Opencv k-平均聚类算法进行减色处理第一步

import cv2
import numpy as np
import matplotlib.pyplot as plt
from glob import glob


# K-means step1
def k_means_step1(img, Class=5):
    #  get shape
    H, W, C = img.shape

    # initiate random seed
    np.random.seed(0)

    # reshape
    img = np.reshape(img, (H * W, -1))

    # select one index randomly
    i = np.random.choice(np.arange(H * W), Class, replace=False)
    Cs = img[i].copy()

    print(Cs)

    clss = np.zeros((H * W), dtype=int)

    # each pixel
    for i in range(H * W):
        # get distance from base pixel
        dis = np.sqrt(np.sum((Cs - img[i]) ** 2, axis=1))
        # get argmin distance
        clss[i] = np.argmin(dis)

    # show
    out = np.reshape(clss, (H, W)) * 50
    out = out.astype(np.uint8)

    return out


# read image
img = cv2.imread("imori.jpg").astype(np.float32)

# K-means step2
out = k_means_step1(img)

cv2.imwrite("out.jpg", out)
cv2.imshow("result", out)
cv2.waitKey(0)

# 最初选择的颜色
[[140. 121. 148.]
 [135. 109. 122.]
 [211. 189. 213.]
 [135.  86.  84.]
 [118.  99.  96.]]