Scikit image
| scikit-image
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|---|---|
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| Basic data
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| Current version |
0.17.2 ( July 6, 2020 ) |
| operating system | Platform independent |
| programming language | Python , Cython |
| License | BSD license |
| scikit-image.org | |
scikit-image (formerly scikits.image) is a free software - library for image processing for the programming language Python . It contains algorithms for segmentation, geometric transformations , color space manipulation, analysis, filtering, morphology , feature recognition and more. As SciKit (short for SciPy Toolkit), like Scikit-learn , for example , it is based on the numerical and scientific Python libraries NumPy and SciPy .
implementation
Scikit-image is largely written in Python. Some core algorithms were implemented in Cython for performance reasons.
example
In this example, a checkerboard pattern data.checkerboard () is generated and then distorted with an affine mapping . After further elements have been added to the image, corner points are determined using the Harris Corner Detector, an interest operator .
from matplotlib import pyplot as plt
from skimage import data
from skimage.feature import corner_harris, corner_subpix, corner_peaks
from skimage.transform import warp, AffineTransform
from skimage.draw import ellipse
# Wir erzeugen eine Affine Abbildung des Schachbrettmusters data.checkerboard()
tform = AffineTransform(scale=(1.3, 1.1), rotation=1, shear=0.7, translation=(210, 50))
image = warp(data.checkerboard(), tform.inverse, output_shape=(350, 350))
# Ellipse zeichnen
rr, cc = ellipse(310, 175, 10, 100)
image[rr, cc] = 1
# zwei Rechtecke zeichnen
image[180:230, 10:60] = 1
image[230:280, 60:110] = 1
# Mit Hilfe des Harris Corner Detectors Eckpunkte ermitteln
coords = corner_peaks(corner_harris(image), min_distance=5)
coords_subpix = corner_subpix(image, coords, window_size=13)
fig, ax = plt.subplots()
ax.imshow(image, interpolation='nearest', cmap=plt.cm.gray)
ax.plot(coords[:, 1], coords[:, 0], '.b', markersize=3)
ax.plot(coords_subpix[:, 1], coords_subpix[:, 0], '+r', markersize=15)
ax.axis((0, 350, 350, 0))
plt.show()
Web links
See also
- OpenCV a free program library with algorithms for image processing and machine vision
Individual evidence
- ↑ Release 0.17.2 . July 6, 2020 (accessed July 7, 2020).
- ↑ Emmanuelle Gouillart: Scikit-image: image processing - Scipy lecture notes. In: Tutorials on the scientific Python ecosystem: a quick introduction to central tools and techniques. Accessed August 31, 2018 .
- ↑ Eric Chiang: Image Processing with Scikit-Image. In: The Yhat Blog. January 30, 2014, accessed August 31, 2018 .