phenopype 0.5.0

a phenotyping pipeline for python

phenopype is a phenotyping pipeline for python. It is designed to extract phenotypic data from digital images or video material with minimal user input. Like other scientific python packages it is designed to be run from a python integrated development environment (IDE), like spyder. Some python knowledge is necessary, but most of the heavy lifting is done in the background. If you are interested in using phenopype, install install it from the Python Package Index using pip install phenopype and check the tutorials to get started.

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DISCLAIMER: ONGOING DEVELOPMENT

The program is still in alpha stage and development progresses slow - this is me trying to write a program, while learning python and finishing a PhD. A few core features like blob-counting, object detection or videotracking work (see below), more detailed documentation is in the making. Please feel free contact me if you need bugfixing, or have requests for features, and I will get back to you as soon as I can.

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features

	Automatic object detection via multistep thresholding in a predefined area. Useful if your images have borders or irregular features. Accurracy can be increased with custom modules, e.g. for colour or shape
	Automatic object tracking that uses foreground-background subtractor. High performance possible (shown example is close to real time with HD stream). Can be set to distinguish colour or shapes.
	Automatic scale detection and pixel-size ratios adjustments. Performance depends on image size
	Basic landmarking functionality - high throughput.
	Extract local features like stickleback body armour or organelles

tutorials

Download and unpack this repository, open a command line /bash terminal, and cd to the example folder inside the repo. Assuming you have phenopype, it's dependencies and jupyter notebook installed (comes with scientific python distributions like Anaconda, see above), type jupyter notebook and open one of the tutorials:

• 0_python_intro.ipynb This tutorial is meant to provide a very short overview of the python code needed for basic phenopype workflow. This is useful if you have never used python before, but would like to be able to explore phenopype functionality on your own.

• 1_basic_functions.ipynb This tutorial demonstrates basic workflow with phenopype: the creation of a project, directories and how to use the functions alone and within a programmed loop.

• 2_object_detection.ipynb This tutorial demonstrates how single or multiple objects can be detected and phenotyped in images.

• 3_landmarks_and_local_features.ipynb

development

Planned featues include

• hdf5-implementation (original image > processed image (+ data) > image for ML-training-dataset >> hdf5)
• build your own training data for deep learning algorithms using hdf5 framework
• add Mask R-CNN deep learning algorithm using the opencv implementation (https://github.com/opencv/opencv/tree/master/samples/dnn)

If you have ideas for other functionality, let me know!