INSTALL.md

Installation

1.) Install CUDA 10.1 (if not yet installed)

Tested on: Ubuntu 18.04, CUDA: 10.1 (10.1.105)

1.1) Install NVIDIA drivers (using the terminal):

• sudo add-apt-repository ppa:graphics-drivers/ppa
• sudo apt update
• sudo apt install nvidia-driver-440
• nvidia-smi
• sudo reboot
  
  

1.2) Download CUDA 10.1:

• download cuda 10.1: https://developer.nvidia.com/cuda-10.1-download-archive-base?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1804&target_type=deblocal
• download the deb file, for example: cuda-repo-ubuntu1804-10-1-local-10.1.105-418.39_1.0-1_amd64.deb
  
  

1.3) Install CUDA 10.1 (using the terminal, cd to the directory where the file has been downloaded):

• sudo dpkg -i cuda-repo-ubuntu1804-10-1-local-10.1.105-418.39_1.0-1_amd64.deb
• sudo apt-key add /var/cuda-repo-10-1-local-10.1.105-418.39/7fa2af80.pub
• sudo apt-get update
• sudo apt-get install cuda-toolkit-10-1
  
  

1.4) Set the environmental path:

• sudo gedit ~/.bashrc
• add the following 2 lines at the end of the bashrc file: export PATH=/usr/local/cuda-10.1/bin${PATH:+:${PATH}} export LD_LIBRARY_PATH=/usr/local/cuda-10.1/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
• save the bashrc file and close it
• source ~/.bashrc
  
  

1.5) Check if CUDA has been installed properly:

• nvcc --version (should the CUDA details)
  
  

2.) Install SizeCNN in a virtual environment (using Anaconda)

Tested with: Pytorch 1.4 and torchvision 0.5

2.1) Download and install Anaconda:

• download anaconda: https://www.anaconda.com/distribution/#download-section (python 3.x version)
• install anaconda (using the terminal, cd to the directory where the file has been downloaded): bash Anaconda3-2019.10-Linux-x86_64.sh
  
  

2.2) Make a virtual environment (called sizecnn) using the terminal:

• conda create --name sizecnn python=3.8 pip
• conda activate sizecnn
  
  

2.3) Download the code repository:

• git clone https://git.wur.nl/blok012/sizecnn
• cd sizecnn
  
  

2.4) Install the required software libraries (in the sizecnn virtual environment, using the terminal):

• pip install -U torch==1.4 torchvision==0.5 -f https://download.pytorch.org/whl/cu101/torch_stable.html
• pip install cython pyyaml==5.1
• pip install -U 'git+https://github.com/cocodataset/cocoapi.git#subdirectory=PythonAPI'
• pip install jupyter
• pip install opencv-python
• conda install -c conda-forge -c fvcore fvcore
• pip install nbformat==4.4
• pip install scikit-image matplotlib imageio
• pip install black isort flake8 flake8-bugbear flake8-comprehensions
• pip install -e .
• pip install tifffile
• pip install tqdm
• pip install pandas
• pip install seaborn
• pip install circle-fit
  
  

2.5) Reboot/restart the computer (sudo reboot)

2.6) Check if Pytorch links with CUDA (in the sizecnn virtual environment, using the terminal):

• python
• import torch
• torch.version.cuda (should print 10.1)
• torch.cuda.is_available() (should True)
• torch.cuda.get_device_name(0) (should print the name of the first GPU)
• quit()
  
  

2.7) Check if detectron2 is found in python (in the sizecnn virtual environment, using the terminal):

• python
• import detectron2 (should not print an error)
• from detectron2 import model_zoo (should not print an error)
• quit()