源码在这

#!/usr/bin/env python

'''
Camshift tracker
================ This is a demo that shows mean-shift based tracking
You select a color objects such as your face and it tracks it.
This reads from video camera (0 by default, or the camera number the user enters) http://www.robinhewitt.com/research/track/camshift.html Usage:
------
camshift.py [<video source>] To initialize tracking, select the object with mouse Keys:
-----
ESC - exit
b - toggle back-projected probability visualization
''' import numpy as np
import cv2
import video class App(object):
def __init__(self, video_src):
self.cam = video.create_capture(video_src) # 开启摄像头
ret, self.frame = self.cam.read() # 读取一帧图片
cv2.namedWindow('camshift') #创建 名为 camshift的窗口
cv2.setMouseCallback('camshift', self.onmouse) #在窗口上增加回调函数 self.selection = None
self.drag_start = None
self.tracking_state = 0
self.show_backproj = False def onmouse(self, event, x, y, flags, param):
x, y = np.int16([x, y]) # BUG
if event == cv2.EVENT_LBUTTONDOWN:
self.drag_start = (x, y)
self.tracking_state = 0
return
if self.drag_start:
if flags & cv2.EVENT_FLAG_LBUTTON:
h, w = self.frame.shape[:2]
xo, yo = self.drag_start
x0, y0 = np.maximum(0, np.minimum([xo, yo], [x, y]))
x1, y1 = np.minimum([w, h], np.maximum([xo, yo], [x, y]))
self.selection = None
if x1-x0 > 0 and y1-y0 > 0:
self.selection = (x0, y0, x1, y1)
else:
self.drag_start = None
if self.selection is not None:
self.tracking_state = 1 def show_hist(self):
bin_count = self.hist.shape[0]
bin_w = 24
img = np.zeros((256, bin_count*bin_w, 3), np.uint8)
for i in xrange(bin_count):
h = int(self.hist[i])
cv2.rectangle(img, (i*bin_w+2, 255), ((i+1)*bin_w-2, 255-h), (int(180.0*i/bin_count), 255, 255), -1)
img = cv2.cvtColor(img, cv2.COLOR_HSV2BGR)
cv2.imshow('hist', img) def run(self):
while True:
ret, self.frame = self.cam.read() #读取一帧图片
vis = self.frame.copy() # 复制一份
hsv = cv2.cvtColor(self.frame, cv2.COLOR_BGR2HSV) # 将图片从 BGR 空间转换到 HSV 空间
mask = cv2.inRange(hsv, np.array((0., 60., 32.)), np.array((180., 255., 255.))) # 找出颜色区间在 np.array((0., 60., 32.)), np.array((180., 255., 255.) if self.selection:
x0, y0, x1, y1 = self.selection
self.track_window = (x0, y0, x1-x0, y1-y0)
hsv_roi = hsv[y0:y1, x0:x1]
mask_roi = mask[y0:y1, x0:x1]
hist = cv2.calcHist( [hsv_roi], [0], mask_roi, [16], [0, 180] )
cv2.normalize(hist, hist, 0, 255, cv2.NORM_MINMAX);
self.hist = hist.reshape(-1)
self.show_hist() vis_roi = vis[y0:y1, x0:x1]
cv2.bitwise_not(vis_roi, vis_roi)
vis[mask == 0] = 0 if self.tracking_state == 1:
self.selection = None
prob = cv2.calcBackProject([hsv], [0], self.hist, [0, 180], 1)
prob &= mask
term_crit = ( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 )
track_box, self.track_window = cv2.CamShift(prob, self.track_window, term_crit) if self.show_backproj:
vis[:] = prob[...,np.newaxis]
try: cv2.ellipse(vis, track_box, (0, 0, 255), 2)
except: print track_box cv2.imshow('camshift', vis) ch = 0xFF & cv2.waitKey(5)
if ch == 27:
break
if ch == ord('b'):
self.show_backproj = not self.show_backproj
cv2.destroyAllWindows() if __name__ == '__main__':
import sys
try: video_src = sys.argv[1]
except: video_src = 0
print __doc__
App(video_src).run()

第117行:sys.argv[]  是用来获取命令行参数的,常见的sys.argv[0]表示本身文件路径,所以一般都从1 开始 这里我将官方文档的教程源码抄下来大家看看就懂了

# jack.py
#!/usr/bin/python
# Filename: using_sys.py import sys print 'The command line arguments are:'
for i in sys.argv:
print i print '\n\nThe PYTHONPATH is', sys.path, '\n'

  在终端输入

python jack.py ba la ba la 

  结果显示

The command line arguments are:
jack.py
ba
la
ba
la The PYTHONPATH is ['/home/x-power/OpenCV', '/usr/lib/python2.7', '/usr/lib/python2.7/plat-x86_64-linux-gnu', '/usr/lib/python2.7/lib-tk', '/usr/lib/python2.7/lib-old', '/usr/lib/python2.7/lib-dynload', '/home/x-power/.local/lib/python2.7/site-packages', '/usr/local/lib/python2.7/dist-packages', '/usr/lib/python2.7/dist-packages', '/usr/lib/python2.7/dist-packages/PILcompat', '/usr/lib/python2.7/dist-packages/gtk-2.0']



camshift.py OpenCv例程阅读的更多相关文章

  1. common.py OpenCv例程阅读

    #!/usr/bin/env python ''' This module contais some common routines used by other samples. ''' import ...

  2. video.py OpenCv例程阅读

    #!/usr/bin/env python ''' Video capture sample. Sample shows how VideoCapture class can be used to a ...

  3. 【双目备课】OpenCV例程_stereo_calib.cpp解析

    stereo_calib是OpenCV官方代码中提供的最正统的双目demo,无论数据集还是代码都有很好实现. 一.代码效果: 相关的内容包括28张图片,1个xml和stereo_calib.cpp的代 ...

  4. OpenCV例程实现人脸检测

    前段时间看的OpenCV,其实有很多的例子程序,参考代码值得我们学习,对图像特征提取三大法宝:HOG特征,LBP特征,Haar特征有一定了解后. 对本文中的例子程序刚开始没有调通,今晚上调通了,试了试 ...

  5. python中 __init__.py的例程

    __init__.py一般是为空,用在一个python目录中,标识该目录是一个python的模块包 先上来看一个例子: .: test1 test2 test_init.py ./test1: tim ...

  6. OpenCV 例程

    采集图片显示视频: #include <iostream> #include <opencv2/opencv.hpp> using namespace std; using n ...

  7. Opencv Cookbook阅读笔记(四):用直方图统计像素

    灰度直方图的定义 灰度直方图是灰度级的函数,描述图像中该灰度级的像素个数(或该灰度级像素出现的频率):其横坐标是灰度级,纵坐标表示图像中该灰度级出现的个数(频率). #include <open ...

  8. [OpenCV-Python] OpenCV 中视频分析 部分 VI

    部分 VI视频分析 OpenCV-Python 中文教程(搬运)目录 39 Meanshift 和 和 Camshift 目标 • 本节我们要学习使用 Meanshift 和 Camshift 算法在 ...

  9. python + opencv: kalman 跟踪

    之前博文中讲解过kalman滤波的原理和应用,这里用一个跟踪鼠标的例程来演示怎么在opencv里用自带的kalman函数进行目标跟踪,文章的内容对做图像跟踪有借鉴意义.文章主要是网络资源进行整理和简单 ...

随机推荐

  1. 使用session来存储用户的登录信息

    对存在cookie端数据进行加密处理,具体代码如下: <?php session_start(); //假设用户登录成功获得了以下用户数据 $userinfo = array( 'uid' =& ...

  2. openstack 中国联盟公开课參会总结

    主流趋势 1. openstack defcore 互操作性认证.打通不同的openstack 厂商之间的连接 2. 首批OpenStack管理员认证(COA)将于2016年进行 3. 混合云应用广泛 ...

  3. C/C++实现删除字符串的首尾空格

    StdStringTrimTest.cpp #include <iostream> int main() { std::string str(" 字符串 String " ...

  4. ubuntu gcc低版本过低引起错误

    错误内容: 正在读取软件包列表... 完成正在分析软件包的依赖关系树 正在读取状态信息... 完成 您可能需要运行“apt-get -f install”来纠正下列错误:下列软件包有未满足的依赖关系: ...

  5. js-easyUI格式化时间

    formatter : function(value, row) { if(value != null){ var date = new Date(value); var y = date.getFu ...

  6. TCO 2016 Round 1B

    problem 250 Problem Statement Vasa likes to construct sequences of numbers. If you tell him a positi ...

  7. bzoj4406: [Wc2016]论战捆竹竿&&uoj#172. 【WC2016】论战捆竹竿

    第二次在bzoj跑进前十竟然是因为在UOJ卡常致死 首先这个题其实就是一个无限背包 一般做法是同余最短路,就是bzoj2118: 墨墨的等式可以拿到30分的好成绩 背包是个卷积就分治FFT优化那么下面 ...

  8. 安装程序工具 (Installutil.exe)22

    网址:https://msdn.microsoft.com/zh-cn/library/50614e95(VS.80).aspx  安装程序工具 (Installutil.exe) .NET Fram ...

  9. 「LuoguP1281」 书的复制(贪心

    Description 大多数人的错误原因:尽可能让前面的人少抄写,如果前几个人可以不写则不写,对应的人输出0 0. 不过,已经修改数据,保证每个人都有活可干. // 现在要把m本有顺序的书分给k给人 ...

  10. vue之安装配置

    直接上图