python 计算积分图和haar特征的实例代码

python 计算积分图和计算积分图和haar特征的实例代码特征的实例代码

今天小编就为大家分享一篇python 计算积分图和haar特征的实例代码，具有很好的参考价值，希望对大家有所

帮助。一起跟随小编过来看看吧

下面的代码通过积分图计算一张图片的一种haar特征的所有可能的值。初步学习图像处理并尝试写代码，如有错误，欢迎指

出。

import cv2

import numpy as np

import matplotlib.pyplot as plt

sum_clo = 0

for y in range(img.shape[1]):

sum_clo = sum_clo + img[x][y]

integ_graph[x][y] = integ_graph[x-1][y] + sum_clo;

return integ_graph

# Types of Haar-like rectangle features

# --- ---

# | | |

# | - | + |

# | | |

heightLimit = height/2-1

features = []

for w in range(1,int(widthLimit)):

for h in range(1,int(heightLimit)):

wMoveLimit = width - w

hMoveLimit = height - 2*h

for x in range(0, wMoveLimit):

for y in range(0, hMoveLimit):

features.append([x, y, w, h])

return features

#计算左面的矩形区局的像素和

haar1 = integral_graph[features_graph[num][0]][features_graph[num][1]]-\

integral_graph[features_graph[num][0]+features_graph[num][2]][features_graph[num][1]] -\

integral_graph[features_graph[num][0]][features_graph[num][1]+features_graph[num][3]] +\

integral_graph[features_graph[num][0]+features_graph[num][2]][features_graph[num][1]+features_graph[num][3]]

#计算右面的矩形区域的像素和

haar2 = integral_graph[features_graph[num][0]][features_graph[num][1]+features_graph[num][3]]-\

integral_graph[features_graph[num][0]+features_graph[num][2]][features_graph[num][1]+features_graph[num][3]] -\

integral_graph[features_graph[num][0]][features_graph[num][1]+2*features_graph[num][3]] +\

integral_graph[features_graph[num][0]+features_graph[num][2]][features_graph[num][1]+2*features_graph[num][3]]

haarFeatures = calHaarFeatures(integeralGraph,featureAreas)

print(haarFeatures)

以上这篇python 计算积分图和haar特征的实例代码就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家

多多支持我们。