PIL: Generating Vertical Gradient Image

Question

In Android, I used the following code to generate a gradient background that I need:

<gradient
    android:angle="90"
    android:startColor="#40000000"
    android:endColor="#00000000"
    android:type="linear" />

The background goes from light to relatively dark from top to bottom. I wonder how to do the same in Python with PIL, since I need the same effect on another program written in Python.

Answer 1

Here's something that shows ways to draw multicolor rectangular horizontal and vertical gradients.

rom PIL import Image, ImageDraw

BLACK, DARKGRAY, GRAY = ((0,0,0), (63,63,63), (127,127,127))
LIGHTGRAY, WHITE = ((191,191,191), (255,255,255))
BLUE, GREEN, RED = ((0, 0, 255), (0, 255, 0), (255, 0, 0))


class Point(object):
    def __init__(self, x, y):
        self.x, self.y = x, y

class Rect(object):
    def __init__(self, x1, y1, x2, y2):
        minx, maxx = (x1,x2) if x1 < x2 else (x2,x1)
        miny, maxy = (y1,y2) if y1 < y2 else (y2,y1)
        self.min = Point(minx, miny)
        self.max = Point(maxx, maxy)

    width  = property(lambda self: self.max.x - self.min.x)
    height = property(lambda self: self.max.y - self.min.y)


def gradient_color(minval, maxval, val, color_palette):
    """ Computes intermediate RGB color of a value in the range of minval
        to maxval (inclusive) based on a color_palette representing the range.
    """
    max_index = len(color_palette)-1
    delta = maxval - minval
    if delta == 0:
        delta = 1
    v = float(val-minval) / delta * max_index
    i1, i2 = int(v), min(int(v)+1, max_index)
    (r1, g1, b1), (r2, g2, b2) = color_palette[i1], color_palette[i2]
    f = v - i1
    return int(r1 + f*(r2-r1)), int(g1 + f*(g2-g1)), int(b1 + f*(b2-b1))

def horz_gradient(draw, rect, color_func, color_palette):
    minval, maxval = 1, len(color_palette)
    delta = maxval - minval
    width = float(rect.width)  # Cache.
    for x in range(rect.min.x, rect.max.x+1):
        f = (x - rect.min.x) / width
        val = minval + f * delta
        color = color_func(minval, maxval, val, color_palette)
        draw.line([(x, rect.min.y), (x, rect.max.y)], fill=color)

def vert_gradient(draw, rect, color_func, color_palette):
    minval, maxval = 1, len(color_palette)
    delta = maxval - minval
    height = float(rect.height)  # Cache.
    for y in range(rect.min.y, rect.max.y+1):
        f = (y - rect.min.y) / height
        val = minval + f * delta
        color = color_func(minval, maxval, val, color_palette)
        draw.line([(rect.min.x, y), (rect.max.x, y)], fill=color)


if __name__ == '__main__':
    # Draw a three color vertical gradient.
    color_palette = [BLUE, GREEN, RED]
    region = Rect(0, 0, 730, 350)
    width, height = region.max.x+1, region.max.y+1
    image = Image.new("RGB", (width, height), WHITE)
    draw = ImageDraw.Draw(image)
    vert_gradient(draw, region, gradient_color, color_palette)
    image.show()
    #image.save("vert_gradient.png", "PNG")
    #print('image saved')

And here's the image it generates and displays:

This calculates the intermediate colors in the RGB color space, but other colorspaces could be used — for examples compare results of my answers to the question Range values to pseudocolor.

This could easily be extended to generate RGBA (RGB+Alpha) mode images.

Answer 2

If you only need two colours, this can be done very simply:

def generate_gradient(
        colour1: str, colour2: str, width: int, height: int) -> Image:
    """Generate a vertical gradient."""
    base = Image.new('RGB', (width, height), colour1)
    top = Image.new('RGB', (width, height), colour2)
    mask = Image.new('L', (width, height))
    mask_data = []
    for y in range(height):
        mask_data.extend([int(255 * (y / height))] * width)
    mask.putdata(mask_data)
    base.paste(top, (0, 0), mask)
    return base

This creates a layer in each colour, then creates a mask with transparency varying according to the y position. You can replace y / height in line 10 with x / width for a horizontal gradient, or any function of x and y for another gradient.