发布于 2015-12-23 07:23:35 | 1320 次阅读 | 评论: 0 | 来源: PHPERZ
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)
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:
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: