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88 lines
3.0 KiB
Python
88 lines
3.0 KiB
Python
import numpy as np
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import cv2
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import cv2.cv as cv
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import video
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from common import anorm2, draw_str
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from time import clock
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help_message = '''
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USAGE: lk_track.py [<video_source>]
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Keys:
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1 - toggle old/new CalcOpticalFlowPyrLK implementation
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SPACE - reset features
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'''
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lk_params = dict( winSize = (21, 21),
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maxLevel = 2,
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criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03),
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derivLambda = 0.0 )
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feature_params = dict( maxCorners = 1000,
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qualityLevel = 0.1,
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minDistance = 5,
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blockSize = 5 )
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def calc_flow_old(img0, img1, p0):
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p0 = [(x, y) for x, y in p0.reshape(-1, 2)]
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h, w = img0.shape[:2]
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img0_cv = cv.CreateMat(h, w, cv.CV_8U)
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img1_cv = cv.CreateMat(h, w, cv.CV_8U)
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np.asarray(img0_cv)[:] = img0
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np.asarray(img1_cv)[:] = img1
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t = clock()
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features, status, error = cv.CalcOpticalFlowPyrLK(img0_cv, img1_cv, None, None, p0,
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lk_params['winSize'], lk_params['maxLevel'], lk_params['criteria'], 0, p0)
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return np.float32(features), status, error, clock()-t
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def main():
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import sys
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try: video_src = sys.argv[1]
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except: video_src = video.presets['chess']
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print help_message
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track_len = 4
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tracks = []
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cam = video.create_capture(video_src)
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old_mode = True
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while True:
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ret, frame = cam.read()
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vis = frame.copy()
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if len(tracks) > 0:
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p0 = np.float32([tr[-1] for tr in tracks]).reshape(-1, 1, 2)
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img0 = cv2.cvtColor(prev_frame, cv2.COLOR_BGR2GRAY)
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img1 = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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if old_mode:
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p1, st, err, dt = calc_flow_old(img0, img1, p0)
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else:
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t = clock()
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p1, st, err = cv2.calcOpticalFlowPyrLK(img0, img1, p0, None, **lk_params)
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dt = clock()-t
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for tr, (x, y) in zip(tracks, p1.reshape(-1, 2)):
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tr.append((x, y))
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if len(tr) > 10:
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del tr[0]
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cv2.circle(vis, (x, y), 2, (0, 255, 0), -1)
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cv2.polylines(vis, [np.int32(tr) for tr in tracks], False, (0, 255, 0))
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draw_str(vis, (20, 20), ['new', 'old'][old_mode]+' mode')
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draw_str(vis, (20, 40), 'time: %.02f ms' % (dt*1000))
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prev_frame = frame.copy()
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cv2.imshow('lk_track', vis)
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ch = cv2.waitKey(5)
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if ch == 27:
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break
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if ch == ord(' ') or len(tracks) == 0:
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gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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p = cv2.goodFeaturesToTrack(gray, **feature_params)
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p = [] if p is None else p.reshape(-1, 2)
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tracks = []
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for x, y in np.float32(p):
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tracks.append([(x, y)])
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if ch == ord('1'):
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old_mode = not old_mode
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if __name__ == '__main__':
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main()
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