1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
|
%global _empty_manifest_terminate_build 0
Name: python-upolygon
Version: 0.1.10
Release: 1
Summary: Collection of fast polygon operations for DL
License: MIT License
URL: https://github.com/v7labs/upolygon
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/59/c7/68a4a1124465b8bc8cd3cd8ea127dcdaf61ddc6f21ec92916d31a09b244e/upolygon-0.1.10.tar.gz
%description
# uPolygon
Library of handy polygon related functions to speed up machine learning projects.
It was born as a replacement for `cv2.fillPoly` when generating masks for instance segmentation, without having to bring in all of opencv.
## TODO
- [x] draw_polygon
- [x] find_contours
- [ ] polygon_area
- [ ] point_in_polygon
## Usage
This library expects all polygons to be model as a list of paths, each path is a list of alternating x and y coordinates (`[x1,y1,x2,y2,...]`).
A simple triangle would be declared as:
```python
triangle = [[50,50, 100,0, 0,0]]
```
Complex polygons (holes and/or disjoints) follow the even-odd rule.
## draw_polygon
`draw_polygon(mask: array[:, :], paths: path[]) -> array[:, :]`
```python
from upolygon import draw_polygon
import numpy as np
mask = np.zeros((100,100), dtype=np.int32)
draw_polygon(mask, [[50,50, 100,0, 0,0]], 1)
```
Equivalent of calling `cv2.fillPoly(mask, [np.array([[50,50], [100,0], [0,0]])], 1)` or `cv2.drawContours(mask, [np.array([[50,50], [100,0], [0,0]])], -1, 1, cv2.FILLED)` when using opencv.
uPolygon is ~ 6 times faster than opencv for large random polygons with many intersecting lines.
For smaller polygons or few intersections, uPolygon is half as fast as opencv.
## find_contours
`find_contours(mask: array[:, :]) -> (array[:, :], path[:], path[:])`
0 is treated as background, 1 is treated as foreground.
```python
from upolygon import find_contours
import numpy as np
mask = np.array([
[0, 0, 0, 0, 0],
[0, 1, 1, 1, 0],
[0, 1, 1, 1, 0],
[0, 1, 1, 1, 0]
], dtype=np.uint8)
_labels, external_paths, internal_paths = find_contours(mask)
```
Similar to OpenCV's `cv2.findContours` but lacking hierarchies. Also similar to BoofCV's `LinearContourLabelChang2004` which is based on the same [algorithm](https://www.iis.sinica.edu.tw/papers/fchang/1362-F.pdf).
Note that currently the input mask to find_contour needs to be uint8.
## rle_encode
`rle_encode(mask: array[:,:]) -> list`
Takes a 2-dim binary mask and generates a run length encoding according to the coco specs
~ 15 times faster than written in plain python
%package -n python3-upolygon
Summary: Collection of fast polygon operations for DL
Provides: python-upolygon
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
BuildRequires: python3-cffi
BuildRequires: gcc
BuildRequires: gdb
%description -n python3-upolygon
# uPolygon
Library of handy polygon related functions to speed up machine learning projects.
It was born as a replacement for `cv2.fillPoly` when generating masks for instance segmentation, without having to bring in all of opencv.
## TODO
- [x] draw_polygon
- [x] find_contours
- [ ] polygon_area
- [ ] point_in_polygon
## Usage
This library expects all polygons to be model as a list of paths, each path is a list of alternating x and y coordinates (`[x1,y1,x2,y2,...]`).
A simple triangle would be declared as:
```python
triangle = [[50,50, 100,0, 0,0]]
```
Complex polygons (holes and/or disjoints) follow the even-odd rule.
## draw_polygon
`draw_polygon(mask: array[:, :], paths: path[]) -> array[:, :]`
```python
from upolygon import draw_polygon
import numpy as np
mask = np.zeros((100,100), dtype=np.int32)
draw_polygon(mask, [[50,50, 100,0, 0,0]], 1)
```
Equivalent of calling `cv2.fillPoly(mask, [np.array([[50,50], [100,0], [0,0]])], 1)` or `cv2.drawContours(mask, [np.array([[50,50], [100,0], [0,0]])], -1, 1, cv2.FILLED)` when using opencv.
uPolygon is ~ 6 times faster than opencv for large random polygons with many intersecting lines.
For smaller polygons or few intersections, uPolygon is half as fast as opencv.
## find_contours
`find_contours(mask: array[:, :]) -> (array[:, :], path[:], path[:])`
0 is treated as background, 1 is treated as foreground.
```python
from upolygon import find_contours
import numpy as np
mask = np.array([
[0, 0, 0, 0, 0],
[0, 1, 1, 1, 0],
[0, 1, 1, 1, 0],
[0, 1, 1, 1, 0]
], dtype=np.uint8)
_labels, external_paths, internal_paths = find_contours(mask)
```
Similar to OpenCV's `cv2.findContours` but lacking hierarchies. Also similar to BoofCV's `LinearContourLabelChang2004` which is based on the same [algorithm](https://www.iis.sinica.edu.tw/papers/fchang/1362-F.pdf).
Note that currently the input mask to find_contour needs to be uint8.
## rle_encode
`rle_encode(mask: array[:,:]) -> list`
Takes a 2-dim binary mask and generates a run length encoding according to the coco specs
~ 15 times faster than written in plain python
%package help
Summary: Development documents and examples for upolygon
Provides: python3-upolygon-doc
%description help
# uPolygon
Library of handy polygon related functions to speed up machine learning projects.
It was born as a replacement for `cv2.fillPoly` when generating masks for instance segmentation, without having to bring in all of opencv.
## TODO
- [x] draw_polygon
- [x] find_contours
- [ ] polygon_area
- [ ] point_in_polygon
## Usage
This library expects all polygons to be model as a list of paths, each path is a list of alternating x and y coordinates (`[x1,y1,x2,y2,...]`).
A simple triangle would be declared as:
```python
triangle = [[50,50, 100,0, 0,0]]
```
Complex polygons (holes and/or disjoints) follow the even-odd rule.
## draw_polygon
`draw_polygon(mask: array[:, :], paths: path[]) -> array[:, :]`
```python
from upolygon import draw_polygon
import numpy as np
mask = np.zeros((100,100), dtype=np.int32)
draw_polygon(mask, [[50,50, 100,0, 0,0]], 1)
```
Equivalent of calling `cv2.fillPoly(mask, [np.array([[50,50], [100,0], [0,0]])], 1)` or `cv2.drawContours(mask, [np.array([[50,50], [100,0], [0,0]])], -1, 1, cv2.FILLED)` when using opencv.
uPolygon is ~ 6 times faster than opencv for large random polygons with many intersecting lines.
For smaller polygons or few intersections, uPolygon is half as fast as opencv.
## find_contours
`find_contours(mask: array[:, :]) -> (array[:, :], path[:], path[:])`
0 is treated as background, 1 is treated as foreground.
```python
from upolygon import find_contours
import numpy as np
mask = np.array([
[0, 0, 0, 0, 0],
[0, 1, 1, 1, 0],
[0, 1, 1, 1, 0],
[0, 1, 1, 1, 0]
], dtype=np.uint8)
_labels, external_paths, internal_paths = find_contours(mask)
```
Similar to OpenCV's `cv2.findContours` but lacking hierarchies. Also similar to BoofCV's `LinearContourLabelChang2004` which is based on the same [algorithm](https://www.iis.sinica.edu.tw/papers/fchang/1362-F.pdf).
Note that currently the input mask to find_contour needs to be uint8.
## rle_encode
`rle_encode(mask: array[:,:]) -> list`
Takes a 2-dim binary mask and generates a run length encoding according to the coco specs
~ 15 times faster than written in plain python
%prep
%autosetup -n upolygon-0.1.10
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-upolygon -f filelist.lst
%dir %{python3_sitearch}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 0.1.10-1
- Package Spec generated
|
