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Module: draw

skimage.draw.bezier_curve(r0, c0, r1, c1, …) Generate Bezier curve coordinates.
skimage.draw.circle(r, c, radius[, shape]) Generate coordinates of pixels within circle.
skimage.draw.circle_perimeter(r, c, radius) Generate circle perimeter coordinates.
skimage.draw.circle_perimeter_aa(r, c, radius) Generate anti-aliased circle perimeter coordinates.
skimage.draw.ellipse(r, c, r_radius, c_radius) Generate coordinates of pixels within ellipse.
skimage.draw.ellipse_perimeter(r, c, …[, …]) Generate ellipse perimeter coordinates.
skimage.draw.ellipsoid(a, b, c[, spacing, …]) Generates ellipsoid with semimajor axes aligned with grid dimensions on grid with specified spacing.
skimage.draw.ellipsoid_stats(a, b, c) Calculates analytical surface area and volume for ellipsoid with semimajor axes aligned with grid dimensions of specified spacing.
skimage.draw.line(r0, c0, r1, c1) Generate line pixel coordinates.
skimage.draw.line_aa(r0, c0, r1, c1) Generate anti-aliased line pixel coordinates.
skimage.draw.polygon(r, c[, shape]) Generate coordinates of pixels within polygon.
skimage.draw.polygon_perimeter(r, c[, …]) Generate polygon perimeter coordinates.
skimage.draw.set_color(img, coords, color[, …]) Set pixel color in the image at the given coordinates.
skimage.draw.draw
skimage.draw.draw3d

bezier_curve

skimage.draw.bezier_curve(r0, c0, r1, c1, r2, c2, weight, shape=None)[source]

Generate Bezier curve coordinates.

Parameters:

r0, c0 : int

Coordinates of the first control point.

r1, c1 : int

Coordinates of the middle control point.

r2, c2 : int

Coordinates of the last control point.

weight : double

Middle control point weight, it describes the line tension.

shape : tuple, optional

Image shape which is used to determine the maximum extent of output pixel coordinates. This is useful for curves that exceed the image size. If None, the full extent of the curve is used.

Returns:

rr, cc : (N,) ndarray of int

Indices of pixels that belong to the Bezier curve. May be used to directly index into an array, e.g. img[rr, cc] = 1.

Notes

The algorithm is the rational quadratic algorithm presented in reference [R99].

References

[R99](1, 2) A Rasterizing Algorithm for Drawing Curves, A. Zingl, 2012 http://members.chello.at/easyfilter/Bresenham.pdf

Examples

>>> import numpy as np
>>> from skimage.draw import bezier_curve
>>> img = np.zeros((10, 10), dtype=np.uint8)
>>> rr, cc = bezier_curve(1, 5, 5, -2, 8, 8, 2)
>>> img[rr, cc] = 1
>>> img
array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 1, 0, 0, 0, 0],
       [0, 0, 0, 1, 1, 0, 0, 0, 0, 0],
       [0, 0, 1, 0, 0, 0, 0, 0, 0, 0],
       [0, 1, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 1, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 1, 1, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 1, 1, 1, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 1, 1, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=uint8)

circle

skimage.draw.circle(r, c, radius, shape=None)[source]

Generate coordinates of pixels within circle.

Parameters:

r, c : double

Centre coordinate of circle.

radius : double

Radius of circle.

shape : tuple, optional

Image shape which is used to determine the maximum extent of output pixel coordinates. This is useful for circles that exceed the image size. If None, the full extent of the circle is used.

Returns:

rr, cc : ndarray of int

Pixel coordinates of circle. May be used to directly index into an array, e.g. img[rr, cc] = 1.

Examples

>>> from skimage.draw import circle
>>> img = np.zeros((10, 10), dtype=np.uint8)
>>> rr, cc = circle(4, 4, 5)
>>> img[rr, cc] = 1
>>> img
array([[0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
       [0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
       [0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
       [0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=uint8)

circle_perimeter

skimage.draw.circle_perimeter(r, c, radius, method='bresenham', shape=None)[source]

Generate circle perimeter coordinates.

Parameters:

r, c : int

Centre coordinate of circle.

radius: int

Radius of circle.

method : {‘bresenham’, ‘andres’}, optional

bresenham : Bresenham method (default) andres : Andres method

shape : tuple, optional

Image shape which is used to determine the maximum extent of output pixel coordinates. This is useful for circles that exceed the image size. If None, the full extent of the circle is used.

Returns:

rr, cc : (N,) ndarray of int

Bresenham and Andres’ method: Indices of pixels that belong to the circle perimeter. May be used to directly index into an array, e.g. img[rr, cc] = 1.

Notes

Andres method presents the advantage that concentric circles create a disc whereas Bresenham can make holes. There is also less distortions when Andres circles are rotated. Bresenham method is also known as midpoint circle algorithm. Anti-aliased circle generator is available with circle_perimeter_aa.

References

[R100]J.E. Bresenham, “Algorithm for computer control of a digital plotter”, IBM Systems journal, 4 (1965) 25-30.
[R101]E. Andres, “Discrete circles, rings and spheres”, Computers & Graphics, 18 (1994) 695-706.

Examples

>>> from skimage.draw import circle_perimeter
>>> img = np.zeros((10, 10), dtype=np.uint8)
>>> rr, cc = circle_perimeter(4, 4, 3)
>>> img[rr, cc] = 1
>>> img
array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 1, 1, 1, 0, 0, 0, 0],
       [0, 0, 1, 0, 0, 0, 1, 0, 0, 0],
       [0, 1, 0, 0, 0, 0, 0, 1, 0, 0],
       [0, 1, 0, 0, 0, 0, 0, 1, 0, 0],
       [0, 1, 0, 0, 0, 0, 0, 1, 0, 0],
       [0, 0, 1, 0, 0, 0, 1, 0, 0, 0],
       [0, 0, 0, 1, 1, 1, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=uint8)

circle_perimeter_aa

skimage.draw.circle_perimeter_aa(r, c, radius, shape=None)[source]

Generate anti-aliased circle perimeter coordinates.

Parameters:

r, c : int

Centre coordinate of circle.

radius: int

Radius of circle.

shape : tuple, optional

Image shape which is used to determine the maximum extent of output pixel coordinates. This is useful for circles that exceed the image size. If None, the full extent of the circle is used.

Returns:

rr, cc, val : (N,) ndarray (int, int, float)

Indices of pixels (rr, cc) and intensity values (val). img[rr, cc] = val.

Notes

Wu’s method draws anti-aliased circle. This implementation doesn’t use lookup table optimization.

References

[R102]X. Wu, “An efficient antialiasing technique”, In ACM SIGGRAPH Computer Graphics, 25 (1991) 143-152.

Examples

>>> from skimage.draw import circle_perimeter_aa
>>> img = np.zeros((10, 10), dtype=np.uint8)
>>> rr, cc, val = circle_perimeter_aa(4, 4, 3)
>>> img[rr, cc] = val * 255
>>> img
array([[  0,   0,   0,   0,   0,   0,   0,   0,   0,   0],
       [  0,   0,  60, 211, 255, 211,  60,   0,   0,   0],
       [  0,  60, 194,  43,   0,  43, 194,  60,   0,   0],
       [  0, 211,  43,   0,   0,   0,  43, 211,   0,   0],
       [  0, 255,   0,   0,   0,   0,   0, 255,   0,   0],
       [  0, 211,  43,   0,   0,   0,  43, 211,   0,   0],
       [  0,  60, 194,  43,   0,  43, 194,  60,   0,   0],
       [  0,   0,  60, 211, 255, 211,  60,   0,   0,   0],
       [  0,   0,   0,   0,   0,   0,   0,   0,   0,   0],
       [  0,   0,   0,   0,   0,   0,   0,   0,   0,   0]], dtype=uint8)

ellipse

skimage.draw.ellipse(r, c, r_radius, c_radius, shape=None, rotation=0.0)[source]

Generate coordinates of pixels within ellipse.

Parameters:

r, c : double

Centre coordinate of ellipse.

r_radius, c_radius : double

Minor and major semi-axes. (r/r_radius)**2 + (c/c_radius)**2 = 1.

shape : tuple, optional

Image shape which is used to determine the maximum extent of output pixel coordinates. This is useful for ellipses which exceed the image size. By default the full extent of the ellipse are used.

rotation : float, optional (default 0.)

Set the ellipse rotation (rotation) in range (-PI, PI) in contra clock wise direction, so PI/2 degree means swap ellipse axis

Returns:

rr, cc : ndarray of int

Pixel coordinates of ellipse. May be used to directly index into an array, e.g. img[rr, cc] = 1.

Notes

The ellipse equation:

((x * cos(alpha) + y * sin(alpha)) / x_radius) ** 2 +
((x * sin(alpha) - y * cos(alpha)) / y_radius) ** 2 = 1

Note that the positions of ellipse without specified shape can have also, negative values, as this is correct on the plane. On the other hand using these ellipse positions for an image afterwards may lead to appearing on the other side of image, because image[-1, -1] = image[end-1, end-1]

>>> rr, cc = ellipse(1, 2, 3, 6)
>>> img = np.zeros((6, 12), dtype=np.uint8)
>>> img[rr, cc] = 1
>>> img
array([[1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1],
       [1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1],
       [1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1],
       [1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1]], dtype=uint8)

Examples

>>> from skimage.draw import ellipse
>>> img = np.zeros((10, 12), dtype=np.uint8)
>>> rr, cc = ellipse(5, 6, 3, 5, rotation=np.deg2rad(30))
>>> img[rr, cc] = 1
>>> img
array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0],
       [0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0],
       [0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0],
       [0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
       [0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0],
       [0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0],
       [0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=uint8)

ellipse_perimeter

skimage.draw.ellipse_perimeter(r, c, r_radius, c_radius, orientation=0, shape=None)[source]

Generate ellipse perimeter coordinates.

Parameters:

r, c : int

Centre coordinate of ellipse.

r_radius, c_radius : int

Minor and major semi-axes. (r/r_radius)**2 + (c/c_radius)**2 = 1.

orientation : double, optional

Major axis orientation in clockwise direction as radians.

shape : tuple, optional

Image shape which is used to determine the maximum extent of output pixel coordinates. This is useful for ellipses that exceed the image size. If None, the full extent of the ellipse is used.

Returns:

rr, cc : (N,) ndarray of int

Indices of pixels that belong to the ellipse perimeter. May be used to directly index into an array, e.g. img[rr, cc] = 1.

References

[R103]A Rasterizing Algorithm for Drawing Curves, A. Zingl, 2012 http://members.chello.at/easyfilter/Bresenham.pdf

Examples

>>> from skimage.draw import ellipse_perimeter
>>> img = np.zeros((10, 10), dtype=np.uint8)
>>> rr, cc = ellipse_perimeter(5, 5, 3, 4)
>>> img[rr, cc] = 1
>>> img
array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 1, 1, 1, 1, 1, 0, 0],
       [0, 0, 1, 0, 0, 0, 0, 0, 1, 0],
       [0, 1, 0, 0, 0, 0, 0, 0, 0, 1],
       [0, 1, 0, 0, 0, 0, 0, 0, 0, 1],
       [0, 1, 0, 0, 0, 0, 0, 0, 0, 1],
       [0, 0, 1, 0, 0, 0, 0, 0, 1, 0],
       [0, 0, 0, 1, 1, 1, 1, 1, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=uint8)

Note that the positions of ellipse without specified shape can have also, negative values, as this is correct on the plane. On the other hand using these ellipse positions for an image afterwards may lead to appearing on the other side of image, because image[-1, -1] = image[end-1, end-1]

>>> rr, cc = ellipse_perimeter(2, 3, 4, 5)
>>> img = np.zeros((9, 12), dtype=np.uint8)
>>> img[rr, cc] = 1
>>> img
array([[0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1],
       [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0],
       [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1],
       [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
       [0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0],
       [0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0],
       [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]], dtype=uint8)

ellipsoid

skimage.draw.ellipsoid(a, b, c, spacing=(1.0, 1.0, 1.0), levelset=False)[source]

Generates ellipsoid with semimajor axes aligned with grid dimensions on grid with specified spacing.

Parameters:

a : float

Length of semimajor axis aligned with x-axis.

b : float

Length of semimajor axis aligned with y-axis.

c : float

Length of semimajor axis aligned with z-axis.

spacing : tuple of floats, length 3

Spacing in (x, y, z) spatial dimensions.

levelset : bool

If True, returns the level set for this ellipsoid (signed level set about zero, with positive denoting interior) as np.float64. False returns a binarized version of said level set.

Returns:

ellip : (N, M, P) array

Ellipsoid centered in a correctly sized array for given spacing. Boolean dtype unless levelset=True, in which case a float array is returned with the level set above 0.0 representing the ellipsoid.

ellipsoid_stats

skimage.draw.ellipsoid_stats(a, b, c)[source]

Calculates analytical surface area and volume for ellipsoid with semimajor axes aligned with grid dimensions of specified spacing.

Parameters:

a : float

Length of semimajor axis aligned with x-axis.

b : float

Length of semimajor axis aligned with y-axis.

c : float

Length of semimajor axis aligned with z-axis.

Returns:

vol : float

Calculated volume of ellipsoid.

surf : float

Calculated surface area of ellipsoid.

line

skimage.draw.line(r0, c0, r1, c1)[source]

Generate line pixel coordinates.

Parameters:

r0, c0 : int

Starting position (row, column).

r1, c1 : int

End position (row, column).

Returns:

rr, cc : (N,) ndarray of int

Indices of pixels that belong to the line. May be used to directly index into an array, e.g. img[rr, cc] = 1.

Notes

Anti-aliased line generator is available with line_aa.

Examples

>>> from skimage.draw import line
>>> img = np.zeros((10, 10), dtype=np.uint8)
>>> rr, cc = line(1, 1, 8, 8)
>>> img[rr, cc] = 1
>>> img
array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 1, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 1, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 1, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 1, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 1, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 1, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=uint8)

line_aa

skimage.draw.line_aa(r0, c0, r1, c1)[source]

Generate anti-aliased line pixel coordinates.

Parameters:

r0, c0 : int

Starting position (row, column).

r1, c1 : int

End position (row, column).

Returns:

rr, cc, val : (N,) ndarray (int, int, float)

Indices of pixels (rr, cc) and intensity values (val). img[rr, cc] = val.

References

[R104]A Rasterizing Algorithm for Drawing Curves, A. Zingl, 2012 http://members.chello.at/easyfilter/Bresenham.pdf

Examples

>>> from skimage.draw import line_aa
>>> img = np.zeros((10, 10), dtype=np.uint8)
>>> rr, cc, val = line_aa(1, 1, 8, 8)
>>> img[rr, cc] = val * 255
>>> img
array([[  0,   0,   0,   0,   0,   0,   0,   0,   0,   0],
       [  0, 255,  74,   0,   0,   0,   0,   0,   0,   0],
       [  0,  74, 255,  74,   0,   0,   0,   0,   0,   0],
       [  0,   0,  74, 255,  74,   0,   0,   0,   0,   0],
       [  0,   0,   0,  74, 255,  74,   0,   0,   0,   0],
       [  0,   0,   0,   0,  74, 255,  74,   0,   0,   0],
       [  0,   0,   0,   0,   0,  74, 255,  74,   0,   0],
       [  0,   0,   0,   0,   0,   0,  74, 255,  74,   0],
       [  0,   0,   0,   0,   0,   0,   0,  74, 255,   0],
       [  0,   0,   0,   0,   0,   0,   0,   0,   0,   0]], dtype=uint8)

polygon

skimage.draw.polygon(r, c, shape=None)[source]

Generate coordinates of pixels within polygon.

Parameters:

r : (N,) ndarray

Row coordinates of vertices of polygon.

c : (N,) ndarray

Column coordinates of vertices of polygon.

shape : tuple, optional

Image shape which is used to determine the maximum extent of output pixel coordinates. This is useful for polygons that exceed the image size. If None, the full extent of the polygon is used.

Returns:

rr, cc : ndarray of int

Pixel coordinates of polygon. May be used to directly index into an array, e.g. img[rr, cc] = 1.

Examples

>>> from skimage.draw import polygon
>>> img = np.zeros((10, 10), dtype=np.uint8)
>>> r = np.array([1, 2, 8, 1])
>>> c = np.array([1, 7, 4, 1])
>>> rr, cc = polygon(r, c)
>>> img[rr, cc] = 1
>>> img
array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
       [0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
       [0, 0, 0, 1, 1, 1, 0, 0, 0, 0],
       [0, 0, 0, 1, 1, 1, 0, 0, 0, 0],
       [0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=uint8)

polygon_perimeter

skimage.draw.polygon_perimeter(r, c, shape=None, clip=False)[source]

Generate polygon perimeter coordinates.

Parameters:

r : (N,) ndarray

Row coordinates of vertices of polygon.

c : (N,) ndarray

Column coordinates of vertices of polygon.

shape : tuple, optional

Image shape which is used to determine maximum extents of output pixel coordinates. This is useful for polygons that exceed the image size. If None, the full extents of the polygon is used.

clip : bool, optional

Whether to clip the polygon to the provided shape. If this is set to True, the drawn figure will always be a closed polygon with all edges visible.

Returns:

rr, cc : ndarray of int

Pixel coordinates of polygon. May be used to directly index into an array, e.g. img[rr, cc] = 1.

Examples

>>> from skimage.draw import polygon_perimeter
>>> img = np.zeros((10, 10), dtype=np.uint8)
>>> rr, cc = polygon_perimeter([5, -1, 5, 10],
...                            [-1, 5, 11, 5],
...                            shape=img.shape, clip=True)
>>> img[rr, cc] = 1
>>> img
array([[0, 0, 0, 0, 1, 1, 1, 0, 0, 0],
       [0, 0, 0, 1, 0, 0, 0, 1, 0, 0],
       [0, 0, 1, 0, 0, 0, 0, 0, 1, 0],
       [0, 1, 0, 0, 0, 0, 0, 0, 0, 1],
       [1, 0, 0, 0, 0, 0, 0, 0, 0, 1],
       [1, 0, 0, 0, 0, 0, 0, 0, 0, 1],
       [1, 0, 0, 0, 0, 0, 0, 0, 0, 1],
       [0, 1, 1, 0, 0, 0, 0, 0, 0, 1],
       [0, 0, 0, 1, 0, 0, 0, 1, 1, 0],
       [0, 0, 0, 0, 1, 1, 1, 0, 0, 0]], dtype=uint8)

set_color

skimage.draw.set_color(img, coords, color, alpha=1)[source]

Set pixel color in the image at the given coordinates.

Coordinates that exceed the shape of the image will be ignored.

Parameters:

img : (M, N, D) ndarray

Image

coords : tuple of ((P,) ndarray, (P,) ndarray)

Row and column coordinates of pixels to be colored.

color : (D,) ndarray

Color to be assigned to coordinates in the image.

alpha : scalar or (N,) ndarray

Alpha values used to blend color with image. 0 is transparent, 1 is opaque.

Returns:

img : (M, N, D) ndarray

The updated image.

Examples

>>> from skimage.draw import line, set_color
>>> img = np.zeros((10, 10), dtype=np.uint8)
>>> rr, cc = line(1, 1, 20, 20)
>>> set_color(img, (rr, cc), 1)
>>> img
array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 1, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 1, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 1, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 1, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 1, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 1, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 1]], dtype=uint8)