GrokSAR

Toolkit for GrokSAR

• GrokSAR
  • Installation
  • Step 1: Create a conda environment
  • Step 2: Install PyTorch
  • Step 3: Install OpenMMLab 2.x Codebases
  • Step 4: Install groksar
  • Model Zoo and Benchmark
  • Leaderboard
  • Model Zoo
    • DenoDet

Installation

Step 1: Create a conda environment

$ conda create --name groksar python=3.9
$ source activate groksar

Step 2: Install PyTorch

conda install pytorch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 pytorch-cuda=11.8 -c pytorch -c nvidia

Step 3: Install OpenMMLab 2.x Codebases

# openmmlab codebases
pip install -U openmim dadaptation --no-input
mim install mmengine "mmcv>=2.0.0" "mmdet>=3.0.0" "mmsegmentation>=1.0.0" "mmrotate>=1.0.0rc1" mmyolo
# heatmap generation dependencies
pip install grad-cam
# other dependencies
pip install ninja --no-input
pip install scikit-learn
pip install psutil

Step 4: Install groksar

python setup.py develop

Note: make sure you have cd to the root directory of groksar

$ git clone git@github.com:GrokCV/groksar.git
$ cd groksar

Model Zoo and Benchmark

Note: Both passwords for BaiduYun and OneDrive is grok.

Leaderboard

Model Zoo

DenoDet

MSAR

SAR-AIRcraft-1.0

AIR-SARShip-1.0