阈值的求解（两峰之间）

import cv2
import numpy as np
image=cv2.imread('4.jpg')
# image=cv2.resize(image1,(200,200))
image_gray=cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
w,h=image_gray.shape
px_count=np.zeros(256)

#照片长、宽分别是w,h
for w_w in range(w):
    for h_h in range(h):
        px_count[image_gray[w_w,h_h]]+=1
# print(px_count)

#找最大次数（最大峰）
max_index=np.argmax(px_count,axis=0)

#找次大峰
px_count[max_index]*=-1
next_max_index=np.argmax(px_count,axis=0)
px_count[next_max_index]*=-1

#找谷值
if max_index>next_max_index:
    min_index=np.agrmin(px_count[next_max_index:max_index+1],axis=0)
    min_index+=next_max_index
else:
    min_index=np.argmin(px_count[max_index:next_max_index+1],axis=0)
    min_index+=max_index
#TODO.1
# image_gray 上面转换为黑白的照片；
# min_index  谷值
#0~255 代表不同的颜色，min_index为阈值，大于阈值的全部置为255（白色）
_,image_binary=cv2.threshold(image_gray,min_index,255,cv2.THRESH_BINARY)
cv2.imshow('the original image',image)
cv2.imshow('black and white figure',image_gray)
cv2.imshow('the threshold figure',image_binary)
if cv2.waitKey(0)&0xFF==27:
    cv2.destroyAllWindows()

4.jpg