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Removed obsolete python samples #25268 Clean Samples #25006 This PR removes 36 obsolete python samples from the project, as part of an effort to keep the codebase clean and focused on current best practices. Some of these samples will be updated with latest algorithms or will be combined with other existing samples. Removed Samples: > browse.py camshift.py coherence.py color_histogram.py contours.py deconvolution.py dft.py dis_opt_flow.py distrans.py edge.py feature_homography.py find_obj.py fitline.py gabor_threads.py hist.py houghcircles.py houghlines.py inpaint.py kalman.py kmeans.py laplace.py lk_homography.py lk_track.py logpolar.py mosse.py mser.py opt_flow.py plane_ar.py squares.py stitching.py text_skewness_correction.py texture_flow.py turing.py video_threaded.py video_v4l2.py watershed.py These changes aim to improve the repository's clarity and usability by removing examples that are no longer relevant or have been superseded by more up-to-date techniques.
107 lines
3.1 KiB
Python
Executable File
107 lines
3.1 KiB
Python
Executable File
#!/usr/bin/env python
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'''
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Lucas-Kanade 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.
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Usage
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-----
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lk_track.py [<video_source>]
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Keys
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----
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ESC - exit
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'''
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# Python 2/3 compatibility
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from __future__ import print_function
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import numpy as np
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import cv2 as cv
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import video
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from common import anorm2, draw_str
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lk_params = dict( winSize = (15, 15),
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maxLevel = 2,
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criteria = (cv.TERM_CRITERIA_EPS | cv.TERM_CRITERIA_COUNT, 10, 0.03))
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feature_params = dict( maxCorners = 500,
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qualityLevel = 0.3,
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minDistance = 7,
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blockSize = 7 )
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class App:
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def __init__(self, video_src):
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self.track_len = 10
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self.detect_interval = 5
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self.tracks = []
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self.cam = video.create_capture(video_src)
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self.frame_idx = 0
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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 = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
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vis = frame.copy()
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if len(self.tracks) > 0:
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img0, img1 = self.prev_gray, frame_gray
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p0 = np.float32([tr[-1] for tr in self.tracks]).reshape(-1, 1, 2)
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p1, _st, _err = cv.calcOpticalFlowPyrLK(img0, img1, p0, None, **lk_params)
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p0r, _st, _err = cv.calcOpticalFlowPyrLK(img1, img0, p1, None, **lk_params)
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d = abs(p0-p0r).reshape(-1, 2).max(-1)
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good = d < 1
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new_tracks = []
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for tr, (x, y), good_flag in zip(self.tracks, p1.reshape(-1, 2), good):
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if not good_flag:
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continue
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tr.append((x, y))
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if len(tr) > self.track_len:
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del tr[0]
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new_tracks.append(tr)
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cv.circle(vis, (int(x), int(y)), 2, (0, 255, 0), -1)
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self.tracks = new_tracks
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cv.polylines(vis, [np.int32(tr) for tr in self.tracks], False, (0, 255, 0))
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draw_str(vis, (20, 20), 'track count: %d' % len(self.tracks))
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if self.frame_idx % self.detect_interval == 0:
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mask = np.zeros_like(frame_gray)
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mask[:] = 255
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for x, y in [np.int32(tr[-1]) for tr in self.tracks]:
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cv.circle(mask, (x, y), 5, 0, -1)
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p = cv.goodFeaturesToTrack(frame_gray, mask = mask, **feature_params)
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if p is not None:
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for x, y in np.float32(p).reshape(-1, 2):
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self.tracks.append([(x, y)])
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self.frame_idx += 1
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self.prev_gray = frame_gray
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cv.imshow('lk_track', vis)
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ch = cv.waitKey(1)
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if ch == 27:
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break
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def main():
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import sys
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try:
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video_src = sys.argv[1]
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except:
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video_src = 0
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App(video_src).run()
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print('Done')
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if __name__ == '__main__':
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print(__doc__)
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main()
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cv.destroyAllWindows()
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