Welcome to the phenopype gallery!
Check out the projects below to get a feeling for which sort of image analysis problems can be tackled with phenopype: either run the code yourself (follow the provided instructions) or just check out the read only html version of the notebooks. If you found a bug in the package or any of these materials, please raise an issue in the main phenopype repo on GitHub.
Instructions¶
(Analogous to the phenopype tutorials)
Install phenopype (
pip install phenopype) and jupyter notebook (pip install jupyter notebook).Download and unpack the github archive containing the data and code.
Open a terminal in the unpacked folder (don’t forget to activate your conda environment).
Start the notebooks with
jupyter notebookand click on one of the tutorial files (your browser might give you a security warning - you can ignore it).Run the code cell by cell inside the browser window (Shift + Enter to run cell and advance).
Additional dependencies: ipyplot to display images in the notebooks: (pip install ipyplot), and trackpy to analyze the data collected in project 4 (pip install trackpy).
Gallery (read-only)¶
Below are the read-only html versions of the code contained in the notebooks - to run them yourself, follow the above instructions. If you want to use the notebooks as a blueprint for your own project, you can also save them as a Python script from a running jupyter notebook using File > Download as > Python (.py).
