A transparent library for processing and analyzing individual images of Optical Array Probes (OAPs)
Project description
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Version 0.0.10
Optical Array Processing (oap)
Licensed under the MIT license (see `LICENSE` file)
A transparent library for processing and analyzing individual
images of Optical Array Probes (OAPs)
Author: Lucas Grulich (lucasgrulich@gmx.de)
Last Update: 02. September 2020
Introduction
The oap library is a transparent tool for working directly with image data from Optical Array Probes. It was initially developed for the preparation and classification of image data with neural networks.
This software will be continuously developed further! Comments on this project are welcome! If you have any suggestions for improvement, you can simply write me an email and I will try to implement them.
At the current state, the decompression algorithm has only been implemented for grayscale probes by Droplet Measurement Technologies (DMT).
- DMT Monoscale Decompression coming next!
The complete documentation can be found at https://oap.readthedocs.io
Installation
The oap library is available on PyPi, so simply open a terminal window and type at the prompt:
pip install oap
I always recommend the use of virtual environments (e.g. venv & pipenv) to avoid destroying your Python installation.
But if you don't want to work with virtual environments and still don't want to mess up your system directories, install the library as a user:
pip install oap --user
Usage
A short code snippet that decompresses an OAP imagefile and outputs the first 100 images to the console:
import oap
images = []
oap.imagefile("Imagefile20200830120000", images=images)
for image in images[:100]:
oap.print_array(image)
Initialization & Compilation by yourself
Prerequisites
- Python >= 3.7
- Pipenv
pipenv install
python setup.py install
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