return _cv.cvHaarDetectObjects(*args)

Question

我试图在ubuntu上使用opencv python从网络摄像头中检测到脸部.我得到了这个在线代码,并试图运行这个程序,我得到了as NULL数组指针传递,我想它无法从网络摄像头捕获视频,但使用相同的代码(只捕获相机)我开了相机它捕获了视频.这是我的代码:

import cv
from opencv import highgui
HAAR_CASCADE_PATH = "/home/OpenCV-2.3.1/data/haarcascades/haarcascade_frontalface_default.xml"

CAMERA_INDEX = 0 
def detect_faces(image):
 faces = []
 detected = cv.HaarDetectObjects(image, cascade, storage, 1.2, 2, cv.CV_HAAR_DO_CANNY_PRUNING, (100,100))
if detected:
    for (x,y,w,h),n in detected:
        faces.append((x,y,w,h))
return faces

if __name__ == "__main__":
cv.NamedWindow("Video", cv.CV_WINDOW_AUTOSIZE)

capture = cv.CaptureFromCAM(0)
storage = cv.CreateMemStorage()
cascade = cv.Load(HAAR_CASCADE_PATH)
print cascade
faces = []

i = 0
c = -1
while (c == -1):
    image = cv.QueryFrame(capture)


    # Only run the Detection algorithm every 5 frames to improve performance
    #if i%5==0:
    faces = detect_faces(image)
    #print image

    for (x,y,w,h) in faces:
        cv.Rectangle(image, (x,y), (x+w,y+h), 255)


    cv.ShowImage("w1", image)
    i += 1

我得到的错误是:

Traceback (most recent call last):
File "/home/OpenCV-2.3.1/webcam_try.py", line 38, in <module>
faces = detect_faces(frame)
File "/home/OpenCV-2.3.1/webcam_try.py", line 13, in detect_faces
detected = cv.cvHaarDetectObjects(frame, cascade, storage, 1.2, 2,    cv.CV_HAAR_DO_CANNY_PRUNING,(100,100))
 File "/usr/lib/pymodules/python2.7/opencv/cv.py", line 1626, in cvHaarDetectObjects
 return _cv.cvHaarDetectObjects(*args)
 NotImplementedError: Wrong number of arguments for overloaded function     'cvHaarDetectObjects'.
 Possible C/C++ prototypes are:
  cvHaarDetectObjects_Shadow(CvArr const *,CvHaarClassifierCascade *,CvMemStorage *,double,int,int,CvSize)
  cvHaarDetectObjects_Shadow(CvArr const *,CvHaarClassifierCascade *,CvMemStorage *,double,int,int)
  cvHaarDetectObjects_Shadow(CvArr const *,CvHaarClassifierCascade *,CvMemStorage *,double,int)
  cvHaarDetectObjects_Shadow(CvArr const *,CvHaarClassifierCascade *,CvMemStorage *,double)
  cvHaarDetectObjects_Shadow(CvArr const *,CvHaarClassifierCascade *,CvMemStorage *)

Answer 1

你的代码对我来说很好(虽然我运行OpenCV v2.4.3而不是你的版本,2.3.1).我上周开始使用相同的在线代码(在这里发布),我最终放弃使用cv并切换到新cv2库.

所以.我已经更新了你的代码,以便它使用新的cv2界面.

cv2用于运行Haar Cascade Classifiers 的Python界面更易于使用.查看cv2.CascadeClassifier.detectMultiScale() 此处的文档.新cv2界面显着简化了您的代码.以下是亮点:

1. 您不再需要担心创建内存缓冲区.
2. 返回的结果detectMultiScale以超级有用的形式返回,消除了对旧代码detect_faces()功能的需求!
3. 您只需要提供一个参数:图像本身.所有其他参数都是可选的.我已经在下面的修订代码中包含了您使用的参数,但随时可以删除它们.

一条建议:如果你的代码运行缓慢,你可以做的最好的事情之一是增加minSize.对于我的网络摄像头,使用(100,100)会导致超慢的帧速率约为0.2fps.将它改为(300,300)将其提升到可观的20fps.

代码应该适用于您现有的安装,因为您运行的是2.3.1,但如果没有,则尝试升级到最新版本.

import cv2
import cv2.cv as cv

HAAR_CASCADE_PATH = "/home/OpenCV-2.3.1/data/haarcascades/haarcascade_frontalface_default.xml";

CAMERA_INDEX = 0;

if __name__ == "__main__":

    # Open window, load webcam and load Haar cascade classifier
    cv2.namedWindow("Video", cv.CV_WINDOW_AUTOSIZE)
    capture = cv2.VideoCapture(CAMERA_INDEX);
    cascade = cv2.CascadeClassifier(HAAR_CASCADE_PATH);

    i = 0;

    while True:
        # Grab frame from webcam
        retVal, image = capture.read(); # note: ignore retVal

        # Only run the Detection algorithm every 5 frames to improve performance
        #if i%5==0:
        faces = cascade.detectMultiScale(image, scaleFactor=1.2, 
                                        minNeighbors=2, minSize=(100,100), 
                                        flags=cv.CV_HAAR_DO_CANNY_PRUNING);

        # Draw rectangles on image, and then show it
        for (x,y,w,h) in faces:
            cv2.rectangle(image, (x,y), (x+w,y+h), 255)
        cv2.imshow("Video", image)

        i += 1;