Add segmentation and object tracking python tests

modules/python/test/test_lk_homography.py

@@ -0,0 +1,96 @@
+#!/usr/bin/env python
+
+'''
+Lucas-Kanade homography tracker test
+===============================
+Uses goodFeaturesToTrack for track initialization and back-tracking for match verification
+between frames. Finds homography between reference and current views.
+'''
+
+# Python 2/3 compatibility
+from __future__ import print_function
+
+import numpy as np
+import cv2
+
+#local modules
+from tst_scene_render import TestSceneRender
+from tests_common import NewOpenCVTests, isPointInRect
+
+lk_params = dict( winSize  = (19, 19),
+                  maxLevel = 2,
+                  criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03))
+
+feature_params = dict( maxCorners = 1000,
+                       qualityLevel = 0.01,
+                       minDistance = 8,
+                       blockSize = 19 )
+
+def checkedTrace(img0, img1, p0, back_threshold = 1.0):
+    p1, st, err = cv2.calcOpticalFlowPyrLK(img0, img1, p0, None, **lk_params)
+    p0r, st, err = cv2.calcOpticalFlowPyrLK(img1, img0, p1, None, **lk_params)
+    d = abs(p0-p0r).reshape(-1, 2).max(-1)
+    status = d < back_threshold
+    return p1, status
+
+class lk_homography_test(NewOpenCVTests):
+
+    render = None
+    framesCounter = 0
+    frame = frame0 = None
+    p0 = None
+    p1 = None
+    gray0 = gray1 = None
+    numFeaturesInRectOnStart = 0
+
+    def test_lk_homography(self):
+        self.render = TestSceneRender(self.get_sample('samples/data/graf1.png'),
+            self.get_sample('samples/data/box.png'), noise = 0.1, speed = 1.0)
+
+        frame = self.render.getNextFrame()
+        frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        self.frame0 = frame.copy()
+        self.p0 = cv2.goodFeaturesToTrack(frame_gray, **feature_params)
+
+        isForegroundHomographyFound = False
+
+        if self.p0 is not None:
+            self.p1 = self.p0
+            self.gray0 = frame_gray
+            self.gray1 = frame_gray
+            currRect = self.render.getCurrentRect()
+            for (x,y) in self.p0[:,0]:
+                if isPointInRect((x,y), currRect):
+                    self.numFeaturesInRectOnStart += 1
+
+        while self.framesCounter < 200:
+            self.framesCounter += 1
+            frame = self.render.getNextFrame()
+            frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+            if self.p0 is not None:
+                p2, trace_status = checkedTrace(self.gray1, frame_gray, self.p1)
+
+                self.p1 = p2[trace_status].copy()
+                self.p0 = self.p0[trace_status].copy()
+                self.gray1 = frame_gray
+
+                if len(self.p0) < 4:
+                    self.p0 = None
+                    continue
+                H, status = cv2.findHomography(self.p0, self.p1, cv2.RANSAC, 5.0)
+
+                goodPointsInRect = 0
+                goodPointsOutsideRect = 0
+                for (x0, y0), (x1, y1), good in zip(self.p0[:,0], self.p1[:,0], status[:,0]):
+                    if good:
+                        if isPointInRect((x1,y1), self.render.getCurrentRect()):
+                            goodPointsInRect += 1
+                        else: goodPointsOutsideRect += 1
+
+                if goodPointsOutsideRect < goodPointsInRect:
+                    isForegroundHomographyFound = True
+                    self.assertGreater(float(goodPointsInRect) / (self.numFeaturesInRectOnStart + 1), 0.6)
+            else:
+                p = cv2.goodFeaturesToTrack(frame_gray, **feature_params)
+
+        self.assertEqual(isForegroundHomographyFound, True)