129 lines
3.9 KiB
Python
Executable File
129 lines
3.9 KiB
Python
Executable File
#!/usr/bin/env python
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'''
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Camshift tracker
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================
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This is a demo that shows mean-shift based tracking
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You select a color objects such as your face and it tracks it.
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This reads from video camera (0 by default, or the camera number the user enters)
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http://www.robinhewitt.com/research/track/camshift.html
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Usage:
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------
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camshift.py [<video source>]
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To initialize tracking, select the object with mouse
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Keys:
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-----
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ESC - exit
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b - toggle back-projected probability visualization
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'''
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# Python 2/3 compatibility
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from __future__ import print_function
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import sys
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PY3 = sys.version_info[0] == 3
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if PY3:
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xrange = range
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import numpy as np
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import cv2
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# local module
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import video
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from video import presets
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class App(object):
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def __init__(self, video_src):
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self.cam = video.create_capture(video_src, presets['cube'])
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ret, self.frame = self.cam.read()
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cv2.namedWindow('camshift')
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cv2.setMouseCallback('camshift', self.onmouse)
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self.selection = None
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self.drag_start = None
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self.show_backproj = False
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self.track_window = None
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def onmouse(self, event, x, y, flags, param):
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if event == cv2.EVENT_LBUTTONDOWN:
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self.drag_start = (x, y)
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self.track_window = None
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if self.drag_start:
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xmin = min(x, self.drag_start[0])
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ymin = min(y, self.drag_start[1])
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xmax = max(x, self.drag_start[0])
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ymax = max(y, self.drag_start[1])
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self.selection = (xmin, ymin, xmax, ymax)
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if event == cv2.EVENT_LBUTTONUP:
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self.drag_start = None
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self.track_window = (xmin, ymin, xmax - xmin, ymax - ymin)
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def show_hist(self):
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bin_count = self.hist.shape[0]
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bin_w = 24
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img = np.zeros((256, bin_count*bin_w, 3), np.uint8)
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for i in xrange(bin_count):
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h = int(self.hist[i])
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cv2.rectangle(img, (i*bin_w+2, 255), ((i+1)*bin_w-2, 255-h), (int(180.0*i/bin_count), 255, 255), -1)
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img = cv2.cvtColor(img, cv2.COLOR_HSV2BGR)
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cv2.imshow('hist', img)
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def run(self):
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while True:
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ret, self.frame = self.cam.read()
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vis = self.frame.copy()
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hsv = cv2.cvtColor(self.frame, cv2.COLOR_BGR2HSV)
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mask = cv2.inRange(hsv, np.array((0., 60., 32.)), np.array((180., 255., 255.)))
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if self.selection:
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x0, y0, x1, y1 = self.selection
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hsv_roi = hsv[y0:y1, x0:x1]
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mask_roi = mask[y0:y1, x0:x1]
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hist = cv2.calcHist( [hsv_roi], [0], mask_roi, [16], [0, 180] )
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cv2.normalize(hist, hist, 0, 255, cv2.NORM_MINMAX)
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self.hist = hist.reshape(-1)
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self.show_hist()
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vis_roi = vis[y0:y1, x0:x1]
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cv2.bitwise_not(vis_roi, vis_roi)
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vis[mask == 0] = 0
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if self.track_window and self.track_window[2] > 0 and self.track_window[3] > 0:
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self.selection = None
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prob = cv2.calcBackProject([hsv], [0], self.hist, [0, 180], 1)
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prob &= mask
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term_crit = ( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 )
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track_box, self.track_window = cv2.CamShift(prob, self.track_window, term_crit)
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if self.show_backproj:
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vis[:] = prob[...,np.newaxis]
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try:
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cv2.ellipse(vis, track_box, (0, 0, 255), 2)
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except:
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print(track_box)
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cv2.imshow('camshift', vis)
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ch = 0xFF & cv2.waitKey(5)
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if ch == 27:
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break
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if ch == ord('b'):
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self.show_backproj = not self.show_backproj
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cv2.destroyAllWindows()
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if __name__ == '__main__':
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import sys
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try:
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video_src = sys.argv[1]
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except:
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video_src = 0
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print(__doc__)
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App(video_src).run()
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