mirror of
https://github.com/opencv/opencv.git
synced 2024-12-26 18:58:16 +08:00
101 lines
3.5 KiB
Python
101 lines
3.5 KiB
Python
#!/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 as cv
|
|
|
|
#local modules
|
|
from tst_scene_render import TestSceneRender
|
|
from tests_common import NewOpenCVTests, isPointInRect
|
|
|
|
lk_params = dict( winSize = (19, 19),
|
|
maxLevel = 2,
|
|
criteria = (cv.TERM_CRITERIA_EPS | cv.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 = cv.calcOpticalFlowPyrLK(img0, img1, p0, None, **lk_params)
|
|
p0r, _st, _err = cv.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 = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
|
|
self.frame0 = frame.copy()
|
|
self.p0 = cv.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 = cv.cvtColor(frame, cv.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 = cv.findHomography(self.p0, self.p1, cv.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:
|
|
self.p0 = cv.goodFeaturesToTrack(frame_gray, **feature_params)
|
|
|
|
self.assertEqual(isForegroundHomographyFound, True)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
NewOpenCVTests.bootstrap()
|