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INSTAllation

Requirements

  • Python 3.7+
  • PyTorch ≥ 1.7
  • CUDA 9.0 or higher

I have tested the following versions of OS and softwares：

  • OS：Ubuntu 16.04/18.04
  • CUDA: 10.0/10.1/10.2/11.3

Install

CUDA Driver Version ≥ CUDA Toolkit Version(runtime version) = torch.version.cuda

a. Create a conda virtual environment and activate it, e.g.,

conda create -n Py39_Torch1.10_cu11.3 python=3.9 -y 
source activate Py39_Torch1.10_cu11.3

b. Make sure your CUDA runtime api version ≤ CUDA driver version. (for example 11.3 ≤ 11.4)

nvcc -V
nvidia-smi

c. Install PyTorch and torchvision following the official instructions, Make sure cudatoolkit version same as CUDA runtime api version, e.g.,

pip3 install torch==1.10.1+cu113 torchvision==0.11.2+cu113 torchaudio==0.10.1+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
nvcc -V
python
>>> import torch
>>> torch.version.cuda
>>> exit()

d. Clone the Yolov8_obb_Prune_Track repository.

git clone https://github.com/yzqxy/Yolov8_obb_Prune_Track.git
cd Yolov8_obb_Prune_Track

e. Install Yolov8_obb_Prune_Track.

pip install -r requirements.txt

Install DOTA_devkit.

(Custom Install, it's just a tool to split the high resolution image and evaluation the obb)

cd Yolov8_obb_Prune_Track/DOTA_devkit
sudo apt-get install swig
swig -c++ -python polyiou.i
python setup.py build_ext --inplace