112 lines
3.4 KiB
Python
112 lines
3.4 KiB
Python
#!/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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'''
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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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from tst_scene_render import TestSceneRender
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def intersectionRate(s1, s2):
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x1, y1, x2, y2 = s1
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s1 = [[x1, y1], [x2,y1], [x2, y2], [x1, y2] ]
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x1, y1, x2, y2 = s2
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s2 = [[x1, y1], [x2,y1], [x2, y2], [x1, y2] ]
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area, intersection = cv2.intersectConvexConvex(np.array(s1), np.array(s2))
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return 2 * area / (cv2.contourArea(np.array(s1)) + cv2.contourArea(np.array(s2)))
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from tests_common import NewOpenCVTests
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class camshift_test(NewOpenCVTests):
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frame = None
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selection = None
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drag_start = None
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show_backproj = False
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track_window = None
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render = None
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def prepareRender(self):
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cv2.namedWindow('camshift')
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self.render = TestSceneRender(self.get_sample('samples/data/pca_test1.jpg'))
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def runTracker(self):
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framesCounter = 0
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self.selection = True
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xmin, ymin, xmax, ymax = self.render.getCurrentRect()
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self.track_window = (xmin, ymin, xmax - xmin, ymax - ymin)
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while True:
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framesCounter += 1
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self.frame = self.render.getNextFrame()
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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.render.getCurrentRect() + 50
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x0 -= 100
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y0 -= 100
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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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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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self.selection = False
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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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cv2.rectangle(vis, (self.track_window[0], self.track_window[1]), (self.track_window[0] + self.track_window[2], self.track_window[1] + self.track_window[3]), (0, 255, 0), 2)
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trackingRect = np.array(self.track_window)
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trackingRect[2] += trackingRect[0]
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trackingRect[3] += trackingRect[1]
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print(intersectionRate((self.render.getCurrentRect()), trackingRect))
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self.assertGreater(intersectionRate((self.render.getCurrentRect()), trackingRect), 0.5)
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if framesCounter > 300:
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break
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def test_camshift(self):
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self.prepareRender()
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self.runTracker() |