Segement wheat leaves and measure cell lengths.
Switch branches/tags
Nothing to show
Clone or download

README.md

README

Mac installation

Ensure that you have Xcode installed, for example by running gcc in the terminal. Alternatively, you can use the app store.

gcc

Install Homebrew.

ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"

Install freetype and Python using Homebrew.

brew install freetype
brew install freeimage
brew install python

Install virtualenv using pip (virtualenv allows you to create a virtual Python environment).

sudo pip install virtualenv

Create a virtual environment.

virtualenv env

Source the virtual environment (note the . at the start of the line).

. ./env/bin/activate

Install Python dependencies into the virtual environment.

pip install numpy
pip install scipy
pip install scikit-image
pip install jicbioimage.core
pip install jicbioimage.transform
pip install jicbioimage.segment
pip install jicbioimage.illustrate

Follow the jicbioimage installation notes to install bioformats.

Download the wheat segementation project from githq and go into it.

Windows installation

Install the Anaconda Python distribution.

Setup a virtual environment named venv and install the scientific Python package dependencies.

conda create –n venv python=2.7 numpy scipy scikit-image

Activate the virtual environment.

activate venv

Install the jicbioimage dependencies.

pip install jicbioimage.core
pip install jicbioimage.transform
pip install jicbioimage.segment
pip install jicbioimage.illustrate

Follow the jicbioimage installation notes to install freeimage and bioformats.

Download the wheat segementation project from githq and go into it.

Data analysis

On Windows remember to activate the virtual environment when you open a new command prompt.

activate venv

On a Mac/Linux system one activates the virtual environment using the command below.

. ./venv/bin/activate

Run the analysis.

python scripts/wheat_variety_analysis.py /path/to/raw/file/of/interest.lif output_directory

This will produce a file named cell_lengths.csv in the output directory along with a number of annotated images. Look at the images and decide if any series need to be excluded from the cell_lengths.csv file due to poor segmentation results.

Use your curated cell_lengths.csv file as input for your statistical analysis.