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Scikit-image

lastmod 2024-06-03created 2017-05-106 edits

Image processing in Python

scikit-image is a collection of algorithms for image processing. It is available free of charge and free of restriction. We pride ourselves on high-quality, peer-reviewed code, written by an active community of volunteers.

How to install 

$ pip install scikit-image

transform

  • scikit-image - transform
  • skimage.transform.downscale_local_mean(…) - Downsamples an N-dimensional image by local averaging.
  • skimage.transform.estimate_transform(ttype, …) - Estimates 2D geometric transformation parameters.
  • skimage.transform.frt2(a) - Computes the 2-dimensional finite Radon transform (FRT) for an nxn integer array.
  • skimage.transform.hough_circle(image, radius) - Performs a circular Hough transform.
  • skimage.transform.hough_circle_peaks(…[, …]) - Returns peaks in a circle Hough transform.
  • skimage.transform.hough_ellipse(image[, …]) - Performs an elliptical Hough transform.
  • skimage.transform.hough_line(image[, theta]) - Performs a straight line Hough transform.
  • skimage.transform.hough_line_peaks(hspace, …) - Returns peaks in a straight line Hough transform.
  • skimage.transform.ifrt2(a) - Computes the 2-dimensional inverse finite Radon transform (iFRT) for an (n+1) xn integer array.
  • skimage.transform.integral_image(image) - Integral image / summed area table.
  • skimage.transform.integrate (ii, 시작, 종료) - Use an integral image to integrate over a given window.
  • skimage.transform.iradon(radon_image[, …]) - Inverse Radon transform.
  • skimage.transform.iradon_sart(radon_image[, …]) - Inverse Radon transform.
  • skimage.transform.matrix_transform(coords, …) - Applies a 2D matrix transform.
  • skimage.transform.order_angles_golden_ratio(theta) - Orders angles to reduce the amount of correlated information in subsequent projections.
  • skimage.transform.probabilistic_hough_line(image) - Returns lines from a progressive probabilistic line Hough transform.
  • skimage.transform.pyramid_expand(image[, …]) - Upsamples and then smooths an image.
  • skimage.transform.pyramid_gaussian(image[, …]) - Yields images of the Gaussian pyramid formed by the input image.
  • skimage.transform.pyramid_laplacian(image[, …]) - Yields images of the Laplacian pyramid formed by the input image.
  • skimage.transform.pyramid_reduce(image[, …]) - Smooths and then downsamples an image.
  • skimage.transform.radon (이미지[, 세타, …]) - Computes the Radon transform of an image given specified projection angles.
  • skimage.transform.rescale (이미지, 크기[, …]) - Scales an image by a certain factor.
  • skimage.transform.resize(image, output_shape) - Resizes an image to match a certain size.
  • skimage.transform.rotate (이미지, 각도[, …]) - Rotates an image by a certain angle around its center.
  • skimage.transform.swirl (이미지[, 중앙, …]) - Performs a swirl transformation.
  • skimage.transform.warp (이미지, inverse_map[, …]) - Warps an image according to a given coordinate transformation.
  • skimage.transform.warp_coords(coord_map, shape) - Builds the source coordinates for the output of a 2D image warp.
  • skimage.transform.warp_polar(image[, …]) - Remaps an image to polar or log-polar coordinate space.
  • skimage.transform.AffineTransform([matrix, …]) - 2D affine transformation.
  • skimage.transform.EssentialMatrixTransform([…]) - Essential matrix transformation.
  • skimage.transform.EuclideanTransform([…]) - 2D Euclidean transformation.
  • skimage.transform.FundamentalMatrixTransform([…]) - Fundamental matrix transformation.
  • skimage.transform.PiecewiseAffineTransform() - 2D piecewise affine transformation.
  • skimage.transform.PolynomialTransform([params]) - 2D polynomial transformation.
  • skimage.transform.ProjectiveTransform([matrix]) - Projective transformation.
  • skimage.transform.SimilarityTransform([…]) - 2D similarity transformation.

See also

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