"""Deals with making images (np arrays). It provides drawing
methods that are difficult to do with the existing Python libraries.
"""
import numpy as np
[docs]
def color_gradient(
size,
p1,
p2=None,
vector=None,
radius=None,
color_1=0.0,
color_2=1.0,
shape="linear",
offset=0,
):
"""Draw a linear, bilinear, or radial gradient.
The result is a picture of size ``size``, whose color varies
gradually from color `color_1` in position ``p1`` to color ``color_2``
in position ``p2``.
If it is a RGB picture the result must be transformed into
a 'uint8' array to be displayed normally:
Parameters
----------
size : tuple or list
Size (width, height) in pixels of the final image array.
p1 : tuple or list
Position for the first coordinate of the gradient in pixels (x, y).
The color 'before' ``p1`` is ``color_1`` and it gradually changes in
the direction of ``p2`` until it is ``color_2`` when it reaches ``p2``.
p2 : tuple or list, optional
Position for the second coordinate of the gradient in pixels (x, y).
Coordinates (x, y) of the limit point for ``color_1``
and ``color_2``.
vector : tuple or list, optional
A vector (x, y) in pixels that can be provided instead of ``p2``.
``p2`` is then defined as (p1 + vector).
color_1 : tuple or list, optional
Starting color for the gradient. As default, black. Either floats
between 0 and 1 (for gradients used in masks) or [R, G, B] arrays
(for colored gradients).
color_2 : tuple or list, optional
Color for the second point in the gradient. As default, white. Either
floats between 0 and 1 (for gradients used in masks) or [R, G, B]
arrays (for colored gradients).
shape : str, optional
Shape of the gradient. Can be either ``"linear"``, ``"bilinear"`` or
``"circular"``. In a linear gradient the color varies in one direction,
from point ``p1`` to point ``p2``. In a bilinear gradient it also
varies symmetrically from ``p1`` in the other direction. In a circular
gradient it goes from ``color_1`` to ``color_2`` in all directions.
radius : float, optional
If ``shape="radial"``, the radius of the gradient is defined with the
parameter ``radius``, in pixels.
offset : float, optional
Real number between 0 and 1 indicating the fraction of the vector
at which the gradient actually starts. For instance if ``offset``
is 0.9 in a gradient going from p1 to p2, then the gradient will
only occur near p2 (before that everything is of color ``color_1``)
If the offset is 0.9 in a radial gradient, the gradient will
occur in the region located between 90% and 100% of the radius,
this creates a blurry disc of radius ``d(p1, p2)``.
Returns
-------
image
An Numpy array of dimensions (width, height, n_colors) of type float
representing the image of the gradient.
Examples
--------
.. code:: python
color_gradient((10, 1), (0, 0), p2=(10, 0)) # from white to black
#[[1. 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1]]
# from red to green
color_gradient(
(10, 1), (0, 0),
p2=(10, 0),
color_1=(255, 0, 0),
color_2=(0, 255, 0)
)
# [[[ 0. 255. 0. ]
# [ 25.5 229.5 0. ]
# [ 51. 204. 0. ]
# [ 76.5 178.5 0. ]
# [102. 153. 0. ]
# [127.5 127.5 0. ]
# [153. 102. 0. ]
# [178.5 76.5 0. ]
# [204. 51. 0. ]
# [229.5 25.5 0. ]]]
"""
# np-arrayize and change x,y coordinates to y,x
w, h = size
color_1 = np.array(color_1).astype(float)
color_2 = np.array(color_2).astype(float)
if shape == "bilinear":
if vector is None:
if p2 is None:
raise ValueError("You must provide either 'p2' or 'vector'")
vector = np.array(p2) - np.array(p1)
m1, m2 = [
color_gradient(
size,
p1,
vector=v,
color_1=1.0,
color_2=0.0,
shape="linear",
offset=offset,
)
for v in [vector, [-v for v in vector]]
]
arr = np.maximum(m1, m2)
if color_1.size > 1:
arr = np.dstack(3 * [arr])
return arr * color_1 + (1 - arr) * color_2
p1 = np.array(p1[::-1]).astype(float)
M = np.dstack(np.meshgrid(range(w), range(h))[::-1]).astype(float)
if shape == "linear":
if vector is None:
if p2 is not None:
vector = np.array(p2[::-1]) - p1
else:
raise ValueError("You must provide either 'p2' or 'vector'")
else:
vector = np.array(vector[::-1])
norm = np.linalg.norm(vector)
n_vec = vector / norm**2 # norm 1/norm(vector)
p1 = p1 + offset * vector
arr = (M - p1).dot(n_vec) / (1 - offset)
arr = np.minimum(1, np.maximum(0, arr))
if color_1.size > 1:
arr = np.dstack(3 * [arr])
return arr * color_1 + (1 - arr) * color_2
elif shape == "radial":
if (radius or 0) == 0:
arr = np.ones((h, w))
else:
arr = (np.sqrt(((M - p1) ** 2).sum(axis=2))) - offset * radius
arr = arr / ((1 - offset) * radius)
arr = np.minimum(1.0, np.maximum(0, arr))
if color_1.size > 1:
arr = np.dstack(3 * [arr])
return (1 - arr) * color_1 + arr * color_2
raise ValueError("Invalid shape, should be either 'radial', 'linear' or 'bilinear'")
[docs]
def color_split(
size,
x=None,
y=None,
p1=None,
p2=None,
vector=None,
color_1=0,
color_2=1.0,
gradient_width=0,
):
"""Make an image split in 2 colored regions.
Returns an array of size ``size`` divided in two regions called 1 and
2 in what follows, and which will have colors color_1 and color_2
respectively.
Parameters
----------
x : int, optional
If provided, the image is split horizontally in x, the left
region being region 1.
y : int, optional
If provided, the image is split vertically in y, the top region
being region 1.
p1, p2: tuple or list, optional
Positions (x1, y1), (x2, y2) in pixels, where the numbers can be
floats. Region 1 is defined as the whole region on the left when
going from ``p1`` to ``p2``.
p1, vector: tuple or list, optional
``p1`` is (x1,y1) and vector (v1,v2), where the numbers can be
floats. Region 1 is then the region on the left when starting
in position ``p1`` and going in the direction given by ``vector``.
gradient_width : float, optional
If not zero, the split is not sharp, but gradual over a region of
width ``gradient_width`` (in pixels). This is preferable in many
situations (for instance for antialiasing).
Examples
--------
.. code:: python
size = [200, 200]
# an image with all pixels with x<50 =0, the others =1
color_split(size, x=50, color_1=0, color_2=1)
# an image with all pixels with y<50 red, the others green
color_split(size, x=50, color_1=[255, 0, 0], color_2=[0, 255, 0])
# An image split along an arbitrary line (see below)
color_split(size, p1=[20, 50], p2=[25, 70], color_1=0, color_2=1)
"""
if gradient_width or ((x is None) and (y is None)):
if p2 is not None:
vector = np.array(p2) - np.array(p1)
elif x is not None:
vector = np.array([0, -1.0])
p1 = np.array([x, 0])
elif y is not None:
vector = np.array([1.0, 0.0])
p1 = np.array([0, y])
x, y = vector
vector = np.array([y, -x]).astype("float")
norm = np.linalg.norm(vector)
vector = max(0.1, gradient_width) * vector / norm
return color_gradient(
size, p1, vector=vector, color_1=color_1, color_2=color_2, shape="linear"
)
else:
w, h = size
shape = (h, w) if np.isscalar(color_1) else (h, w, len(color_1))
arr = np.zeros(shape)
if x:
arr[:, :x] = color_1
arr[:, x:] = color_2
elif y:
arr[:y] = color_1
arr[y:] = color_2
return arr
[docs]
def circle(screensize, center, radius, color=1.0, bg_color=0, blur=1):
"""Draw an image with a circle.
Draws a circle of color ``color``, on a background of color ``bg_color``,
on a screen of size ``screensize`` at the position ``center=(x, y)``,
with a radius ``radius`` but slightly blurred on the border by ``blur``
pixels.
Parameters
----------
screensize : tuple or list
Size of the canvas.
center : tuple or list
Center of the circle.
radius : float
Radius of the circle, in pixels.
bg_color : tuple or float, optional
Color for the background of the canvas. As default, black.
blur : float, optional
Blur for the border of the circle.
Examples
--------
.. code:: python
from moviepy.video.tools.drawing import circle
circle(
(5, 5), # size
(2, 2), # center
2, # radius
)
# array([[0. , 0. , 0. , 0. , 0. ],
# [0. , 0.58578644, 1. , 0.58578644, 0. ],
# [0. , 1. , 1. , 1. , 0. ],
# [0. , 0.58578644, 1. , 0.58578644, 0. ],
# [0. , 0. , 0. , 0. , 0. ]])
"""
offset = 1.0 * (radius - blur) / radius if radius else 0
return color_gradient(
screensize,
p1=center,
radius=radius,
color_1=color,
color_2=bg_color,
shape="radial",
offset=offset,
)
