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Quantitative Image Analysis in C++, MATLAB and Python


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, except where the syntax differs from that of DIPlib. 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. The dip.viewer sub-module gives access to DIPviewer. When Python is started through the examples/python/pydip.py script, the Show function 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

We recommend to import the module using

import diplib as dip

All documentation assumes dip is the module name.

NOTE! We consider the Python bindings (PyDIP) to be in development. We aim at not making breaking changes, but will sometimes do so when we feel it significantly improves the usability of the module. These changes will always be highlighted in the change logs and the release notification on the DIPlib website. We recommend that you pin your project to use a specific version of the package on PyPI, and carefully read the change logs before upgrading.