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Python-OpenCV 处理图像（六）：对象识别

0x00. 特征识别

这里主要用到两个函数：

GoodFeaturesToTrack 和 extractSURF

GoodFeaturesToTrack: 在图像中寻找具有大特征值的角点。
SURF算法: 是一个稳健的图像识别和描述算法。

总之这俩个我目前也不清楚能用来干嘛，以后用到了在更新吧。

import cv2.cv as cv import math im = cv.LoadImage("img/church.png", cv.CV_LOAD_IMAGE_GRAYSCALE) im2 = cv.CloneImage(im) # Goodfeatureto track algorithm eigImage = cv.CreateMat(im.height, im.width, cv.IPL_DEPTH_32F) tempImage = cv.CloneMat(eigImage) cornerCount = 500 quality = 0.01 minDistance = 10 corners = cv.GoodFeaturesToTrack(im, eigImage, tempImage, cornerCount, quality, minDistance) radius = 3 thickness = 2 for (x,y) in corners:  cv.Circle(im, (int(x),int(y)), radius, (255,255,255), thickness) cv.ShowImage("GoodfeaturesToTrack", im) #SURF algorithm hessthresh = 1500 # 400 500 dsize = 0 # 1 layers = 1 # 3 10 keypoints, descriptors = cv.ExtractSURF(im2, None, cv.CreateMemStorage(), (dsize, hessthresh, 3, layers)) for ((x, y), laplacian, size, dir, hessian) in keypoints:  cv.Circle(im2, (int(x),int(y)), cv.Round(size/2), (255,255,255), 1)  x2 = x+((size/2)*math.cos(dir))  y2 = y+((size/2)*math.sin(dir))  cv.Line(im2, (int(x),int(y)), (int(x2),int(y2)), (255,255,255), 1) cv.ShowImage("SURF ", im2) cv.WaitKey(0)

0x01. 人脸识别

可以使用 OpenCV 训练好的级联分类器来识别图像中的人脸，当然还有很多其他的分类器：例如表情识别，鼻子等，具体可在这里下载：

OpenCV分类器

具体使用代码：

#import library - MUST use cv2 if using opencv_traincascade import cv2 # rectangle color and stroke color = (0,0,255)    # reverse of RGB (B,G,R) - weird strokeWeight = 1  # thickness of outline # set window name windowName = "Object Detection" # load an image to search for faces img = cv2.imread("mao.jpg") # load detection file (various files for different views and uses) cascade = cv2.CascadeClassifier("haarcascade_frontalface_alt.xml") # preprocessing, as suggested by: http://www.bytefish.de/wiki/opencv/object_detection # img_copy = cv2.resize(img, (img.shape[1]/2, img.shape[0]/2)) # gray = cv2.cvtColor(img_copy, cv2.COLOR_BGR2GRAY) # gray = cv2.equalizeHist(gray) # detect objects, return as list rects = cascade.detectMultiScale(img) # display until escape key is hit while True:  # get a list of rectangles  for x,y, width,height in rects:   cv2.rectangle(img, (x,y), (x+width, y+height), color, strokeWeight)  # display!  cv2.imshow(windowName, img)  # escape key (ASCII 27) closes window  if cv2.waitKey(20) == 27:   break # if esc key is hit, quit! exit()

效果：

Python-OpenCV 处理图像（六）：对象识别