相关疑难解决方法(0)

我想知道是否有一种模糊haarcascade face分类器自动识别的面部的方法.

使用下面的代码,我能够检测到面部,裁剪这个面部周围的图像或在其上绘制一个矩形.

image = cv2.imread(imagepath)

# Specify the trained cascade classifier
face_cascade_name = "./haarcascade_frontalface_alt.xml"

# Create a cascade classifier
face_cascade = cv2.CascadeClassifier()

# Load the specified classifier
face_cascade.load(face_cascade_name)

#Preprocess the image
grayimg = cv2.cvtColor(image, cv2.cv.CV_BGR2GRAY)
grayimg = cv2.equalizeHist(grayimg)

#Run the classifiers
faces = face_cascade.detectMultiScale(grayimg, 1.1, 2, 0|cv2.cv.CV_HAAR_SCALE_IMAGE, (30, 30))

print "Faces detected"

if len(faces) != 0:            # If there are faces in the images
    for f in faces:         # For each face in the image

        # Get the origin …

我正在教自己如何通过编写我在youtube上找到的简单的面部识别程序来使用openCV.我已经安装了opencv版本2以及numpy 1.8.0.我正在使用python2.7.

我在下面的视频和文章链接中准确地复制了这段代码,但我一直在收到错误.AttributeError:'module'对象没有属性'cv'我做错了什么？

这是我正在使用的代码.

import cv2
import sys

# Get user supplied values
imagePath = sys.argv[1]
cascPath = sys.argv[2]

# Create the haar cascade
faceCascade = cv2.CascadeClassifier(cascPath)

# Read the image
image = cv2.imread(imagePath)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# Detect faces in the image
faces = (faceCascade.detectMultiScale(
    gray,
    scaleFactor=1.1,
    minNeighbors=5,
    minSize=(30, 30),
    flags = cv2.cv.CV_HAAR_SCALE_IMAGE)
)

print "Found {0} faces!".format(len(faces))

# Draw a rectangle around the faces
for (x, y, w, h) in faces:
    cv2.rectangle(image, (x, y), (x+w, y+h), (0, …