在pcDuino上安装OpenCV,以及两个OpenCV入门的例子

OpenCV是一个很基于 Python的开源视觉识别工具。 在这里，我们相信地介绍了如何如何在pcDuino上安装OpenCV。 然后给出了两个例子。 第一个例子是介绍如何用OpenCV抓图像，第二个例子介绍如何用OpenCV进行人脸识别。

安装步骤：

$ sudo apt-get -y install build-essential cmake cmake-qt-gui pkg-config libpng12-0 libpng12-dev libpng++-dev libpng3 libpnglite-dev zlib1g-dbg zlib1g zlib1g-dev pngtools libtiff4-dev libtiff4 libtiffxx0c2 libtiff-tools

$sudo apt-get -y install libjpeg8 libjpeg8-dev libjpeg8-dbg libjpeg-progs ffmpeg libavcodec-dev libavcodec53 libavformat53 libavformat-dev libgstreamer0.10-0-dbg libgstreamer0.10-0 libgstreamer0.10-dev libxine1-ffmpeg libxine-dev libxine1-bin libunicap2 libunicap2-dev libdc1394-22-dev libdc1394-22 libdc1394-utils swig libv4l-0 libv4l-dev python-numpy libpython2.6 python2.6-dev libgtk2.0-dev pkg-config

$sudo apt-get install libopencv-dev python-opencv

$sudo apt-get install python-dev

$sudo ln -s /usr/lib/arm-linux-gnueabihf/libjpeg.so /usr/lib
$sudo ln -s /usr/lib/arm-linux-gnueabihf/libfreetype.so /usr/lib
$sudo ln -s /usr/lib/arm-linux-gnueabihf/libz.so /usr/lib 

$sudo easy_install PIL
$sudo pip install -v PIL

例子一：如何用OpenCV抓图像

#!/Users/brent/.virtualenvs/lumber/bin/python

import cv

cv.NamedWindow("w1", cv.CV_WINDOW_AUTOSIZE)
camera_index = 0
capture = cv.CaptureFromCAM(camera_index)

gx = gy = 1
grayscale = blur = canny = False

def repeat():
    global capture #declare as globals since we are assigning to them now
    global camera_index
    global gx, gy, grayscale, canny, blur
    frame = cv.QueryFrame(capture)
    # import pdb; pdb.set_trace()

    if grayscale:
        gray = cv.CreateImage(cv.GetSize(frame), frame.depth, 1)
        cv.CvtColor(frame, gray, cv.CV_RGB2GRAY)
        frame = gray

    if blur:
        g = cv.CreateImage(cv.GetSize(frame), cv.IPL_DEPTH_8U, frame.channels)
        cv.Smooth(frame, g, cv.CV_GAUSSIAN, gx, gy)
        frame = g

    if grayscale and canny:
        c = cv.CreateImage(cv.GetSize(frame), frame.depth, frame.channels)
        cv.Canny(frame, c, 10, 100, 3)
        frame = c
    cv.ShowImage("w1", frame)

    c = cv.WaitKey(10)
    if c==ord('='): #in "n" key is pressed while the popup window is in focus
        gx += 2
        gy += 2
    elif c == ord('-'):
        gx = max(1, gx-2)
        gy = max(1, gy-2)
    elif c == ord('x'):
        gx += 2
    elif c == ord('X'):
        gx = max(1, gx-2)
    elif c == ord('q'):
        exit(0)

    elif c == ord('b'):
        blur = not blur
    elif c == ord('g'):
        grayscale = not grayscale
    elif c == ord('c'):
        canny = not canny

while True:
    repeat()

例子二：人脸识别

输入图像：

下载上面的图片，保存为 “opencv_in.jpg”.

输出图像：

#!/usr/bin/env python
#coding=utf-8
import os
from PIL import Image, ImageDraw
import cv

def detect_object(image):
    grayscale = cv.CreateImage((image.width, image.height), 8, 1)
    cv.CvtColor(image, grayscale, cv.CV_BGR2GRAY)

    cascade = cv.Load("/usr/share/opencv/haarcascades/haarcascade_frontalface_alt_tree.xml")
    rect = cv.HaarDetectObjects(grayscale, cascade, cv.CreateMemStorage(), 1.1, 2,
        cv.CV_HAAR_DO_CANNY_PRUNING, (20,20))

    result = []
    for r in rect:
        result.append((r[0][0], r[0][1], r[0][0]+r[0][2], r[0][1]+r[0][3]))

    return result

def process(infile):
    image = cv.LoadImage(infile);
    if image:
        faces = detect_object(image)

    im = Image.open(infile)
    path = os.path.abspath(infile)
    save_path = os.path.splitext(path)[0]+"_face"
    try:
        os.mkdir(save_path)
    except:
        pass
    if faces:
        draw = ImageDraw.Draw(im)
        count = 0
        for f in faces:
            count += 1
            draw.rectangle(f, outline=(255, 0, 0))
            a = im.crop(f)
            file_name = os.path.join(save_path,str(count)+".jpg")
     #       print file_name
            a.save(file_name)

        drow_save_path = os.path.join(save_path,"out.jpg")
        im.save(drow_save_path, "JPEG", quality=80)
    else:
        print "Error: cannot detect faces on %s" % infile

if __name__ == "__main__":
    process("./opencv_in.jpg")

保存上面的代码为  test_face.py.

运行 $python test_face.py 来运行。