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100 lines
3.5 KiB
100 lines
3.5 KiB
#!/usr/bin/env python |
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''' |
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Lucas-Kanade homography tracker test |
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=============================== |
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Uses goodFeaturesToTrack for track initialization and back-tracking for match verification |
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between frames. Finds homography between reference and current views. |
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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 numpy as np |
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import cv2 as cv |
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#local modules |
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from tst_scene_render import TestSceneRender |
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from tests_common import NewOpenCVTests, isPointInRect |
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lk_params = dict( winSize = (19, 19), |
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maxLevel = 2, |
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criteria = (cv.TERM_CRITERIA_EPS | cv.TERM_CRITERIA_COUNT, 10, 0.03)) |
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feature_params = dict( maxCorners = 1000, |
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qualityLevel = 0.01, |
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minDistance = 8, |
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blockSize = 19 ) |
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def checkedTrace(img0, img1, p0, back_threshold = 1.0): |
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p1, _st, _err = cv.calcOpticalFlowPyrLK(img0, img1, p0, None, **lk_params) |
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p0r, _st, _err = cv.calcOpticalFlowPyrLK(img1, img0, p1, None, **lk_params) |
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d = abs(p0-p0r).reshape(-1, 2).max(-1) |
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status = d < back_threshold |
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return p1, status |
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class lk_homography_test(NewOpenCVTests): |
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render = None |
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framesCounter = 0 |
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frame = frame0 = None |
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p0 = None |
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p1 = None |
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gray0 = gray1 = None |
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numFeaturesInRectOnStart = 0 |
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def test_lk_homography(self): |
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self.render = TestSceneRender(self.get_sample('samples/data/graf1.png'), |
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self.get_sample('samples/data/box.png'), noise = 0.1, speed = 1.0) |
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frame = self.render.getNextFrame() |
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frame_gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY) |
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self.frame0 = frame.copy() |
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self.p0 = cv.goodFeaturesToTrack(frame_gray, **feature_params) |
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isForegroundHomographyFound = False |
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if self.p0 is not None: |
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self.p1 = self.p0 |
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self.gray0 = frame_gray |
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self.gray1 = frame_gray |
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currRect = self.render.getCurrentRect() |
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for (x,y) in self.p0[:,0]: |
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if isPointInRect((x,y), currRect): |
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self.numFeaturesInRectOnStart += 1 |
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while self.framesCounter < 200: |
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self.framesCounter += 1 |
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frame = self.render.getNextFrame() |
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frame_gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY) |
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if self.p0 is not None: |
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p2, trace_status = checkedTrace(self.gray1, frame_gray, self.p1) |
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self.p1 = p2[trace_status].copy() |
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self.p0 = self.p0[trace_status].copy() |
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self.gray1 = frame_gray |
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if len(self.p0) < 4: |
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self.p0 = None |
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continue |
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_H, status = cv.findHomography(self.p0, self.p1, cv.RANSAC, 5.0) |
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goodPointsInRect = 0 |
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goodPointsOutsideRect = 0 |
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for (_x0, _y0), (x1, y1), good in zip(self.p0[:,0], self.p1[:,0], status[:,0]): |
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if good: |
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if isPointInRect((x1,y1), self.render.getCurrentRect()): |
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goodPointsInRect += 1 |
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else: goodPointsOutsideRect += 1 |
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if goodPointsOutsideRect < goodPointsInRect: |
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isForegroundHomographyFound = True |
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self.assertGreater(float(goodPointsInRect) / (self.numFeaturesInRectOnStart + 1), 0.6) |
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else: |
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self.p0 = cv.goodFeaturesToTrack(frame_gray, **feature_params) |
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self.assertEqual(isForegroundHomographyFound, True) |
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if __name__ == '__main__': |
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NewOpenCVTests.bootstrap()
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