annotate OrthancStone/Resources/Computations/IntersectSegmentAndHorizontalLine.py @ 2070:82dbe2729b69 deep-learning

separation of deep learning resources
author Sebastien Jodogne <s.jodogne@gmail.com>
date Fri, 19 May 2023 17:19:50 +0200
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1 #!/usr/bin/env python
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2
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3 # Stone of Orthanc
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4 # Copyright (C) 2012-2016 Sebastien Jodogne, Medical Physics
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5 # Department, University Hospital of Liege, Belgium
1871
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6 # Copyright (C) 2017-2022 Osimis S.A., Belgium
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7 # Copyright (C) 2021-2022 Sebastien Jodogne, ICTEAM UCLouvain, Belgium
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8 #
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9 # This program is free software: you can redistribute it and/or
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10 # modify it under the terms of the GNU Lesser General Public License
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11 # as published by the Free Software Foundation, either version 3 of
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12 # the License, or (at your option) any later version.
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13 #
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14 # This program is distributed in the hope that it will be useful, but
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15 # WITHOUT ANY WARRANTY; without even the implied warranty of
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16 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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17 # Lesser General Public License for more details.
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18 #
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19 # You should have received a copy of the GNU Lesser General Public
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20 # License along with this program. If not, see
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21 # <http://www.gnu.org/licenses/>.
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22
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24 from sympy import *
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25
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26 # Intersection between the 2D line segment (prevX,prevY)-(curX,curY) and the
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27 # horizontal line "y = y0" using homogeneous coordinates
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28
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29 prevX, prevY, curX, curY, y0 = symbols('prevX prevY curX curY y0')
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30
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31 p1 = Matrix([prevX, prevY, 1])
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32 p2 = Matrix([curX, curY, 1])
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33 l1 = p1.cross(p2)
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34
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35 h1 = Matrix([0, y0, 1])
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36 h2 = Matrix([1, y0, 1])
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37 l2 = h1.cross(h2)
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38
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39 a = l1.cross(l2)
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41 #pprint(cse(a/a[2], symbols = symbols('a b')))
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42 pprint(a / a[2])