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']
