使用python图像库绘制抗锯齿线

2024-04-27 00:38:56 发布

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我正在用Python Imaging库的ImageDraw.line()绘制一些线,但是它们看起来很可怕,因为我找不到反别名的方法。如何在PIL中反别名行?如果PIL不能做到这一点,是否还有另一个Python图像处理库可以做到这一点?


Tags: 方法pilline绘制图像处理imagingimagedraw
3条回答

aggdraw比PIL提供更好的绘图。

我有一个类似的问题,我的线条在改变方向的地方有粗糙的边缘。我从IOS中画线的方式中得到了一条线索,并给出了这段代码。它把圆形的线帽放在线的末端,真正的清理东西。不完全是反走样,但完全是新的皮尔和有这么难找到一个答案,我想我会分享。需要一些调整,也许有更好的方法,但做我需要的:)


    from PIL import Image
    import ImageDraw

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

    class DrawLines:
        def draw(self, points, color, imageName):
            img = Image.new("RGBA", [1440,1080], (255,255,255,0))
            draw  =  ImageDraw.Draw(img)
            linePoints = []
            for point in points:
                draw.ellipse((point.x-7, point.y-7, point.x+7, point.y+7), fill=color)
                linePoints.append(point.x)
                linePoints.append(point.y)
            draw.line(linePoints, fill=color, width=14)
            img.save(imageName)

    p1 = Point(100,200)
    p2 = Point(190,250)
    points = [p1,p2]

    red = (255,0,0)
    drawLines = DrawLines()
    drawLines.draw(points, red, "C:\\test.png")

这是一个很快被黑在一起的功能,以绘制一个反锯齿线与皮尔,我写了相同的问题后,看到这篇文章,并未能安装aggdraw和在一个紧的最后期限。这是吴小林线算法的一个实现。我希望它能帮助任何人搜索相同的东西!!

:)

"""Library to draw an antialiased line."""
# http://stackoverflow.com/questions/3122049/drawing-an-anti-aliased-line-with-thepython-imaging-library
# https://en.wikipedia.org/wiki/Xiaolin_Wu%27s_line_algorithm
import math


def plot(draw, img, x, y, c, col, steep, dash_interval):
    """Draws an antiliased pixel on a line."""
    if steep:
        x, y = y, x
    if x < img.size[0] and y < img.size[1] and x >= 0 and y >= 0:
        c = c * (float(col[3]) / 255.0)
        p = img.getpixel((x, y))
        x = int(x)
        y = int(y)
        if dash_interval:
            d = dash_interval - 1
            if (x / dash_interval) % d == 0 and (y / dash_interval) % d == 0:
                return
        draw.point((x, y), fill=(
            int((p[0] * (1 - c)) + col[0] * c),
            int((p[1] * (1 - c)) + col[1] * c),
            int((p[2] * (1 - c)) + col[2] * c), 255))


def iround(x):
    """Rounds x to the nearest integer."""
    return ipart(x + 0.5)


def ipart(x):
    """Floors x."""
    return math.floor(x)


def fpart(x):
    """Returns the fractional part of x."""
    return x - math.floor(x)


def rfpart(x):
    """Returns the 1 minus the fractional part of x."""
    return 1 - fpart(x)


def draw_line_antialiased(draw, img, x1, y1, x2, y2, col, dash_interval=None):
    """Draw an antialised line in the PIL ImageDraw.

    Implements the Xialon Wu antialiasing algorithm.

    col - color
    """
    dx = x2 - x1
    if not dx:
        draw.line((x1, y1, x2, y2), fill=col, width=1)
        return

    dy = y2 - y1
    steep = abs(dx) < abs(dy)
    if steep:
        x1, y1 = y1, x1
        x2, y2 = y2, x2
        dx, dy = dy, dx
    if x2 < x1:
        x1, x2 = x2, x1
        y1, y2 = y2, y1
    gradient = float(dy) / float(dx)

    # handle first endpoint
    xend = round(x1)
    yend = y1 + gradient * (xend - x1)
    xgap = rfpart(x1 + 0.5)
    xpxl1 = xend    # this will be used in the main loop
    ypxl1 = ipart(yend)
    plot(draw, img, xpxl1, ypxl1, rfpart(yend) * xgap, col, steep,
         dash_interval)
    plot(draw, img, xpxl1, ypxl1 + 1, fpart(yend) * xgap, col, steep,
         dash_interval)
    intery = yend + gradient  # first y-intersection for the main loop

    # handle second endpoint
    xend = round(x2)
    yend = y2 + gradient * (xend - x2)
    xgap = fpart(x2 + 0.5)
    xpxl2 = xend    # this will be used in the main loop
    ypxl2 = ipart(yend)
    plot(draw, img, xpxl2, ypxl2, rfpart(yend) * xgap, col, steep,
         dash_interval)
    plot(draw, img, xpxl2, ypxl2 + 1, fpart(yend) * xgap, col, steep,
         dash_interval)

    # main loop
    for x in range(int(xpxl1 + 1), int(xpxl2)):
        plot(draw, img, x, ipart(intery), rfpart(intery), col, steep,
             dash_interval)
        plot(draw, img, x, ipart(intery) + 1, fpart(intery), col, steep,
             dash_interval)
        intery = intery + gradient

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