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Open Source Computer Vision Library
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64 lines
1.7 KiB
64 lines
1.7 KiB
''' |
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Multiscale Turing Patterns generator |
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==================================== |
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Inspired by http://www.jonathanmccabe.com/Cyclic_Symmetric_Multi-Scale_Turing_Patterns.pdf |
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''' |
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import numpy as np |
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import cv2 |
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import cv2.cv as cv |
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from common import draw_str |
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import getopt, sys |
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from itertools import count |
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help_message = ''' |
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USAGE: turing.py [-o <output.avi>] |
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Press ESC to stop. |
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''' |
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if __name__ == '__main__': |
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print help_message |
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w, h = 512, 512 |
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args, args_list = getopt.getopt(sys.argv[1:], 'o:', []) |
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args = dict(args) |
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out = None |
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if '-o' in args: |
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fn = args['-o'] |
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out = cv2.VideoWriter(args['-o'], cv.CV_FOURCC(*'DIB '), 30.0, (w, h), False) |
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print 'writing %s ...' % fn |
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a = np.zeros((h, w), np.float32) |
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cv2.randu(a, np.array([0]), np.array([1])) |
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def process_scale(a_lods, lod): |
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d = a_lods[lod] - cv2.pyrUp(a_lods[lod+1]) |
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for i in xrange(lod): |
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d = cv2.pyrUp(d) |
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v = cv2.GaussianBlur(d*d, (3, 3), 0) |
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return np.sign(d), v |
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scale_num = 6 |
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for frame_i in count(): |
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a_lods = [a] |
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for i in xrange(scale_num): |
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a_lods.append(cv2.pyrDown(a_lods[-1])) |
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ms, vs = [], [] |
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for i in xrange(1, scale_num): |
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m, v = process_scale(a_lods, i) |
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ms.append(m) |
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vs.append(v) |
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mi = np.argmin(vs, 0) |
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a += np.choose(mi, ms) * 0.025 |
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a = (a-a.min()) / a.ptp() |
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if out: |
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out.write(a) |
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vis = a.copy() |
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draw_str(vis, (20, 20), 'frame %d' % frame_i) |
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cv2.imshow('a', vis) |
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if cv2.waitKey(5) == 27: |
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break
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