- The pipelines can be run locally or on a slurm-based computing cluster. This package was made for linux/osx, not windows. If running windows we suggest using a virtual machine. (1) Download Virtual Box (2) Download Linux Ubuntu (3) Install the VM machine
First, clone this repository.
If on a local machine:
sudo apt-get install elastix
sudo apt-get install xvfb
sudo apt-get install libboost-all-dev
[Download] and unpack terastitcher: https://github.com/abria/TeraStitcher/wiki/Binary-packages and then run:
bash TeraStitcher-Qt4-standalone-1.10.16-Linux.sh?dl=1
Note that the filename may slightly differ from this if the version has changed.
- Modify Path in
~/.bashrc:
export PATH="<path/to/software>TeraStitcher-Qt4-standalone-1.16.11-Linux/bin:$PATH"
Check to see if successful
which terastitcher
This should show the path. If it shows nothing, then check the export line in your bashrc file to make sure it is correct.
If you are planning to run BrainPipe on a computing cluster ask your system administrator to install the dependencies mentioned above on the cluster. You will also need Cuda installed under your username to run the CNN (see EXAMPLES: CNN Demo)
Includes three-dimensional convolutional neural network (CNN) with a U-Net architecture (Gornet et al., 2019; K. Lee, Zung, Li, Jain, & Sebastian Seung, 2017) with added packages developed by Kisuk Lee (Massachusetts Institute of Technology), Nick Turner (Princeton University), James Gornet (Columbia University), and Kannan Umadevi Venkatarju (Cold Spring Harbor Laboratories).
DataProvider3
PyTorchUtils
Augmentor
DataTools
Once you have completed the system-wide requirements, install anaconda if not already present on your machine or cluster.
The file in this github repository called: brainpipe_environment.yml contains the configuration of the specific anaconda environment used for BrainPipe. Install the anaconda environment by running the command:
conda env create -f brainpipe_environment.yml
This will create an anaconda environment called brainpipe on your machine. Activate the environment by running:
conda activate brainpipe
If you want to go through the example jupyter notebooks in tutorials/ you will need to add this conda environment as a jupyter kernel:
pip install --user ipykernel
python -m ipykernel install --user --name=brainpipe
Navigate to tools/conv_net and clone the necessary C++ extension scripts for working with DataProvider3:
git clone https://github.com/torms3/DataTools.git
Go to the dataprovider3 and DataTools directories in tools/conv_net and run (for each directory):
python setup.py install
Then go to the augmentor directory in tools/conv_net and run:
pip install -e .
Edit the function directorydeterminer() in tools/utils/directorydeterminer.py to include your system paths on your cluster and/or local machine.
We recommend going through the EXAMPLES to explore the different use cases of BrainPipe.
BrainPipe expects a certain file format for the light sheet files you input to it. This is flexible (see FILE-FORMATTING for details).