Open Source Python API for Images
Scientific Image Analysis in Python.
Sikit-Image is an open source Python API for image processing. The API provides a wide range of image processing routines in Python. Using the API, you can extract data from specific, scientific and general purpose images, use NumPy operations for image manipulation, generate structuring elements, block views on images, manipulate exposure and color channels, manage edges and lines and perform geometrical transformations.
Furthermore, the API allows filtering an restoration in images. You can remove small scale object in grayscale images, use mean filters, usharp masking and more. Not only this, the API allows much more features to manipulate images.
At A Glance
An overview of Sikit-Image features.
- Extract Data
- NumPy Arrays
- Manipulate Colors
- Manipulate Exposure
- Manage Edges
- Manage Lines
- Geometrical Transformations
- Image registration
Sikit-Image works with Python 3.x
Getting Started with Sikit-Image
The recommended way to install Sikit-Image is via Pip. Please use the following command to install Sikit-Image.
pip install scikit-image
Manipulate Exposure & Color Channels via Python
Sikit-Image API allows manipulating color & exposure of images programatically.You can convert and RGB Image to grayscale image or HSV image. You can work on histogram matching, Immunohistochemical staining colors separation, tinting gray-scale images, histogram Equalization, gamma and log contrast adjustmen, filtering regional maxima, and adapting gray-scale filters to RGB images
Geometrical Transformations Using Free Python API
The Open Source image library Scikit-Image allows working geometrical transformations of images via python. Using the API, you can rescale, resize, & downscale images, build image pyramids, and swirl image. Furthermore, you can compare two images using structural similarity index, transform images using homographies to preserve the alignmet of the points and more.
Image Filtering & Restoration via Python
Scikit-Image library allows developers to filter and restore images programatically. You can remove small objects from grayscale images with a top hat filter, use windows functions with images, use mean filters, use unsharp masking, use image image deconvolution and more.