新聞中心
這里有您想知道的互聯(lián)網(wǎng)營(yíng)銷解決方案
python計(jì)算積分圖和haar特征的實(shí)例代碼-創(chuàng)新互聯(lián)
下面的代碼通過(guò)積分圖計(jì)算一張圖片的一種haar特征的所有可能的值。初步學(xué)習(xí)圖像處理并嘗試寫代碼,如有錯(cuò)誤,歡迎指出。
import cv2 import numpy as np import matplotlib.pyplot as plt # #計(jì)算積分圖 # 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 # --- --- # | | | # | - | + | # | | | # --- --- # #就算所有需要計(jì)算haar特征的區(qū)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 # #通過(guò)積分圖特征區(qū)域計(jì)算haar特征 # def calHaarFeatures(integral_graph,features_graph): haarFeatures = [] for num in range(len(features_graph)): #計(jì)算左面的矩形區(qū)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]] #計(jì)算右面的矩形區(qū)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]] #右面的像素和減去左面的像素和 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)
新聞名稱:python計(jì)算積分圖和haar特征的實(shí)例代碼-創(chuàng)新互聯(lián)
分享鏈接:http://ef60e0e.cn/article/ddissg.html