Open Source Computer Vision Library
https://opencv.org/
112 lines
3.4 KiB
112 lines
3.4 KiB
#!/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 |
|
|
|
''' |
|
|
|
# Python 2/3 compatibility |
|
from __future__ import print_function |
|
import sys |
|
PY3 = sys.version_info[0] == 3 |
|
|
|
if PY3: |
|
xrange = range |
|
|
|
import numpy as np |
|
import cv2 |
|
from tst_scene_render import TestSceneRender |
|
|
|
def intersectionRate(s1, s2): |
|
|
|
x1, y1, x2, y2 = s1 |
|
s1 = [[x1, y1], [x2,y1], [x2, y2], [x1, y2] ] |
|
|
|
x1, y1, x2, y2 = s2 |
|
s2 = [[x1, y1], [x2,y1], [x2, y2], [x1, y2] ] |
|
|
|
area, intersection = cv2.intersectConvexConvex(np.array(s1), np.array(s2)) |
|
return 2 * area / (cv2.contourArea(np.array(s1)) + cv2.contourArea(np.array(s2))) |
|
|
|
|
|
from tests_common import NewOpenCVTests |
|
|
|
class camshift_test(NewOpenCVTests): |
|
|
|
frame = None |
|
selection = None |
|
drag_start = None |
|
show_backproj = False |
|
track_window = None |
|
render = None |
|
|
|
def prepareRender(self): |
|
|
|
cv2.namedWindow('camshift') |
|
self.render = TestSceneRender(self.get_sample('samples/data/pca_test1.jpg')) |
|
|
|
def runTracker(self): |
|
|
|
framesCounter = 0 |
|
self.selection = True |
|
|
|
xmin, ymin, xmax, ymax = self.render.getCurrentRect() |
|
|
|
self.track_window = (xmin, ymin, xmax - xmin, ymax - ymin) |
|
|
|
while True: |
|
framesCounter += 1 |
|
self.frame = self.render.getNextFrame() |
|
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.render.getCurrentRect() + 50 |
|
x0 -= 100 |
|
y0 -= 100 |
|
|
|
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) |
|
|
|
vis_roi = vis[y0:y1, x0:x1] |
|
cv2.bitwise_not(vis_roi, vis_roi) |
|
vis[mask == 0] = 0 |
|
|
|
self.selection = False |
|
|
|
if self.track_window and self.track_window[2] > 0 and self.track_window[3] > 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] |
|
|
|
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) |
|
|
|
trackingRect = np.array(self.track_window) |
|
trackingRect[2] += trackingRect[0] |
|
trackingRect[3] += trackingRect[1] |
|
|
|
print(intersectionRate((self.render.getCurrentRect()), trackingRect)) |
|
self.assertGreater(intersectionRate((self.render.getCurrentRect()), trackingRect), 0.5) |
|
|
|
if framesCounter > 300: |
|
break |
|
|
|
def test_camshift(self): |
|
self.prepareRender() |
|
self.runTracker() |