added lk_track.py sample (currently as a comparison between flow tracker implementations)

pull/13383/head
Alexander Mordvintsev 14 years ago
parent 086643f5a7
commit 4151a4590e
  1. 4
      samples/python2/facedetect.py
  2. 87
      samples/python2/lk_track.py

@ -15,7 +15,7 @@ def detect(img, cascade):
def draw_rects(img, rects, color):
for x1, y1, x2, y2 in rects:
cv2.rectangle(img, (x1, y1), (x2, y2), color)
cv2.rectangle(img, (x1, y1), (x2, y2), color, 2)
if __name__ == '__main__':
import sys, getopt
@ -38,7 +38,7 @@ if __name__ == '__main__':
gray = cv2.cvtColor(img, cv.CV_BGR2GRAY)
gray = cv2.equalizeHist(gray)
rects = detect(gray, cascade)
vis = cv2.cvtColor(gray, cv.CV_GRAY2BGR)
vis = img.copy()
draw_rects(vis, rects, (0, 255, 0))
for x1, y1, x2, y2 in rects:
roi = gray[y1:y2, x1:x2]

@ -0,0 +1,87 @@
import numpy as np
import cv2, cv
import video
from common import anorm2, draw_str
from time import clock
help_message = '''
USAGE: lk_track.py [<video_source>]
Keys:
1 - toggle old/new CalcOpticalFlowPyrLK implementation
SPACE - reset features
'''
lk_params = dict( winSize = (3, 3),
maxLevel = 2,
criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03),
derivLambda = 0.0 )
feature_params = dict( maxCorners = 500,
qualityLevel = 0.1,
minDistance = 5,
blockSize = 5 )
def calc_flow_old(img0, img1, p0):
p0 = [(x, y) for x, y in p0.reshape(-1, 2)]
h, w = img0.shape[:2]
img0_cv = cv.CreateMat(h, w, cv.CV_8U)
img1_cv = cv.CreateMat(h, w, cv.CV_8U)
np.asarray(img0_cv)[:] = img0
np.asarray(img1_cv)[:] = img1
t = clock()
features, status, error = cv.CalcOpticalFlowPyrLK(img0_cv, img1_cv, None, None, p0,
lk_params['winSize'], lk_params['maxLevel'], (cv.CV_TERMCRIT_EPS | cv.CV_TERMCRIT_ITER, 10, 0.03), 0, p0)
return np.float32(features), status, error, clock()-t
def main():
import sys
try: video_src = sys.argv[1]
except: video_src = video.presets['chess']
track_len = 4
tracks = []
cam = video.create_capture(video_src)
old_mode = True
while True:
ret, frame = cam.read()
vis = frame.copy()
if len(tracks) > 0:
p0 = np.float32([tr[-1] for tr in tracks]).reshape(-1, 1, 2)
img0 = cv2.cvtColor(prev_frame, cv.CV_BGR2GRAY)
img1 = cv2.cvtColor(frame, cv.CV_BGR2GRAY)
if old_mode:
p1, st, err, dt = calc_flow_old(img0, img1, p0)
else:
t = clock()
p1, st, err = cv2.calcOpticalFlowPyrLK(img0, img1, p0, **lk_params)
dt = clock()-t
for tr, (x, y) in zip(tracks, p1.reshape(-1, 2)):
tr.append((x, y))
if len(tr) > 10:
del tr[0]
cv2.circle(vis, (x, y), 2, (0, 255, 0), -2)
cv2.polylines(vis, [np.int32(tr) for tr in tracks], False, (0, 255, 0))
draw_str(vis, (20, 20), ['new', 'old'][old_mode]+' mode')
draw_str(vis, (20, 40), 'time: %.02f ms' % (dt*1000))
prev_frame = frame.copy()
cv2.imshow('img', vis)
ch = cv2.waitKey(5)
if ch == 27:
break
if ch == ord(' ') or len(tracks) == 0:
gray = cv2.cvtColor(frame, cv.CV_BGR2GRAY)
p = cv2.goodFeaturesToTrack(gray, **feature_params)
p = [] if p is None else p.reshape(-1, 2)
tracks = []
for x, y in np.float32(p):
tracks.append([(x, y)])
if ch == ord('1'):
old_mode = not old_mode
if __name__ == '__main__':
main()
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