetection.git
cd mmdetection
git checkout rotated
python setup.py build develop
python setup_rotated.py build develop
unset INSTALL_DIR
rm -rf /mnt/lustre/yanhongchang/.conda/envs/open-mmlab/lib/python3.7/site-packages/torchvision-0.4.1-py3.7-linux-x86_64.egg/

Get Started

Please see GETTING_STARTED.md for the basic usage of MMDetection.