deep.piste

Tools for implementing Deep.piste study.

Installation

Prerequisites

On windows:

You may need to install "Visual C++ Redistributable Packages for Visual Studio 2013" Microsoft C++ Build Tools.

On Ubuntu:

sudo apt-get install python3-tk

Installation

pip install deep-piste

Installation for contributors

1. Download source code

git clone https://github.com/Epiconcept-Paris/deidcm.git
git clone https://github.com/Epiconcept-Paris/deep.piste.git

2. Create and activate a virtual environment

cd deep.piste/
python3 -m venv env
. env/bin/activate

3. Install deidcm

cd ../deidcm
pip install -e .

4. Install deep.piste

cd ../deep.piste
pip install -e .

Checking installation

1. Checking deidcm installation

Open a python interpreter and try to deidentify a dicom file:

from deidcm.dicom.deid_mammogram import deidentify_image_png

deidentify_image_png(
    "/path/to/mammogram.dcm",
    "/path/to/processed/output-folder",
    "output-filename"
)

2. Checking deep.piste installation

When writing the following command, you should be able to see the help menu:

>>> python3 -m dpiste -h

usage: __main__.py [-h] {extract,transform,export,backup} ...

positional arguments:
  {extract,transform,export,backup}
	extract         	Invoke initial extractions commands
	transform       	Perform transformation on input data
	export          	Sending data
	backup          	Back up data

options:
  -h, --help        	show this help message and exit

Tools for developers

Installation

pip install -e .[quality-tools]

Test and Test Coverage

Tests

Run all tests

pytest

Calculate and Visualize Test Coverage

1. Run test coverage

coverage run --omit="*/test*,*/deidcm/*" -m pytest

2. Visualize report in terminal

coverage report -i

Formatter and Linter

Format your files with python3 -m autopep8 --in-place file/to/format

Lint your files with python3 -m pylint file/to/lint