## 1 圖像分割--Keman聚類
import cv2
import numpy as np
import matplotlib.pyplot as plt

# 1 讀入圖片
img0 = cv2.imread('bird.png', 1)  # (548,727,3)
img0 = cv2.cvtColor(img0, cv2.COLOR_BGR2RGB)
img_ = cv2.GaussianBlur(img0, (13, 13), 10, 10)
h, w, c = img_.shape
img_blur = img_.reshape([-1, 3])
img_blur = np.float32(img_blur)

# 2 分類
criteria = (
cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 10, 1.0)
num_clusters = 2
_, label, center_color = cv2.kmeans(img_blur, num_clusters,
                                    None, criteria,
                                    num_clusters,
                                    cv2.KMEANS_RANDOM_CENTERS)
center_color = np.uint8(
    center_color)  # img_blur[398396,3],label[398396,1],center[2,3]
res = center_color[label.ravel()]  # [398396,3]
res = res.reshape([h, w, c])  # res[668044,3]--> [548,727,3]

# 3 顯示
plt.subplot(131)
plt.title('origin')
plt.imshow(img0)
plt.subplot(132)
plt.title('img_blur')
plt.imshow(img_)
plt.subplot(133)
plt.title('result')
plt.imshow(res)

plt.show()

## 1 圖像分割--Keman聚類
import cv2
import numpy as np
import matplotlib.pyplot as plt

# 1 讀入圖片
img = cv2.imread('luna.png', 1)  # (548,727,3)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
h, w, c = img.shape
img0= img.reshape([-1, 3])
img0 = np.float32(img0)

# 3 分類
criteria = (
cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 10, 1.0)
num_clusters = 2
_, label, center_color = cv2.kmeans(img0, num_clusters,
                                    None, criteria,
                                    num_clusters,
                                    cv2.KMEANS_RANDOM_CENTERS)
center_color = np.uint8(
    center_color)  # img_blur[398396,3],label[398396,1],center[2,3]
res = center_color[label.ravel()]  # [398396,3]

res = res.reshape([h, w, c])  # res[668044,3]--> [548,727,3]

plt.subplot(121)
plt.title('origin')
plt.imshow(img)
plt.subplot(122)
plt.title('result')
plt.imshow(res)

plt.show()

center_color = np.uint8(
    center_color)  
## 調(diào)整顯示顏色
center_color[0]=[0,0,255]
center_color[1]=[255,0,0]

res = center_color[label.ravel()]