opencv/samples/python2/camshift.py

135 lines
4.1 KiB
Python
Raw Normal View History

2013-03-06 14:41:02 +08:00
#!/usr/bin/env python
2012-10-17 07:18:30 +08:00
'''
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
'''
# Python 2/3 compatibility
from __future__ import print_function
import sys
PY3 = sys.version_info[0] == 3
if PY3:
xrange = range
2012-10-17 07:18:30 +08:00
import numpy as np
import cv2
2013-03-06 14:41:02 +08:00
# local module
2012-10-17 07:18:30 +08:00
import video
class App(object):
def __init__(self, video_src):
self.cam = video.create_capture(video_src)
ret, self.frame = self.cam.read()
cv2.namedWindow('camshift')
cv2.setMouseCallback('camshift', self.onmouse)
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
2015-10-15 10:03:46 +08:00
return
2012-10-17 07:18:30 +08:00
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()
vis = self.frame.copy()
hsv = cv2.cvtColor(self.frame, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv, 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] )
2015-07-22 01:54:06 +08:00
cv2.normalize(hist, hist, 0, 255, cv2.NORM_MINMAX)
2012-10-17 07:18:30 +08:00
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]
2013-03-06 14:41:02 +08:00
try:
cv2.ellipse(vis, track_box, (0, 0, 255), 2)
except:
print(track_box)
2012-10-17 07:18:30 +08:00
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
2013-03-06 14:41:02 +08:00
try:
video_src = sys.argv[1]
except:
2013-03-06 14:41:02 +08:00
video_src = 0
print(__doc__)
2012-10-17 07:18:30 +08:00
App(video_src).run()