mirror of
https://github.com/opencv/opencv.git
synced 2024-12-21 05:28:01 +08:00
105 lines
3.1 KiB
Python
Executable File
105 lines
3.1 KiB
Python
Executable File
#!/usr/bin/env python
|
|
|
|
'''
|
|
Lucas-Kanade tracker
|
|
====================
|
|
|
|
Lucas-Kanade sparse optical flow demo. Uses goodFeaturesToTrack
|
|
for track initialization and back-tracking for match verification
|
|
between frames.
|
|
|
|
Usage
|
|
-----
|
|
lk_track.py [<video_source>]
|
|
|
|
|
|
Keys
|
|
----
|
|
ESC - exit
|
|
'''
|
|
|
|
# Python 2/3 compatibility
|
|
from __future__ import print_function
|
|
|
|
import numpy as np
|
|
import cv2
|
|
import video
|
|
from common import anorm2, draw_str
|
|
from time import clock
|
|
|
|
lk_params = dict( winSize = (15, 15),
|
|
maxLevel = 2,
|
|
criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03))
|
|
|
|
feature_params = dict( maxCorners = 500,
|
|
qualityLevel = 0.3,
|
|
minDistance = 7,
|
|
blockSize = 7 )
|
|
|
|
class App:
|
|
def __init__(self, video_src):
|
|
self.track_len = 10
|
|
self.detect_interval = 5
|
|
self.tracks = []
|
|
self.cam = video.create_capture(video_src)
|
|
self.frame_idx = 0
|
|
|
|
def run(self):
|
|
while True:
|
|
_ret, frame = self.cam.read()
|
|
frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
|
|
vis = frame.copy()
|
|
|
|
if len(self.tracks) > 0:
|
|
img0, img1 = self.prev_gray, frame_gray
|
|
p0 = np.float32([tr[-1] for tr in self.tracks]).reshape(-1, 1, 2)
|
|
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)
|
|
good = d < 1
|
|
new_tracks = []
|
|
for tr, (x, y), good_flag in zip(self.tracks, p1.reshape(-1, 2), good):
|
|
if not good_flag:
|
|
continue
|
|
tr.append((x, y))
|
|
if len(tr) > self.track_len:
|
|
del tr[0]
|
|
new_tracks.append(tr)
|
|
cv2.circle(vis, (x, y), 2, (0, 255, 0), -1)
|
|
self.tracks = new_tracks
|
|
cv2.polylines(vis, [np.int32(tr) for tr in self.tracks], False, (0, 255, 0))
|
|
draw_str(vis, (20, 20), 'track count: %d' % len(self.tracks))
|
|
|
|
if self.frame_idx % self.detect_interval == 0:
|
|
mask = np.zeros_like(frame_gray)
|
|
mask[:] = 255
|
|
for x, y in [np.int32(tr[-1]) for tr in self.tracks]:
|
|
cv2.circle(mask, (x, y), 5, 0, -1)
|
|
p = cv2.goodFeaturesToTrack(frame_gray, mask = mask, **feature_params)
|
|
if p is not None:
|
|
for x, y in np.float32(p).reshape(-1, 2):
|
|
self.tracks.append([(x, y)])
|
|
|
|
|
|
self.frame_idx += 1
|
|
self.prev_gray = frame_gray
|
|
cv2.imshow('lk_track', vis)
|
|
|
|
ch = cv2.waitKey(1)
|
|
if ch == 27:
|
|
break
|
|
|
|
def main():
|
|
import sys
|
|
try:
|
|
video_src = sys.argv[1]
|
|
except:
|
|
video_src = 0
|
|
|
|
print(__doc__)
|
|
App(video_src).run()
|
|
cv2.destroyAllWindows()
|
|
|
|
if __name__ == '__main__':
|
|
main()
|