python 计算积分图和haar特征的实例代码

 import cv2 import numpy as np import matplotlib.pyplot as plt # #计算积分图 # def integral(img): integ_graph = np.zeros((img.shape[0],img.shape[1]),dtype = np.int32) for x in range(img.shape[0]): 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 #  --- --- # |  |  | # | - | + | # |  |  | # --- --- # #就算所有需要计算haar特征的区域 # def getHaarFeaturesArea(width,height): widthLimit = width-1 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 # #通过积分图特征区域计算haar特征 # def calHaarFeatures(integral_graph,features_graph): haarFeatures = [] for num in range(len(features_graph)): #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]<b style="color:transparent">来源gao@dai!ma.com搞$代^码网</b>+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]] #右面的像素和减去左面的像素和 haarFeatures.append(haar2-haar1) return haarFeatures img = cv2.imread("faces/face00001.bmp",0) integeralGraph = integral(img) featureAreas = getHaarFeaturesArea(img.shape[0],img.shape[1]) haarFeatures = calHaarFeatures(integeralGraph,featureAreas) print(haarFeatures)