`skimage`#

Image Processing for Python

scikit-image (a.k.a. skimage) is a collection of algorithms for image processing and computer vision.

Attributes#

color: Color space conversion.
data: Example images and datasets.
draw: Drawing primitives, such as lines, circles, text, etc.
exposure: Image intensity adjustment, e.g., histogram equalization, etc.
feature: Feature detection and extraction, e.g., texture analysis, corners, etc.
filters: Sharpening, edge finding, rank filters, thresholding, etc.
future: Functionality with an experimental API.
graph: Graph-based operations, e.g., shortest paths.
io: Reading and saving of images and videos.
measure: Measurement of image properties, e.g., region properties, contours.
metrics: Metrics corresponding to images, e.g., distance metrics, similarity, etc.
morphology: Morphological algorithms, e.g., closing, opening, skeletonization.
registration: Image registration algorithms, e.g., optical flow or phase cross correlation.
restoration: Restoration algorithms, e.g., deconvolution algorithms, denoising, etc.
segmentation: Algorithms to partition images into meaningful regions or boundaries.
transform: Geometric and other transformations, e.g., rotations, Radon transform.
util: Generic utilities.

`color`	Color space conversion.
`data`	Example images and datasets.
`draw`	Drawing primitives, such as lines, circles, text, etc.
`exposure`	Image intensity adjustment, e.g., histogram equalization, etc.
`feature`	Feature detection and extraction, e.g., texture analysis, corners, etc.
`filters`	Sharpening, edge finding, rank filters, thresholding, etc.
`future`	Functionality with an experimental API.
`graph`	Graph-based operations, e.g., shortest paths.
`io`	Reading and saving of images and videos.
`measure`	Measurement of image properties, e.g., region properties, contours.
`metrics`	Metrics corresponding to images, e.g., distance metrics, similarity, etc.
`morphology`	Morphological algorithms, e.g., closing, opening, skeletonization.
`registration`	Image registration algorithms, e.g., optical flow or phase cross correlation.
`restoration`	Restoration algorithms, e.g., deconvolution algorithms, denoising, etc.
`segmentation`	Algorithms to partition images into meaningful regions or boundaries.
`transform`	Geometric and other transformations, e.g., rotations, Radon transform.
`util`	Generic utilities.