--- /dev/null
+#!/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 rospy
+from sensor_msgs.msg import Image
+import numpy as np
+import cv2
+from cv_bridge import CvBridge, CvBridgeError
+
+class App:
+ def __init__(self):
+ rospy.init_node('camshift')
+ rospy.Subscriber("/usb_cam/image_raw", Image, self.cmdImageReceived)
+ self.bridge = CvBridge()
+
+ self.first_run = True
+ 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
+ if self.drag_start:
+ if event == cv2.EVENT_LBUTTONUP:
+ self.drag_start = None
+ if self.selection is not None:
+ self.tracking_state = 1
+ elif 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)
+
+ 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):
+ rospy.spin()
+ cv2.destroyAllWindows()
+
+ def cmdImageReceived(self, msg):
+ if self.first_run:
+ cv2.namedWindow('camshift')
+ cv2.namedWindow('hist')
+ cv2.setMouseCallback('camshift', self.onmouse)
+ self.first_run = False
+
+ self.frame = self.bridge.imgmsg_to_cv2(msg, desired_encoding="passthrough")
+ 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] )
+ 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 and self.track_window != (0, 0, 0, 0):
+ 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:
+ rospy.signal_shutdown("Exit from keyboard")
+ if ch == ord('b'):
+ self.show_backproj = not self.show_backproj
+
+
+if __name__ == '__main__':
+ App().run()