mirror of
https://github.com/opencv/opencv.git
synced 2024-11-26 04:00:30 +08:00
121 lines
3.6 KiB
Python
Executable File
121 lines
3.6 KiB
Python
Executable File
#!/usr/bin/env python
|
|
|
|
'''
|
|
Lucas-Kanade homography tracker
|
|
===============================
|
|
|
|
Lucas-Kanade sparse optical flow demo. Uses goodFeaturesToTrack
|
|
for track initialization and back-tracking for match verification
|
|
between frames. Finds homography between reference and current views.
|
|
|
|
Usage
|
|
-----
|
|
lk_homography.py [<video_source>]
|
|
|
|
|
|
Keys
|
|
----
|
|
ESC - exit
|
|
SPACE - start tracking
|
|
r - toggle RANSAC
|
|
'''
|
|
|
|
# Python 2/3 compatibility
|
|
from __future__ import print_function
|
|
|
|
import numpy as np
|
|
import cv2 as cv
|
|
import video
|
|
from common import draw_str
|
|
from video import presets
|
|
|
|
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
|
|
|
|
green = (0, 255, 0)
|
|
red = (0, 0, 255)
|
|
|
|
class App:
|
|
def __init__(self, video_src):
|
|
self.cam = self.cam = video.create_capture(video_src, presets['book'])
|
|
self.p0 = None
|
|
self.use_ransac = True
|
|
|
|
def run(self):
|
|
while True:
|
|
_ret, frame = self.cam.read()
|
|
frame_gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
|
|
vis = frame.copy()
|
|
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, (0, cv.RANSAC)[self.use_ransac], 10.0)
|
|
h, w = frame.shape[:2]
|
|
overlay = cv.warpPerspective(self.frame0, H, (w, h))
|
|
vis = cv.addWeighted(vis, 0.5, overlay, 0.5, 0.0)
|
|
|
|
for (x0, y0), (x1, y1), good in zip(self.p0[:,0], self.p1[:,0], status[:,0]):
|
|
if good:
|
|
cv.line(vis, (x0, y0), (x1, y1), (0, 128, 0))
|
|
cv.circle(vis, (x1, y1), 2, (red, green)[good], -1)
|
|
draw_str(vis, (20, 20), 'track count: %d' % len(self.p1))
|
|
if self.use_ransac:
|
|
draw_str(vis, (20, 40), 'RANSAC')
|
|
else:
|
|
p = cv.goodFeaturesToTrack(frame_gray, **feature_params)
|
|
if p is not None:
|
|
for x, y in p[:,0]:
|
|
cv.circle(vis, (x, y), 2, green, -1)
|
|
draw_str(vis, (20, 20), 'feature count: %d' % len(p))
|
|
|
|
cv.imshow('lk_homography', vis)
|
|
|
|
ch = cv.waitKey(1)
|
|
if ch == 27:
|
|
break
|
|
if ch == ord(' '):
|
|
self.frame0 = frame.copy()
|
|
self.p0 = cv.goodFeaturesToTrack(frame_gray, **feature_params)
|
|
if self.p0 is not None:
|
|
self.p1 = self.p0
|
|
self.gray0 = frame_gray
|
|
self.gray1 = frame_gray
|
|
if ch == ord('r'):
|
|
self.use_ransac = not self.use_ransac
|
|
|
|
|
|
|
|
def main():
|
|
import sys
|
|
try:
|
|
video_src = sys.argv[1]
|
|
except:
|
|
video_src = 0
|
|
|
|
print(__doc__)
|
|
App(video_src).run()
|
|
cv.destroyAllWindows()
|
|
|
|
if __name__ == '__main__':
|
|
main()
|