image processing, image filtering, image analysis, ndarray, segmentation
scikit-image is a collection of algorithms for image processing and analysis, including functions for filtering, feature extraction, segmentation, measurement, and more. It is designed to work seamlessly within the scientific Python ecosystem, including the NumPy and SciPy libraries.
scikit-image has been used in industry, education, and academic research, in fields as disparate as biology and life sciences, materials science, remote sensing/satellite imaging, astrophysics, archaeology, and more. With a common API for 2D, 3D and higher-dimensional imaging, it is usable for a wide variety of imaging data. scikit-image is also being used for pre- and post-processing and analysis with deep learning frameworks such as PyTorch, TensorFlow, and Chainer. With its focus on a clear API for reference algorithms, scikit-image is also used in educational projects such as the SciPy Lecture Notes, the Python Data Science Handbook, and FastAI.