Currently, PyDIP is a thin wrapper that makes most of the functionality in DIPlib accessible from within Python. Function names and arguments are mostly identical to the C++ functions. The only exception is for indexing into images, which uses the Python slicing syntax. Image objects created by the interface expose their data buffer, and so can be used with most NumPy functions. Likewise, any object that exposes a data buffer (e.g. NumPy arrays) can be used as input to PyDIP functions.
The interface only has automatically generated docstrings that show the names of each of the parameters. Use the DIPlib reference to learn how to use each function. Get started by reading the PyDIP User Manual.
Images can be shown using the
Show method, which uses matplotlib.
PyDIP.PyDIPviewer sub-module gives access to DIPviewer.
When Python is started through the
examples/python/pydip.py script, the
will use the DIPviewer interactive display.
These Jupyter notebooks give a short introduction:
To install, simply type
pip install diplib
Windows users might need to install the Microsoft Visual C++ Redistributable for Visual Studio 2015, 2017 and 2019. To read images through the Bio-Formats library, you will need to download it separately:
python -m diplib download_bioformats