python-3.x - 使用 KMeans 进行 Floyd 抖动

Question

在使用 KMeans 之后，我正在尝试在 Python 中实现 Floyd-Steinberg 抖动。我意识到，在抖动之后，我收到了不包含在缩小调色板中的颜色，所以我再次使用 KMeans 修改图像。但是，在尝试使用这张图片时，我完全看不到抖动。我被卡住了，我累了——请帮帮我。我的想法几乎消失了。

from PIL import Image
import numpy as np
import matplotlib.pyplot as plt
from sklearn.cluster import KMeans

k = 16

im = Image.open('Image.png').convert('RGB') #Image converted to RGB
pic = np.array(im, dtype = np.float)/255 #Enables imshow()
im.close()

def kmeans(pic): #Prepares algorithmic data
    v, c, s = pic.shape
    repic = np.resize(pic, (c*v, 3))

    kme = KMeans(n_clusters = k).fit(repic)
    cl = kme.cluster_centers_

    return kme, cl, repic, v, c

kme, cl, repic, v, c = kmeans(pic)
pred = kme.predict(repic)

def picture(v, c, cl, pred): #Creates a picture with reduced colors
    image = np.ones((v, c, 3))
    ind = 0
    for i in range(v):
        for j in range(c):
            image[i][j] = cl[pred[ind]]
            ind+=1
    return image

image = picture(v, c, cl, pred)

def dither(pic, image): #Floyd-Steinberg dithering
    v, c, s = pic.shape
    Floyd = np.copy(image)
    for i in range(1, v-1):
        for j in range(1, c-1):
            quan = pic[i][j] - image[i][j]
            Floyd[i][j + 1] = quan * (np.float(7 / 16)) + pic[i][j + 1]
            Floyd[i + 1][j - 1] = quan * (np.float(5 / 16)) + pic[i + 1][j - 1]
            Floyd[i + 1][j] = quan * (np.float(3 / 16)) + pic[i + 1][j]
            Floyd[i + 1][j + 1] = quan * (np.float(1 / 16)) + pic[i + 1][j + 1]
    return Floyd

fld = dither(pic, image)
a1, a2, reim, a3, a4 = kmeans(fld)
lab = kme.predict(reim)
Floyd = picture(v, c, cl, lab)

plt.imshow(Floyd)
plt.show()

标签： python-3.ximage-processingk-meansdithering