極大位置の検出

# -*- coding: utf-8 -*-
#参考：http://scikit-image.org/ 
from scipy import ndimage as ndi
import matplotlib.pyplot as plt
from skimage.feature import peak_local_max
from skimage import data, img_as_float

#Ipythonで表示用の設定
%matplotlib inline

#サンプルデータ読込
im = img_as_float(data.coins())

# image_max is the dilation of im with a 20*20 structuring element
# It is used within peak_local_max function
image_max = ndi.maximum_filter(im, size=20, mode='constant')

# Comparison between image_max and im to find the coordinates of local maxima
coordinates = peak_local_max(im, min_distance=20)

# 結果の表示
fig, ax = plt.subplots(1, 3, figsize=(10, 3))
ax1, ax2, ax3 = ax.ravel()
ax1.imshow(im, cmap=plt.cm.gray)
ax1.axis('off')
ax1.set_title('Original')

ax2.imshow(image_max, cmap=plt.cm.gray)
ax2.axis('off')
ax2.set_title('Maximum filter')

ax3.imshow(im, cmap=plt.cm.gray)
ax3.autoscale(False)
ax3.plot(coordinates[:, 1], coordinates[:, 0], 'r.')
ax3.axis('off')
ax3.set_title('Peak local max')

fig.subplots_adjust(wspace=0.02, hspace=0.02, top=0.9,
                    bottom=0.02, left=0.02, right=0.98)

plt.show()

To Return CV&ML.