Add 2 new tests, bugfixed in old tests

modules/python/test/test_camshift.py

@@ -0,0 +1,112 @@
+#!/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()