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Merge pull request #798 from matttrent/luv-colorspace
Add Luv colorspace
This commit is contained in:
Stefan van der Walt
@@ -13,6 +13,10 @@ from .colorconv import (convert_colorspace,
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lab2xyz,
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lab2rgb,
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rgb2lab,
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xyz2luv,
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luv2xyz,
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luv2rgb,
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rgb2luv,
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rgb2hed,
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hed2rgb,
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lab2lch,
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+246
-63
@@ -29,9 +29,12 @@ Supported color spaces
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* LAB CIE : Lightness, a, b
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Colorspace derived from XYZ CIE that is intended to be more
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perceptually uniform
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* LUV CIE : Lightness, u, v
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Colorspace derived from XYZ CIE that is intended to be more
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perceptually uniform
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* LCH CIE : Lightness, Chroma, Hue
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Defined in terms of LAB CIE. C and H are the polar representation of
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a and b. The polar angle C is defined to be on (0, 2*pi)
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a and b. The polar angle C is defined to be on ``(0, 2*pi)``
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:author: Nicolas Pinto (rgb2hsv)
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:author: Ralf Gommers (hsv2rgb)
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@@ -68,7 +71,7 @@ def guess_spatial_dimensions(image):
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-------
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spatial_dims : int or None
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The number of spatial dimensions of `image`. If ambiguous, the value
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is `None`.
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is ``None``.
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Raises
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------
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@@ -122,12 +125,12 @@ def convert_colorspace(arr, fromspace, tospace):
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The image to convert.
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fromspace : str
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The color space to convert from. Valid color space strings are
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['RGB', 'HSV', 'RGB CIE', 'XYZ']. Value may also be specified as lower
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case.
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``['RGB', 'HSV', 'RGB CIE', 'XYZ']``. Value may also be specified as
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lower case.
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tospace : str
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The color space to convert to. Valid color space strings are
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['RGB', 'HSV', 'RGB CIE', 'XYZ']. Value may also be specified as lower
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case.
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``['RGB', 'HSV', 'RGB CIE', 'XYZ']``. Value may also be specified as
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lower case.
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Returns
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-------
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@@ -137,7 +140,7 @@ def convert_colorspace(arr, fromspace, tospace):
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Notes
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-----
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Conversion occurs through the "central" RGB color space, i.e. conversion
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from XYZ to HSV is implemented as XYZ -> RGB -> HSV instead of directly.
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from XYZ to HSV is implemented as ``XYZ -> RGB -> HSV`` instead of directly.
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Examples
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--------
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@@ -181,17 +184,17 @@ def rgb2hsv(rgb):
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Parameters
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----------
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rgb : array_like
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The image in RGB format, in a 3-D array of shape (.., .., 3).
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The image in RGB format, in a 3-D array of shape ``(.., .., 3)``.
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Returns
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-------
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out : ndarray
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The image in HSV format, in a 3-D array of shape (.., .., 3).
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The image in HSV format, in a 3-D array of shape ``(.., .., 3)``.
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Raises
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------
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ValueError
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If `rgb` is not a 3-D array of shape (.., .., 3).
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If `rgb` is not a 3-D array of shape ``(.., .., 3)``.
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Notes
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-----
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@@ -259,21 +262,21 @@ def hsv2rgb(hsv):
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Parameters
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----------
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hsv : array_like
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The image in HSV format, in a 3-D array of shape (.., .., 3).
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The image in HSV format, in a 3-D array of shape ``(.., .., 3)``.
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Returns
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-------
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out : ndarray
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The image in RGB format, in a 3-D array of shape (.., .., 3).
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The image in RGB format, in a 3-D array of shape ``(.., .., 3)``.
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Raises
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------
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ValueError
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If `hsv` is not a 3-D array of shape (.., .., 3).
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If `hsv` is not a 3-D array of shape ``(.., .., 3)``.
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Notes
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-----
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The conversion assumes an input data range of [0, 1] for all
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The conversion assumes an input data range of ``[0, 1]`` for all
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color components.
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Conversion between RGB and HSV color spaces results in some loss of
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@@ -468,17 +471,17 @@ def xyz2rgb(xyz):
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Parameters
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----------
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xyz : array_like
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The image in XYZ format, in a 3-D array of shape (.., .., 3).
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The image in XYZ format, in a 3-D array of shape ``(.., .., 3)``.
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Returns
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-------
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out : ndarray
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The image in RGB format, in a 3-D array of shape (.., .., 3).
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The image in RGB format, in a 3-D array of shape ``(.., .., 3)``.
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Raises
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------
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ValueError
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If `xyz` is not a 3-D array of shape (.., .., 3).
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If `xyz` is not a 3-D array of shape ``(.., .., 3)``.
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Notes
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-----
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@@ -513,18 +516,18 @@ def rgb2xyz(rgb):
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----------
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rgb : array_like
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The image in RGB format, in a 3- or 4-D array of shape
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(.., ..,[ ..,] 3).
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``(.., ..,[ ..,] 3)``.
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Returns
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-------
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out : ndarray
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The image in XYZ format, in a 3- or 4-D array of shape
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(.., ..,[ ..,] 3).
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``(.., ..,[ ..,] 3)``.
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Raises
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------
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ValueError
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If `rgb` is not a 3- or 4-D array of shape (.., ..,[ ..,] 3).
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If `rgb` is not a 3- or 4-D array of shape ``(.., ..,[ ..,] 3)``.
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Notes
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-----
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@@ -556,17 +559,17 @@ def rgb2rgbcie(rgb):
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Parameters
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----------
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rgb : array_like
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The image in RGB format, in a 3-D array of shape (.., .., 3).
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The image in RGB format, in a 3-D array of shape ``(.., .., 3)``.
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Returns
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-------
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out : ndarray
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The image in RGB CIE format, in a 3-D array of shape (.., .., 3).
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The image in RGB CIE format, in a 3-D array of shape ``(.., .., 3)``.
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Raises
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------
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ValueError
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If `rgb` is not a 3-D array of shape (.., .., 3).
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If `rgb` is not a 3-D array of shape ``(.., .., 3)``.
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References
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----------
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@@ -588,17 +591,17 @@ def rgbcie2rgb(rgbcie):
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Parameters
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----------
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rgbcie : array_like
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The image in RGB CIE format, in a 3-D array of shape (.., .., 3).
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The image in RGB CIE format, in a 3-D array of shape ``(.., .., 3)``.
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Returns
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-------
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out : ndarray
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The image in RGB format, in a 3-D array of shape (.., .., 3).
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The image in RGB format, in a 3-D array of shape ``(.., .., 3)``.
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Raises
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------
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ValueError
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If `rgbcie` is not a 3-D array of shape (.., .., 3).
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If `rgbcie` is not a 3-D array of shape ``(.., .., 3)``.
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References
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----------
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@@ -621,8 +624,8 @@ def rgb2gray(rgb):
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Parameters
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----------
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rgb : array_like
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The image in RGB format, in a 3-D array of shape (.., .., 3),
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or in RGBA format with shape (.., .., 4).
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The image in RGB format, in a 3-D array of shape ``(.., .., 3)``,
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or in RGBA format with shape ``(.., .., 4)``.
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Returns
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-------
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@@ -632,8 +635,8 @@ def rgb2gray(rgb):
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Raises
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------
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ValueError
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If `rgb2gray` is not a 3-D array of shape (.., .., 3) or
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(.., .., 4).
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If `rgb2gray` is not a 3-D array of shape ``(.., .., 3)`` or
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``(.., .., 4)``.
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References
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----------
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@@ -698,18 +701,18 @@ def xyz2lab(xyz):
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----------
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xyz : array_like
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The image in XYZ format, in a 3- or 4-D array of shape
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(.., ..,[ ..,] 3).
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``(.., ..,[ ..,] 3)``.
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Returns
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-------
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out : ndarray
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The image in CIE-LAB format, in a 3- or 4-D array of shape
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(.., ..,[ ..,] 3).
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``(.., ..,[ ..,] 3)``.
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Raises
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------
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ValueError
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If `xyz` is not a 3-D array of shape (.., ..,[ ..,] 3).
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If `xyz` is not a 3-D array of shape ``(.., ..,[ ..,] 3)``.
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Notes
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-----
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@@ -755,21 +758,21 @@ def lab2xyz(lab):
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Parameters
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----------
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lab : array_like
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The image in lab format, in a 3-D array of shape (.., .., 3).
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The image in lab format, in a 3-D array of shape ``(.., .., 3)``.
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Returns
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-------
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out : ndarray
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The image in XYZ format, in a 3-D array of shape (.., .., 3).
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The image in XYZ format, in a 3-D array of shape ``(.., .., 3)``.
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Raises
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------
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ValueError
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If `lab` is not a 3-D array of shape (.., .., 3).
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If `lab` is not a 3-D array of shape ``(.., .., 3)``.
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Notes
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-----
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Observer= 2A, Illuminant= D65
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Observer = 2A, Illuminant = D65
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CIE XYZ tristimulus values x_ref = 95.047, y_ref = 100., z_ref = 108.883
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References
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@@ -804,18 +807,18 @@ def rgb2lab(rgb):
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----------
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rgb : array_like
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The image in RGB format, in a 3- or 4-D array of shape
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(.., ..,[ ..,] 3).
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``(.., ..,[ ..,] 3)``.
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Returns
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-------
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out : ndarray
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The image in Lab format, in a 3- or 4-D array of shape
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(.., ..,[ ..,] 3).
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``(.., ..,[ ..,] 3)``.
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Raises
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------
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ValueError
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If `rgb` is not a 3- or 4-D array of shape (.., ..,[ ..,] 3).
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If `rgb` is not a 3- or 4-D array of shape ``(.., ..,[ ..,] 3)``.
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Notes
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-----
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@@ -830,17 +833,17 @@ def lab2rgb(lab):
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Parameters
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----------
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rgb : array_like
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The image in Lab format, in a 3-D array of shape (.., .., 3).
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The image in Lab format, in a 3-D array of shape ``(.., .., 3)``.
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Returns
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-------
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out : ndarray
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The image in RGB format, in a 3-D array of shape (.., .., 3).
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The image in RGB format, in a 3-D array of shape ``(.., .., 3)``.
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Raises
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------
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ValueError
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If `lab` is not a 3-D array of shape (.., .., 3).
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If `lab` is not a 3-D array of shape ``(.., .., 3)``.
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Notes
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-----
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@@ -849,23 +852,203 @@ def lab2rgb(lab):
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return xyz2rgb(lab2xyz(lab))
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def xyz2luv(xyz):
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"""XYZ to CIE-Luv color space conversion.
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Parameters
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----------
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xyz : (M, N, [P,] 3) array_like
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The 3 or 4 dimensional image in XYZ format. Final dimension denotes
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channels.
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Returns
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-------
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out : (M, N, [P,] 3) ndarray
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The image in CIE-Luv format. Same dimensions as input.
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Raises
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------
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ValueError
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If `xyz` is not a 3-D or 4-D array of shape ``(M, N, [P,] 3)``.
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Notes
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-----
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XYZ conversion weights use Observer = 2A. Reference whitepoint for D65
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Illuminant, with XYZ tristimulus values of ``(95.047, 100., 108.883)``.
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References
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----------
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.. [1] http://www.easyrgb.com/index.php?X=MATH&H=16#text16
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.. [2] http://en.wikipedia.org/wiki/CIELUV
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Examples
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--------
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>>> from skimage import data
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>>> from skimage.color import rgb2xyz, xyz2luv
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>>> lena = data.lena()
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>>> lena_xyz = rgb2xyz(lena)
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>>> lena_luv = xyz2luv(lena_xyz)
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"""
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arr = _prepare_colorarray(xyz)
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# extract channels
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x, y, z = arr[..., 0], arr[..., 1], arr[..., 2]
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eps = np.finfo(np.float).eps
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# compute y_r and L
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L = y / lab_ref_white[1]
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mask = L > 0.008856
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L[mask] = 116. * np.power(L[mask], 1. / 3.) - 16.
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L[~mask] = 903.3 * L[~mask]
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u0 = 4*lab_ref_white[0] / np.dot([1, 15, 3], lab_ref_white)
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v0 = 9*lab_ref_white[1] / np.dot([1, 15, 3], lab_ref_white)
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# u' and v' helper functions
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def fu(X, Y, Z):
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return (4.*X) / (X + 15.*Y + 3.*Z + eps)
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def fv(X, Y, Z):
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return (9.*Y) / (X + 15.*Y + 3.*Z + eps)
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# compute u and v using helper functions
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u = 13.*L * (fu(x, y, z) - u0)
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v = 13.*L * (fv(x, y, z) - v0)
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return np.concatenate([q[..., np.newaxis] for q in [L, u, v]], axis=-1)
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def luv2xyz(luv):
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"""CIE-Luv to XYZ color space conversion.
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Parameters
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----------
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luv : (M, N, [P,] 3) array_like
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The 3 or 4 dimensional image in CIE-Luv format. Final dimension denotes
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channels.
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Returns
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-------
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out : (M, N, [P,] 3) ndarray
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The image in XYZ format. Same dimensions as input.
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Raises
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------
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ValueError
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If `luv` is not a 3-D or 4-D array of shape ``(M, N, [P,] 3)``.
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Notes
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-----
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XYZ conversion weights use Observer = 2A. Reference whitepoint for D65
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Illuminant, with XYZ tristimulus values of ``(95.047, 100., 108.883)``.
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References
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----------
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.. [1] http://www.easyrgb.com/index.php?X=MATH&H=16#text16
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.. [2] http://en.wikipedia.org/wiki/CIELUV
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"""
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arr = _prepare_colorarray(luv).copy()
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L, u, v = arr[:, :, 0], arr[:, :, 1], arr[:, :, 2]
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eps = np.finfo(np.float).eps
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# compute y
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y = L.copy()
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mask = y > 7.999625
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y[mask] = np.power((y[mask]+16.) / 116., 3.)
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y[~mask] = y[~mask] / 903.3
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y *= lab_ref_white[1]
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# reference white x,z
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uv_weights = [1, 15, 3]
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u0 = 4*lab_ref_white[0] / np.dot(uv_weights, lab_ref_white)
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v0 = 9*lab_ref_white[1] / np.dot(uv_weights, lab_ref_white)
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# compute intermediate values
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a = u0 + u / (13.*L + eps)
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b = v0 + v / (13.*L + eps)
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c = 3*y * (5*b-3)
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# compute x and z
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z = ((a-4)*c - 15*a*b*y) / (12*b)
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x = -(c/b + 3.*z)
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return np.concatenate([q[..., np.newaxis] for q in [x, y, z]], axis=-1)
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def rgb2luv(rgb):
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"""RGB to CIE-Luv color space conversion.
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Parameters
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----------
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rgb : (M, N, [P,] 3) array_like
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The 3 or 4 dimensional image in RGB format. Final dimension denotes
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channels.
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Returns
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-------
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out : (M, N, [P,] 3) ndarray
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The image in CIE Luv format. Same dimensions as input.
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Raises
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------
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ValueError
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If `rgb` is not a 3-D or 4-D array of shape ``(M, N, [P,] 3)``.
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Notes
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-----
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This function uses rgb2xyz and xyz2luv.
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"""
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return xyz2luv(rgb2xyz(rgb))
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def luv2rgb(luv):
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"""Luv to RGB color space conversion.
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Parameters
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----------
|
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luv : (M, N, [P,] 3) array_like
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The 3 or 4 dimensional image in CIE Luv format. Final dimension denotes
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||||
channels.
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Returns
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||||
-------
|
||||
out : (M, N, [P,] 3) ndarray
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||||
The image in RGB format. Same dimensions as input.
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||||
|
||||
Raises
|
||||
------
|
||||
ValueError
|
||||
If `luv` is not a 3-D or 4-D array of shape ``(M, N, [P,] 3)``.
|
||||
|
||||
Notes
|
||||
-----
|
||||
This function uses luv2xyz and xyz2rgb.
|
||||
"""
|
||||
return xyz2rgb(luv2xyz(luv))
|
||||
|
||||
|
||||
def rgb2hed(rgb):
|
||||
"""RGB to Haematoxylin-Eosin-DAB (HED) color space conversion.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
rgb : array_like
|
||||
The image in RGB format, in a 3-D array of shape (.., .., 3).
|
||||
The image in RGB format, in a 3-D array of shape ``(.., .., 3)``.
|
||||
|
||||
Returns
|
||||
-------
|
||||
out : ndarray
|
||||
The image in HED format, in a 3-D array of shape (.., .., 3).
|
||||
The image in HED format, in a 3-D array of shape ``(.., .., 3)``.
|
||||
|
||||
Raises
|
||||
------
|
||||
ValueError
|
||||
If `rgb` is not a 3-D array of shape (.., .., 3).
|
||||
If `rgb` is not a 3-D array of shape ``(.., .., 3)``.
|
||||
|
||||
|
||||
References
|
||||
@@ -891,17 +1074,17 @@ def hed2rgb(hed):
|
||||
Parameters
|
||||
----------
|
||||
hed : array_like
|
||||
The image in the HED color space, in a 3-D array of shape (.., .., 3).
|
||||
The image in the HED color space, in a 3-D array of shape ``(.., .., 3)``.
|
||||
|
||||
Returns
|
||||
-------
|
||||
out : ndarray
|
||||
The image in RGB, in a 3-D array of shape (.., .., 3).
|
||||
The image in RGB, in a 3-D array of shape ``(.., .., 3)``.
|
||||
|
||||
Raises
|
||||
------
|
||||
ValueError
|
||||
If `hed` is not a 3-D array of shape (.., .., 3).
|
||||
If `hed` is not a 3-D array of shape ``(.., .., 3)``.
|
||||
|
||||
References
|
||||
----------
|
||||
@@ -927,19 +1110,19 @@ def separate_stains(rgb, conv_matrix):
|
||||
Parameters
|
||||
----------
|
||||
rgb : array_like
|
||||
The image in RGB format, in a 3-D array of shape (.., .., 3).
|
||||
The image in RGB format, in a 3-D array of shape ``(.., .., 3)``.
|
||||
conv_matrix: ndarray
|
||||
The stain separation matrix as described by G. Landini [1]_.
|
||||
|
||||
Returns
|
||||
-------
|
||||
out : ndarray
|
||||
The image in stain color space, in a 3-D array of shape (.., .., 3).
|
||||
The image in stain color space, in a 3-D array of shape ``(.., .., 3)``.
|
||||
|
||||
Raises
|
||||
------
|
||||
ValueError
|
||||
If `rgb` is not a 3-D array of shape (.., .., 3).
|
||||
If `rgb` is not a 3-D array of shape ``(.., .., 3)``.
|
||||
|
||||
Notes
|
||||
-----
|
||||
@@ -981,19 +1164,19 @@ def combine_stains(stains, conv_matrix):
|
||||
Parameters
|
||||
----------
|
||||
stains : array_like
|
||||
The image in stain color space, in a 3-D array of shape (.., .., 3).
|
||||
The image in stain color space, in a 3-D array of shape ``(.., .., 3)``.
|
||||
conv_matrix: ndarray
|
||||
The stain separation matrix as described by G. Landini [1]_.
|
||||
|
||||
Returns
|
||||
-------
|
||||
out : ndarray
|
||||
The image in RGB format, in a 3-D array of shape (.., .., 3).
|
||||
The image in RGB format, in a 3-D array of shape ``(.., .., 3)``.
|
||||
|
||||
Raises
|
||||
------
|
||||
ValueError
|
||||
If `stains` is not a 3-D array of shape (.., .., 3).
|
||||
If `stains` is not a 3-D array of shape ``(.., .., 3)``.
|
||||
|
||||
Notes
|
||||
-----
|
||||
@@ -1043,9 +1226,9 @@ def lab2lch(lab):
|
||||
Parameters
|
||||
----------
|
||||
lab : array_like
|
||||
The N-D image in CIE-LAB format. The last (`N+1`th) dimension must have
|
||||
at least 3 elements, corresponding to the ``L``, ``a``, and ``b`` color
|
||||
channels. Subsequent elements are copied.
|
||||
The N-D image in CIE-LAB format. The last (``N+1``-th) dimension must
|
||||
have at least 3 elements, corresponding to the ``L``, ``a``, and ``b``
|
||||
color channels. Subsequent elements are copied.
|
||||
|
||||
Returns
|
||||
-------
|
||||
@@ -1059,7 +1242,7 @@ def lab2lch(lab):
|
||||
|
||||
Notes
|
||||
-----
|
||||
The Hue is expressed as an angle between (0, 2*pi)
|
||||
The Hue is expressed as an angle between ``(0, 2*pi)``
|
||||
|
||||
Examples
|
||||
--------
|
||||
@@ -1079,7 +1262,7 @@ def lab2lch(lab):
|
||||
def _cart2polar_2pi(x, y):
|
||||
"""convert cartesian coordiantes to polar (uses non-standard theta range!)
|
||||
|
||||
NON-STANDARD RANGE! Maps to (0, 2*pi) rather than usual (-pi, +pi)
|
||||
NON-STANDARD RANGE! Maps to ``(0, 2*pi)`` rather than usual ``(-pi, +pi)``
|
||||
"""
|
||||
r, t = np.hypot(x, y), np.arctan2(y, x)
|
||||
t += np.where(t < 0., 2 * np.pi, 0)
|
||||
@@ -1094,9 +1277,9 @@ def lch2lab(lch):
|
||||
Parameters
|
||||
----------
|
||||
lch : array_like
|
||||
The N-D image in CIE-LCH format. The last (`N+1`th) dimension must have
|
||||
at least 3 elements, corresponding to the ``L``, ``a``, and ``b`` color
|
||||
channels. Subsequent elements are copied.
|
||||
The N-D image in CIE-LCH format. The last (``N+1``-th) dimension must
|
||||
have at least 3 elements, corresponding to the ``L``, ``a``, and ``b``
|
||||
color channels. Subsequent elements are copied.
|
||||
|
||||
Returns
|
||||
-------
|
||||
|
||||
@@ -33,6 +33,8 @@ from skimage.color import (rgb2hsv, hsv2rgb,
|
||||
rgb2grey, gray2rgb,
|
||||
xyz2lab, lab2xyz,
|
||||
lab2rgb, rgb2lab,
|
||||
xyz2luv, luv2xyz,
|
||||
luv2rgb, rgb2luv,
|
||||
is_rgb, is_gray,
|
||||
lab2lch, lch2lab,
|
||||
guess_spatial_dimensions
|
||||
@@ -69,17 +71,24 @@ class TestColorconv(TestCase):
|
||||
colbars_point75_array = np.swapaxes(colbars_point75.reshape(3, 4, 2), 0, 2)
|
||||
|
||||
xyz_array = np.array([[[0.4124, 0.21260, 0.01930]], # red
|
||||
[[0, 0, 0]], # black
|
||||
[[.9505, 1., 1.089]], # white
|
||||
[[.1805, .0722, .9505]], # blue
|
||||
[[.07719, .15438, .02573]], # green
|
||||
])
|
||||
[[0, 0, 0]], # black
|
||||
[[.9505, 1., 1.089]], # white
|
||||
[[.1805, .0722, .9505]], # blue
|
||||
[[.07719, .15438, .02573]], # green
|
||||
])
|
||||
lab_array = np.array([[[53.233, 80.109, 67.220]], # red
|
||||
[[0., 0., 0.]], # black
|
||||
[[100.0, 0.005, -0.010]], # white
|
||||
[[32.303, 79.197, -107.864]], # blue
|
||||
[[46.229, -51.7, 49.898]], # green
|
||||
])
|
||||
[[0., 0., 0.]], # black
|
||||
[[100.0, 0.005, -0.010]], # white
|
||||
[[32.303, 79.197, -107.864]], # blue
|
||||
[[46.229, -51.7, 49.898]], # green
|
||||
])
|
||||
|
||||
luv_array = np.array([[[53.233, 175.053, 37.751]], # red
|
||||
[[0., 0., 0.]], # black
|
||||
[[100., 0.001, -0.017]], # white
|
||||
[[32.303, -9.400, -130.358]], # blue
|
||||
[[46.228, -43.774, 56.589]], # green
|
||||
])
|
||||
|
||||
# RGB to HSV
|
||||
def test_rgb2hsv_conversion(self):
|
||||
@@ -250,6 +259,41 @@ class TestColorconv(TestCase):
|
||||
img_rgb = img_as_float(self.img_rgb)
|
||||
assert_array_almost_equal(lab2rgb(rgb2lab(img_rgb)), img_rgb)
|
||||
|
||||
# test matrices for xyz2luv and luv2xyz generated using
|
||||
# http://www.easyrgb.com/index.php?X=CALC
|
||||
# Note: easyrgb website displays xyz*100
|
||||
def test_xyz2luv(self):
|
||||
assert_array_almost_equal(xyz2luv(self.xyz_array),
|
||||
self.luv_array, decimal=3)
|
||||
|
||||
def test_luv2xyz(self):
|
||||
assert_array_almost_equal(luv2xyz(self.luv_array),
|
||||
self.xyz_array, decimal=3)
|
||||
|
||||
def test_rgb2luv_brucelindbloom(self):
|
||||
"""
|
||||
Test the RGB->Lab conversion by comparing to the calculator on the
|
||||
authoritative Bruce Lindbloom
|
||||
[website](http://brucelindbloom.com/index.html?ColorCalculator.html).
|
||||
"""
|
||||
# Obtained with D65 white point, sRGB model and gamma
|
||||
gt_for_colbars = np.array([
|
||||
[100, 0, 0],
|
||||
[97.1393, 7.7056, 106.7866],
|
||||
[91.1132, -70.4773, -15.2042],
|
||||
[87.7347, -83.0776, 107.3985],
|
||||
[60.3242, 84.0714, -108.6834],
|
||||
[53.2408, 175.0151, 37.7564],
|
||||
[32.2970, -9.4054, -130.3423],
|
||||
[0, 0, 0]]).T
|
||||
gt_array = np.swapaxes(gt_for_colbars.reshape(3, 4, 2), 0, 2)
|
||||
assert_array_almost_equal(rgb2luv(self.colbars_array),
|
||||
gt_array, decimal=2)
|
||||
|
||||
def test_luv_rgb_roundtrip(self):
|
||||
img_rgb = img_as_float(self.img_rgb)
|
||||
assert_array_almost_equal(luv2rgb(rgb2luv(img_rgb)), img_rgb)
|
||||
|
||||
def test_lab_lch_roundtrip(self):
|
||||
rgb = img_as_float(self.img_rgb)
|
||||
lab = rgb2lab(rgb)
|
||||
|
||||
Reference in New Issue
Block a user