installation_linux.md

Installation Instruction for Linux

(tested on Ubuntu 16.04 and 18.04)

Step 1: Install conda

Go to Step 2 if you have anaconda or miniconda installed

Go to Install conda on Linux, choose Anaconda Installer (for Python 3) and then follow the installation instructions.

Note: What is conda and anaconda, and why we need this? Because conda can effectively manage environment and package installation, setting up conda will make the following steps straightforward and help avoid future problems (conda itself is also very easy to set up).

Step 2: Verify requirement and prepare for installing segmenter

Step 2.1: Start conda

All commands below are typed in the Terminal window

Step 2.2: Test conda version

conda info

You may see somthing like

conda version : 4.6.11
python version : 3.7.3.final.0

conda version > 4.4 is preferred. To update conda, check out how to update your conda. python version >=3.6 is required.

Step 2.3: Test git

git --version

If you don't have git, follow Git for Linux to install.

Step 2.4: Test pip

pip show pip

A message will be printed out on your screen. If you see a warning, like a newer version is available, you can follow the instruction to upgrade you pip.

Step 2.5: Create a new empty conda environment, which we will name "segmentation" (You can certainly choose a different name.)

conda create -n segmentation python=3.6

Step 2.6: Activate your conda environment "segmentation"

conda activate segmentation

(For older version conda, the command is source activate segmentation.)

Step 2.7: Install nb_conda (for easy conda environment management in jupyter notebook)

conda install nb_conda

Step 3: Install segmenter

Step 3.1: Clone aics-segmentation repository from Github (suppose you want to save the folder under '~/Projects')

cd ~/Projects
git clone https://github.com/AllenInstitute/aics-segmentation.git

Step 3.2: install the packages

cd ~/Projects/aics-segmentation
pip install numpy
pip install itkwidgets==0.14.0
pip install -e .[all]

Note 1: Please note that for the users with both python 2 and python 3 installed, use pip3 instead of pip in the commands

Note 2: We use the packge itkwidgets for visualizaiotn within jupyter notebook. Currently, we find version 0.14.0 has slightly better performance in visualizing segmentation results. If you find this viwer keeps crashing in your browser, try pip uninstall itkwidgets and then pip install itkwidgets==0.12.2. For JupyterLab users, version >= 0.17.1 is needed.

Note 3: For Jupyter Lab users, the itk viewer requires additionally run:

jupyter labextension install @jupyter-widgets/jupyterlab-manager itk-jupyter-widgets

Note 4: For advanced user to deploy segmenter on cluster, our package is also available on PyPi

Step 3.3: Test segmenter

cd ~/Projects/aics-segmentation/lookup_table_demo
jupyter notebook

This will take you to your default browser (e.g., Firefox) and launch Jupyter Notebook App within your browser. Open "test_viewer.ipynb" and test if you can run the notebook from beginning to the end. See more details on How to use Jupyter Notebook to running the workflow in the Look-up Table