camshift.py OpenCv例程阅读
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']
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