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Open Source Computer Vision Library
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114 lines
3.5 KiB
114 lines
3.5 KiB
#!/usr/bin/env python |
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''' |
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Lucas-Kanade homography tracker |
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=============================== |
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Lucas-Kanade sparse optical flow demo. Uses goodFeaturesToTrack |
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for track initialization and back-tracking for match verification |
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between frames. Finds homography between reference and current views. |
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Usage |
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----- |
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lk_homography.py [<video_source>] |
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Keys |
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---- |
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ESC - exit |
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SPACE - start tracking |
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r - toggle RANSAC |
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''' |
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import numpy as np |
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import cv2 |
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import video |
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from common import draw_str |
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lk_params = dict( winSize = (19, 19), |
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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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feature_params = dict( maxCorners = 1000, |
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qualityLevel = 0.01, |
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minDistance = 8, |
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blockSize = 19 ) |
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def checkedTrace(img0, img1, p0, back_threshold = 1.0): |
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p1, st, err = cv2.calcOpticalFlowPyrLK(img0, img1, p0, None, **lk_params) |
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p0r, st, err = cv2.calcOpticalFlowPyrLK(img1, img0, p1, None, **lk_params) |
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d = abs(p0-p0r).reshape(-1, 2).max(-1) |
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status = d < back_threshold |
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return p1, status |
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green = (0, 255, 0) |
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red = (0, 0, 255) |
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class App: |
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def __init__(self, video_src): |
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self.cam = video.create_capture(video_src) |
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self.p0 = None |
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self.use_ransac = True |
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def run(self): |
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while True: |
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ret, frame = self.cam.read() |
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frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) |
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vis = frame.copy() |
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if self.p0 is not None: |
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p2, trace_status = checkedTrace(self.gray1, frame_gray, self.p1) |
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self.p1 = p2[trace_status].copy() |
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self.p0 = self.p0[trace_status].copy() |
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self.gray1 = frame_gray |
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if len(self.p0) < 4: |
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self.p0 = None |
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continue |
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H, status = cv2.findHomography(self.p0, self.p1, (0, cv2.RANSAC)[self.use_ransac], 10.0) |
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h, w = frame.shape[:2] |
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overlay = cv2.warpPerspective(self.frame0, H, (w, h)) |
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vis = cv2.addWeighted(vis, 0.5, overlay, 0.5, 0.0) |
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for (x0, y0), (x1, y1), good in zip(self.p0[:,0], self.p1[:,0], status[:,0]): |
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if good: |
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cv2.line(vis, (x0, y0), (x1, y1), (0, 128, 0)) |
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cv2.circle(vis, (x1, y1), 2, (red, green)[good], -1) |
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draw_str(vis, (20, 20), 'track count: %d' % len(self.p1)) |
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if self.use_ransac: |
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draw_str(vis, (20, 40), 'RANSAC') |
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else: |
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p = cv2.goodFeaturesToTrack(frame_gray, **feature_params) |
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if p is not None: |
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for x, y in p[:,0]: |
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cv2.circle(vis, (x, y), 2, green, -1) |
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draw_str(vis, (20, 20), 'feature count: %d' % len(p)) |
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cv2.imshow('lk_homography', vis) |
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ch = 0xFF & cv2.waitKey(1) |
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if ch == 27: |
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break |
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if ch == ord(' '): |
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self.frame0 = frame.copy() |
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self.p0 = cv2.goodFeaturesToTrack(frame_gray, **feature_params) |
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if self.p0 is not None: |
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self.p1 = self.p0 |
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self.gray0 = frame_gray |
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self.gray1 = frame_gray |
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if ch == ord('r'): |
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self.use_ransac = not self.use_ransac |
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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 = 0 |
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print __doc__ |
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App(video_src).run() |
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cv2.destroyAllWindows() |
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if __name__ == '__main__': |
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main()
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