forked from opendatalab/MinerU
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathtest_unit.py
530 lines (472 loc) · 29.3 KB
/
test_unit.py
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
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
import pytest
import os
from magic_pdf.libs.boxbase import _is_in_or_part_overlap, _is_in_or_part_overlap_with_area_ratio, _is_in, \
_is_part_overlap, _left_intersect, _right_intersect, _is_vertical_full_overlap, _is_bottom_full_overlap, \
_is_left_overlap, __is_overlaps_y_exceeds_threshold, calculate_iou, calculate_overlap_area_2_minbox_area_ratio, \
calculate_overlap_area_in_bbox1_area_ratio, get_minbox_if_overlap_by_ratio, get_bbox_in_boundry, \
find_top_nearest_text_bbox, find_bottom_nearest_text_bbox, find_left_nearest_text_bbox, \
find_right_nearest_text_bbox, bbox_relative_pos, bbox_distance
from magic_pdf.libs.commons import mymax, join_path, get_top_percent_list
from magic_pdf.libs.config_reader import get_s3_config
from magic_pdf.libs.path_utils import parse_s3path
# 输入一个列表,如果列表空返回0,否则返回最大元素
@pytest.mark.parametrize("list_input, target_num",
[
([0, 0, 0, 0], 0),
([0], 0),
([1, 2, 5, 8, 4], 8),
([], 0),
([1.1, 7.6, 1.009, 9.9], 9.9),
([1.0 * 10 ** 2, 3.5 * 10 ** 3, 0.9 * 10 ** 6], 0.9 * 10 ** 6),
])
def test_list_max(list_input: list, target_num) -> None:
"""
list_input: 输入列表元素,元素均为数字类型
"""
assert target_num == mymax(list_input)
# 连接多个参数生成路径信息,使用"/"作为连接符,生成的结果需要是一个合法路径
@pytest.mark.parametrize("path_input, target_path", [
(['https:', '', 'www.baidu.com'], 'https://www.baidu.com'),
(['https:', 'www.baidu.com'], 'https:/www.baidu.com'),
(['D:', 'file', 'pythonProject', 'demo' + '.py'], 'D:/file/pythonProject/demo.py'),
])
def test_join_path(path_input: list, target_path: str) -> None:
"""
path_input: 输入path的列表,列表元素均为字符串
"""
assert target_path == join_path(*path_input)
# 获取列表中前百分之多少的元素
@pytest.mark.parametrize("num_list, percent, target_num_list", [
([], 0.75, []),
([-5, -10, 9, 3, 7, -7, 0, 23, -1, -11], 0.8, [23, 9, 7, 3, 0, -1, -5, -7]),
([-5, -10, 9, 3, 7, -7, 0, 23, -1, -11], 0, []),
([-5, -10, 9, 3, 7, -7, 0, 23, -1, -11, 28], 0.8, [28, 23, 9, 7, 3, 0, -1, -5])
])
def test_get_top_percent_list(num_list: list, percent: float, target_num_list: list) -> None:
"""
num_list: 数字列表,列表元素为数字
percent: 占比,float, 向下取证
"""
assert target_num_list == get_top_percent_list(num_list, percent)
# 输入一个s3路径,返回bucket名字和其余部分(key)
@pytest.mark.parametrize("s3_path, target_data", [
("s3://bucket/path/to/my/file.txt", "bucket"),
("s3a://bucket1/path/to/my/file2.txt", "bucket1"),
# ("/path/to/my/file1.txt", "path"),
# ("bucket/path/to/my/file2.txt", "bucket"),
])
def test_parse_s3path(s3_path: str, target_data: str):
"""
s3_path: s3路径
如果为无效路径,则返回对应的bucket名字和其余部分
如果为异常路径 例如:file2.txt,则报异常
"""
bucket_name, key = parse_s3path(s3_path)
assert target_data == bucket_name
# 2个box是否处于包含或者部分重合关系。
# 如果某边界重合算重合。
# 部分边界重合,其他在内部也算包含
@pytest.mark.parametrize("box1, box2, target_bool", [
((120, 133, 223, 248), (128, 168, 269, 295), True),
((137, 53, 245, 157), (134, 11, 200, 147), True), # 部分重合
((137, 56, 211, 116), (140, 66, 202, 199), True), # 部分重合
((42, 34, 69, 65), (42, 34, 69, 65), True), # 部分重合
((39, 63, 87, 106), (37, 66, 85, 109), True), # 部分重合
((13, 37, 55, 66), (7, 46, 49, 75), True), # 部分重合
((56, 83, 85, 104), (64, 85, 93, 106), True), # 部分重合
((12, 53, 48, 94), (14, 53, 50, 94), True), # 部分重合
((43, 54, 93, 131), (55, 82, 77, 106), True), # 包含
((63, 2, 134, 71), (72, 43, 104, 78), True), # 包含
((25, 57, 109, 127), (26, 73, 49, 95), True), # 包含
((24, 47, 111, 115), (34, 81, 58, 106), True), # 包含
((34, 8, 105, 83), (76, 20, 116, 45), True), # 包含
])
def test_is_in_or_part_overlap(box1: tuple, box2: tuple, target_bool: bool) -> None:
"""
box1: 坐标数组
box2: 坐标数组
"""
assert target_bool == _is_in_or_part_overlap(box1, box2)
# 如果box1在box2内部,返回True
# 如果是部分重合的,则重合面积占box1的比例大于阈值时候返回True
@pytest.mark.parametrize("box1, box2, target_bool", [
((35, 28, 108, 90), (47, 60, 83, 96), False), # 包含 box1 up box2, box2 多半,box1少半
((65, 151, 92, 177), (49, 99, 105, 198), True), # 包含 box1 in box2
((80, 62, 112, 84), (74, 40, 144, 111), True), # 包含 box1 in box2
((65, 88, 127, 144), (92, 102, 131, 139), False), # 包含 box2 多半,box1约一半
((92, 102, 131, 139), (65, 88, 127, 144), True), # 包含 box1 多半
((100, 93, 199, 168), (169, 126, 198, 165), False), # 包含 box2 in box1
((26, 75, 106, 172), (65, 108, 90, 128), False), # 包含 box2 in box1
((28, 90, 77, 126), (35, 84, 84, 120), True), # 相交 box1多半,box2多半
((37, 6, 69, 52), (28, 3, 60, 49), True), # 相交 box1多半,box2多半
((94, 29, 133, 60), (84, 30, 123, 61), True), # 相交 box1多半,box2多半
])
def test_is_in_or_part_overlap_with_area_ratio(box1: tuple, box2: tuple, target_bool: bool) -> None:
out_bool = _is_in_or_part_overlap_with_area_ratio(box1, box2)
assert target_bool == out_bool
# box1在box2内部或者box2在box1内部返回True。如果部分边界重合也算作包含。
@pytest.mark.parametrize("box1, box2, target_bool", [
# ((), (), "Error"), # Error
((65, 151, 92, 177), (49, 99, 105, 198), True), # 包含 box1 in box2
((80, 62, 112, 84), (74, 40, 144, 111), True), # 包含 box1 in box2
((76, 140, 154, 277), (121, 326, 192, 384), False), # 分离
((65, 88, 127, 144), (92, 102, 131, 139), False), # 包含 box2 多半,box1约一半
((92, 102, 131, 139), (65, 88, 127, 144), False), # 包含 box1 多半
((68, 94, 118, 120), (68, 90, 118, 122), True), # 包含,box1 in box2 两边x相切
((69, 94, 118, 120), (68, 90, 118, 122), True), # 包含,box1 in box2 一边x相切
((69, 114, 118, 122), (68, 90, 118, 122), True), # 包含,box1 in box2 一边y相切
# ((100, 93, 199, 168), (169, 126, 198, 165), True), # 包含 box2 in box1 Error
# ((26, 75, 106, 172), (65, 108, 90, 128), True), # 包含 box2 in box1 Error
# ((38, 94, 122, 120), (68, 94, 118, 120), True), # 包含,box2 in box1 两边y相切 Error
# ((68, 34, 118, 158), (68, 94, 118, 120), True), # 包含,box2 in box1 两边x相切 Error
# ((68, 34, 118, 158), (68, 94, 84, 120), True), # 包含,box2 in box1 一边x相切 Error
# ((27, 94, 118, 158), (68, 94, 84, 120), True), # 包含,box2 in box1 一边y相切 Error
])
def test_is_in(box1: tuple, box2: tuple, target_bool: bool) -> None:
assert target_bool == _is_in(box1, box2)
# 仅仅是部分包含关系,返回True,如果是完全包含关系则返回False
@pytest.mark.parametrize("box1, box2, target_bool", [
((65, 151, 92, 177), (49, 99, 105, 198), False), # 包含 box1 in box2
((80, 62, 112, 84), (74, 40, 144, 111), False), # 包含 box1 in box2
# ((76, 140, 154, 277), (121, 326, 192, 384), False), # 分离 Error
((76, 140, 154, 277), (121, 277, 192, 384), True), # 外相切
((65, 88, 127, 144), (92, 102, 131, 139), True), # 包含 box2 多半,box1约一半
((92, 102, 131, 139), (65, 88, 127, 144), True), # 包含 box1 多半
((68, 94, 118, 120), (68, 90, 118, 122), False), # 包含,box1 in box2 两边x相切
((69, 94, 118, 120), (68, 90, 118, 122), False), # 包含,box1 in box2 一边x相切
((69, 114, 118, 122), (68, 90, 118, 122), False), # 包含,box1 in box2 一边y相切
# ((26, 75, 106, 172), (65, 108, 90, 128), False), # 包含 box2 in box1 Error
# ((38, 94, 122, 120), (68, 94, 118, 120), False), # 包含,box2 in box1 两边y相切 Error
# ((68, 34, 118, 158), (68, 94, 84, 120), False), # 包含,box2 in box1 一边x相切 Error
])
def test_is_part_overlap(box1: tuple, box2: tuple, target_bool: bool) -> None:
assert target_bool == _is_part_overlap(box1, box2)
# left_box右侧是否和right_box左侧有部分重叠
@pytest.mark.parametrize("box1, box2, target_bool", [
(None, None, False),
((88, 81, 222, 173), (60, 221, 123, 358), False), # 分离
((121, 149, 184, 289), (172, 130, 230, 268), True), # box1 left bottom box2 相交
((172, 130, 230, 268), (121, 149, 184, 289), False), # box2 left bottom box1 相交
((109, 68, 182, 146), (215, 188, 277, 253), False), # box1 top left box2 分离
((117, 53, 222, 176), (174, 142, 298, 276), True), # box1 left top box2 相交
((174, 142, 298, 276), (117, 53, 222, 176), False), # box2 left top box1 相交
((65, 88, 127, 144), (92, 102, 131, 139), True), # box1 left box2 y:box2 in box1
((92, 102, 131, 139), (65, 88, 127, 144), False), # box2 left box1 y:box1 in box2
((182, 130, 230, 268), (121, 149, 174, 289), False), # box2 left box1 分离
((1, 10, 26, 45), (3, 4, 20, 39), True), # box1 bottom box2 x:box2 in box1
])
def test_left_intersect(box1: tuple, box2: tuple, target_bool: bool) -> None:
assert target_bool == _left_intersect(box1, box2)
# left_box左侧是否和right_box右侧部分重叠
@pytest.mark.parametrize("box1, box2, target_bool", [
(None, None, False),
((88, 81, 222, 173), (60, 221, 123, 358), False), # 分离
((121, 149, 184, 289), (172, 130, 230, 268), False), # box1 left bottom box2 相交
((172, 130, 230, 268), (121, 149, 184, 289), True), # box2 left bottom box1 相交
((109, 68, 182, 146), (215, 188, 277, 253), False), # box1 top left box2 分离
((117, 53, 222, 176), (174, 142, 298, 276), False), # box1 left top box2 相交
((174, 142, 298, 276), (117, 53, 222, 176), True), # box2 left top box1 相交
((65, 88, 127, 144), (92, 102, 131, 139), False), # box1 left box2 y:box2 in box1
# ((92, 102, 131, 139), (65, 88, 127, 144), True), # box2 left box1 y:box1 in box2 Error
((182, 130, 230, 268), (121, 149, 174, 289), False), # box2 left box1 分离
# ((1, 10, 26, 45), (3, 4, 20, 39), False), # box1 bottom box2 x:box2 in box1 Error
])
def test_right_intersect(box1: tuple, box2: tuple, target_bool: bool) -> None:
assert target_bool == _right_intersect(box1, box2)
# x方向上:要么box1包含box2, 要么box2包含box1。不能部分包含
# y方向上:box1和box2有重叠
@pytest.mark.parametrize("box1, box2, target_bool", [
# (None, None, False), # Error
((35, 28, 108, 90), (47, 60, 83, 96), True), # box1 top box2, x:box2 in box1, y:有重叠
((35, 28, 98, 90), (27, 60, 103, 96), True), # box1 top box2, x:box1 in box2, y:有重叠
((57, 77, 130, 210), (59, 219, 119, 293), False), # box1 top box2, x: box2 in box1, y:无重叠
((47, 60, 83, 96), (35, 28, 108, 90), True), # box2 top box1, x:box1 in box2, y:有重叠
((27, 60, 103, 96), (35, 28, 98, 90), True), # box2 top box1, x:box2 in box1, y:有重叠
((59, 219, 119, 293), (57, 77, 130, 210), False), # box2 top box1, x: box1 in box2, y:无重叠
((35, 28, 55, 90), (57, 60, 83, 96), False), # box1 top box2, x:无重叠, y:有重叠
((47, 60, 63, 96), (65, 28, 108, 90), False), # box2 top box1, x:无重叠, y:有重叠
])
def test_is_vertical_full_overlap(box1: tuple, box2: tuple, target_bool: bool) -> None:
assert target_bool == _is_vertical_full_overlap(box1, box2)
# 检查box1下方和box2的上方有轻微的重叠,轻微程度收到y_tolerance的限制
@pytest.mark.parametrize("box1, box2, target_bool", [
(None, None, False),
((35, 28, 108, 90), (47, 89, 83, 116), True), # box1 top box2, y:有重叠
((35, 28, 108, 90), (47, 60, 83, 96), False), # box1 top box2, y:有重叠且过多
((57, 77, 130, 210), (59, 219, 119, 293), False), # box1 top box2, y:无重叠
((47, 60, 83, 96), (35, 28, 108, 90), False), # box2 top box1, y:有重叠且过多
((27, 89, 103, 116), (35, 28, 98, 90), False), # box2 top box1, y:有重叠
((59, 219, 119, 293), (57, 77, 130, 210), False), # box2 top box1, y:无重叠
])
def test_is_bottom_full_overlap(box1: tuple, box2: tuple, target_bool: bool) -> None:
assert target_bool == _is_bottom_full_overlap(box1, box2)
# 检查box1的左侧是否和box2有重叠
@pytest.mark.parametrize("box1, box2, target_bool", [
(None, None, False),
((88, 81, 222, 173), (60, 221, 123, 358), False), # 分离
# ((121, 149, 184, 289), (172, 130, 230, 268), False), # box1 left bottom box2 相交 Error
# ((172, 130, 230, 268), (121, 149, 184, 289), True), # box2 left bottom box1 相交 Error
((109, 68, 182, 146), (215, 188, 277, 253), False), # box1 top left box2 分离
((117, 53, 222, 176), (174, 142, 298, 276), False), # box1 left top box2 相交
# ((174, 142, 298, 276), (117, 53, 222, 176), True), # box2 left top box1 相交 Error
# ((65, 88, 127, 144), (92, 102, 131, 139), False), # box1 left box2 y:box2 in box1 Error
((1, 10, 26, 45), (3, 4, 20, 39), True), # box1 middle bottom box2 x:box2 in box1
])
def test_is_left_overlap(box1: tuple, box2: tuple, target_bool: bool) -> None:
assert target_bool == _is_left_overlap(box1, box2)
# 查两个bbox在y轴上是否有重叠,并且该重叠区域的高度占两个bbox高度更低的那个超过阈值
@pytest.mark.parametrize("box1, box2, target_bool", [
# (None, None, "Error"), # Error
((51, 69, 192, 147), (75, 48, 132, 187), True), # y: box1 in box2
((51, 39, 192, 197), (75, 48, 132, 187), True), # y: box2 in box1
((88, 81, 222, 173), (60, 221, 123, 358), False), # y: box1 top box2
((109, 68, 182, 196), (215, 188, 277, 253), False), # y: box1 top box2 little
((109, 68, 182, 196), (215, 78, 277, 253), True), # y: box1 top box2 more
((109, 68, 182, 196), (215, 138, 277, 213), False), # y: box1 top box2 more but lower overlap_ratio_threshold
((109, 68, 182, 196), (215, 138, 277, 203), True), # y: box1 top box2 more and more overlap_ratio_threshold
])
def test_is_overlaps_y_exceeds_threshold(box1: tuple, box2: tuple, target_bool: bool) -> None:
assert target_bool == __is_overlaps_y_exceeds_threshold(box1, box2)
# Determine the coordinates of the intersection rectangle
@pytest.mark.parametrize("box1, box2, target_num", [
# (None, None, "Error"), # Error
((88, 81, 222, 173), (60, 221, 123, 358), 0.0), # 分离
((76, 140, 154, 277), (121, 326, 192, 384), 0.0), # 分离
((142, 109, 238, 164), (134, 211, 224, 270), 0.0), # 分离
((109, 68, 182, 196), (175, 138, 277, 213), 0.024475524475524476), # 相交
((56, 90, 170, 219), (103, 212, 171, 304), 0.02288586346557361), # 相交
((109, 126, 204, 245), (130, 127, 232, 186), 0.33696071621517326), # 相交
((109, 126, 204, 245), (110, 127, 232, 206), 0.5493822593770807), # 相交
((76, 140, 154, 277), (121, 277, 192, 384), 0.0) # 相切
])
def test_calculate_iou(box1: tuple, box2: tuple, target_num: float) -> None:
assert target_num == calculate_iou(box1, box2)
# 计算box1和box2的重叠面积占最小面积的box的比例
@pytest.mark.parametrize("box1, box2, target_num", [
# (None, None, "Error"), # Error
((142, 109, 238, 164), (134, 211, 224, 270), 0.0), # 分离
((88, 81, 222, 173), (60, 221, 123, 358), 0.0), # 分离
((76, 140, 154, 277), (121, 326, 192, 384), 0.0), # 分离
((76, 140, 154, 277), (121, 277, 192, 384), 0.0), # 相切
((109, 126, 204, 245), (110, 127, 232, 206), 0.7704918032786885), # 相交
((56, 90, 170, 219), (103, 212, 171, 304), 0.07496803069053709), # 相交
((121, 149, 184, 289), (172, 130, 230, 268), 0.17841079460269865), # 相交
((51, 69, 192, 147), (75, 48, 132, 187), 0.5611510791366906), # 相交
((117, 53, 222, 176), (174, 142, 298, 276), 0.12636469221835075), # 相交
((102, 60, 233, 203), (70, 190, 220, 319), 0.08188757807078417), # 相交
((109, 126, 204, 245), (130, 127, 232, 186), 0.7254901960784313), # 相交
])
def test_calculate_overlap_area_2_minbox_area_ratio(box1: tuple, box2: tuple, target_num: float) -> None:
assert target_num == calculate_overlap_area_2_minbox_area_ratio(box1, box2)
# 计算box1和box2的重叠面积占bbox1的比例
@pytest.mark.parametrize("box1, box2, target_num", [
# (None, None, "Error"), # Error
((142, 109, 238, 164), (134, 211, 224, 270), 0.0), # 分离
((88, 81, 222, 173), (60, 221, 123, 358), 0.0), # 分离
((76, 140, 154, 277), (121, 326, 192, 384), 0.0), # 分离
((76, 140, 154, 277), (121, 277, 192, 384), 0.0), # 相切
((142, 109, 238, 164), (134, 164, 224, 270), 0.0), # 相切
((109, 126, 204, 245), (110, 127, 232, 206), 0.6568774878372402), # 相交
((56, 90, 170, 219), (103, 212, 171, 304), 0.03189174486604107), # 相交
((121, 149, 184, 289), (172, 130, 230, 268), 0.1619047619047619), # 相交
((51, 69, 192, 147), (75, 48, 132, 187), 0.40425531914893614), # 相交
((117, 53, 222, 176), (174, 142, 298, 276), 0.12636469221835075), # 相交
((102, 60, 233, 203), (70, 190, 220, 319), 0.08188757807078417), # 相交
((109, 126, 204, 245), (130, 127, 232, 186), 0.38620079610791685), # 相交
])
def test_calculate_overlap_area_in_bbox1_area_ratio(box1: tuple, box2: tuple, target_num: float) -> None:
assert target_num == calculate_overlap_area_in_bbox1_area_ratio(box1, box2)
# 计算两个bbox重叠的面积占最小面积的box的比例,如果比例大于ratio,则返回小的那个bbox,否则返回None
@pytest.mark.parametrize("box1, box2, ratio, target_box", [
# (None, None, 0.8, "Error"), # Error
((142, 109, 238, 164), (134, 211, 224, 270), 0.0, None), # 分离
((109, 126, 204, 245), (110, 127, 232, 206), 0.5, (110, 127, 232, 206)),
((56, 90, 170, 219), (103, 212, 171, 304), 0.5, None),
((121, 149, 184, 289), (172, 130, 230, 268), 0.5, None),
((51, 69, 192, 147), (75, 48, 132, 187), 0.5, (75, 48, 132, 187)),
((117, 53, 222, 176), (174, 142, 298, 276), 0.5, None),
((102, 60, 233, 203), (70, 190, 220, 319), 0.5, None),
((109, 126, 204, 245), (130, 127, 232, 186), 0.5, (130, 127, 232, 186)),
])
def test_get_minbox_if_overlap_by_ratio(box1: tuple, box2: tuple, ratio: float, target_box: list) -> None:
assert target_box == get_minbox_if_overlap_by_ratio(box1, box2, ratio)
# 根据boundry获取在这个范围内的所有的box的列表,完全包含关系
@pytest.mark.parametrize("boxes, boundry, target_boxs", [
# ([], (), "Error"), # Error
([], (110, 340, 209, 387), []),
([(142, 109, 238, 164)], (134, 211, 224, 270), []), # 分离
([(109, 126, 204, 245), (110, 127, 232, 206)], (105, 116, 258, 300), [(109, 126, 204, 245), (110, 127, 232, 206)]),
([(109, 126, 204, 245), (110, 127, 232, 206)], (105, 116, 258, 230), [(110, 127, 232, 206)]),
([(81, 280, 123, 315), (282, 203, 342, 247), (183, 100, 300, 155), (46, 99, 133, 148), (33, 156, 97, 211),
(137, 29, 287, 87)], (80, 90, 249, 200), []),
([(81, 280, 123, 315), (282, 203, 342, 247), (183, 100, 300, 155), (46, 99, 133, 148), (33, 156, 97, 211),
(137, 29, 287, 87)], (30, 20, 349, 320),
[(81, 280, 123, 315), (282, 203, 342, 247), (183, 100, 300, 155), (46, 99, 133, 148), (33, 156, 97, 211),
(137, 29, 287, 87)]),
([(81, 280, 123, 315), (282, 203, 342, 247), (183, 100, 300, 155), (46, 99, 133, 148), (33, 156, 97, 211),
(137, 29, 287, 87)], (30, 20, 200, 320),
[(81, 280, 123, 315), (46, 99, 133, 148), (33, 156, 97, 211)]),
])
def test_get_bbox_in_boundry(boxes: list, boundry: tuple, target_boxs: list) -> None:
assert target_boxs == get_bbox_in_boundry(boxes, boundry)
# 寻找上方距离最近的box,margin 4个单位, x方向有重合,y方向最近的
@pytest.mark.parametrize("pymu_blocks, obj_box, target_boxs", [
([{"bbox": (81, 280, 123, 315)}, {"bbox": (282, 203, 342, 247)}, {"bbox": (183, 100, 300, 155)},
{"bbox": (46, 99, 133, 148)}, {"bbox": (33, 156, 97, 211)},
{"bbox": (137, 29, 287, 87)}], (81, 280, 123, 315), {"bbox": (33, 156, 97, 211)}),
# ([{"bbox": (168, 120, 263, 159)},
# {"bbox": (231, 61, 279, 159)},
# {"bbox": (35, 85, 136, 110)},
# {"bbox": (228, 193, 347, 225)},
# {"bbox": (144, 264, 188, 323)},
# {"bbox": (62, 37, 126, 64)}], (228, 193, 347, 225),
# [{"bbox": (168, 120, 263, 159)}, {"bbox": (231, 61, 279, 159)}]), # y:方向最近的有两个,x: 两个均有重合 Error
([{"bbox": (35, 85, 136, 159)},
{"bbox": (168, 120, 263, 159)},
{"bbox": (231, 61, 279, 118)},
{"bbox": (228, 193, 347, 225)},
{"bbox": (144, 264, 188, 323)},
{"bbox": (62, 37, 126, 64)}], (228, 193, 347, 225),
{"bbox": (168, 120, 263, 159)},), # y:方向最近的有两个,x:只有一个有重合
([{"bbox": (239, 115, 379, 167)},
{"bbox": (33, 237, 104, 262)},
{"bbox": (124, 288, 168, 325)},
{"bbox": (242, 291, 379, 340)},
{"bbox": (55, 117, 121, 154)},
{"bbox": (266, 183, 384, 217)}, ], (124, 288, 168, 325), {'bbox': (55, 117, 121, 154)}),
([{"bbox": (239, 115, 379, 167)},
{"bbox": (33, 237, 104, 262)},
{"bbox": (124, 288, 168, 325)},
{"bbox": (242, 291, 379, 340)},
{"bbox": (55, 117, 119, 154)},
{"bbox": (266, 183, 384, 217)}, ], (124, 288, 168, 325), None), # x没有重合
([{"bbox": (80, 90, 249, 200)},
{"bbox": (183, 100, 240, 155)}, ], (183, 100, 240, 155), None), # 包含
])
def test_find_top_nearest_text_bbox(pymu_blocks: list, obj_box: tuple, target_boxs: dict) -> None:
assert target_boxs == find_top_nearest_text_bbox(pymu_blocks, obj_box)
# 寻找下方距离自己最近的box, x方向有重合,y方向最近的
@pytest.mark.parametrize("pymu_blocks, obj_box, target_boxs", [
([{"bbox": (165, 96, 300, 114)},
{"bbox": (11, 157, 139, 201)},
{"bbox": (124, 208, 265, 262)},
{"bbox": (124, 283, 248, 306)},
{"bbox": (39, 267, 84, 301)},
{"bbox": (36, 89, 114, 145)}, ], (165, 96, 300, 114), {"bbox": (124, 208, 265, 262)}),
([{"bbox": (187, 37, 303, 49)},
{"bbox": (2, 227, 90, 283)},
{"bbox": (158, 174, 200, 212)},
{"bbox": (259, 174, 324, 228)},
{"bbox": (205, 61, 316, 97)},
{"bbox": (295, 248, 374, 287)}, ], (205, 61, 316, 97), {"bbox": (259, 174, 324, 228)}), # y有两个最近的, x只有一个重合
# ([{"bbox": (187, 37, 303, 49)},
# {"bbox": (2, 227, 90, 283)},
# {"bbox": (259, 174, 324, 228)},
# {"bbox": (205, 61, 316, 97)},
# {"bbox": (295, 248, 374, 287)},
# {"bbox": (158, 174, 209, 212)}, ], (205, 61, 316, 97),
# [{"bbox": (259, 174, 324, 228)}, {"bbox": (158, 174, 209, 212)}]), # x有重合,y有两个最近的 Error
([{"bbox": (287, 132, 398, 191)},
{"bbox": (44, 141, 163, 188)},
{"bbox": (132, 191, 240, 241)},
{"bbox": (81, 25, 142, 67)},
{"bbox": (74, 297, 116, 314)},
{"bbox": (77, 84, 224, 107)}, ], (287, 132, 398, 191), None), # x没有重合
([{"bbox": (80, 90, 249, 200)},
{"bbox": (183, 100, 240, 155)}, ], (183, 100, 240, 155), None), # 包含
])
def test_find_bottom_nearest_text_bbox(pymu_blocks: list, obj_box: tuple, target_boxs: dict) -> None:
assert target_boxs == find_bottom_nearest_text_bbox(pymu_blocks, obj_box)
# 寻找左侧距离自己最近的box, y方向有重叠,x方向最近
@pytest.mark.parametrize("pymu_blocks, obj_box, target_boxs", [
([{"bbox": (80, 90, 249, 200)}, {"bbox": (183, 100, 240, 155)}], (183, 100, 240, 155), None), # 包含
([{"bbox": (28, 90, 77, 126)}, {"bbox": (35, 84, 84, 120)}], (35, 84, 84, 120), None), # y:重叠,x:重叠大于2
([{"bbox": (28, 90, 77, 126)}, {"bbox": (75, 84, 134, 120)}], (75, 84, 134, 120), {"bbox": (28, 90, 77, 126)}),
# y:重叠,x:重叠小于等于2
([{"bbox": (239, 115, 379, 167)},
{"bbox": (33, 237, 104, 262)},
{"bbox": (124, 288, 168, 325)},
{"bbox": (242, 291, 379, 340)},
{"bbox": (55, 113, 161, 154)},
{"bbox": (266, 123, 384, 217)}], (266, 123, 384, 217), {"bbox": (55, 113, 161, 154)}), # y重叠,x left
# ([{"bbox": (136, 219, 268, 240)},
# {"bbox": (169, 115, 268, 181)},
# {"bbox": (33, 237, 104, 262)},
# {"bbox": (124, 288, 168, 325)},
# {"bbox": (55, 117, 161, 154)},
# {"bbox": (266, 183, 384, 217)}], (266, 183, 384, 217),
# [{"bbox": (136, 219, 267, 240)}, {"bbox": (169, 115, 267, 181)}]), # y有重叠,x重叠小于2或者在left Error
])
def test_find_left_nearest_text_bbox(pymu_blocks: list, obj_box: tuple, target_boxs: dict) -> None:
assert target_boxs == find_left_nearest_text_bbox(pymu_blocks, obj_box)
# 寻找右侧距离自己最近的box, y方向有重叠,x方向最近
@pytest.mark.parametrize("pymu_blocks, obj_box, target_boxs", [
([{"bbox": (80, 90, 249, 200)}, {"bbox": (183, 100, 240, 155)}], (183, 100, 240, 155), None), # 包含
([{"bbox": (28, 90, 77, 126)}, {"bbox": (35, 84, 84, 120)}], (28, 90, 77, 126), None), # y:重叠,x:重叠大于2
([{"bbox": (28, 90, 77, 126)}, {"bbox": (75, 84, 134, 120)}], (28, 90, 77, 126), {"bbox": (75, 84, 134, 120)}),
# y:重叠,x:重叠小于等于2
([{"bbox": (239, 115, 379, 167)},
{"bbox": (33, 237, 104, 262)},
{"bbox": (124, 288, 168, 325)},
{"bbox": (242, 291, 379, 340)},
{"bbox": (55, 113, 161, 154)},
{"bbox": (266, 123, 384, 217)}], (55, 113, 161, 154), {"bbox": (239, 115, 379, 167)}), # y重叠,x right
# ([{"bbox": (169, 115, 298, 181)},
# {"bbox": (169, 219, 268, 240)},
# {"bbox": (33, 177, 104, 262)},
# {"bbox": (124, 288, 168, 325)},
# {"bbox": (55, 117, 161, 154)},
# {"bbox": (266, 183, 384, 217)}], (33, 177, 104, 262),
# [{"bbox": (169, 115, 298, 181)}, {"bbox": (169, 219, 268, 240)}]), # y有重叠,x重叠小于2或者在right Error
])
def test_find_right_nearest_text_bbox(pymu_blocks: list, obj_box: tuple, target_boxs: dict) -> None:
assert target_boxs == find_right_nearest_text_bbox(pymu_blocks, obj_box)
# 判断两个矩形框的相对位置关系 (left, right, bottom, top)
@pytest.mark.parametrize("box1, box2, target_box", [
# (None, None, "Error"), # Error
((80, 90, 249, 200), (183, 100, 240, 155), (False, False, False, False)), # 包含
# ((124, 81, 222, 173), (60, 221, 123, 358), (False, True, False, True)), # 分离,右上 Error
((142, 109, 238, 164), (134, 211, 224, 270), (False, False, False, True)), # 分离,上
# ((51, 69, 192, 147), (205, 198, 282, 297), (True, False, False, True)), # 分离,左上 Error
# ((101, 149, 164, 289), (172, 130, 230, 268), (True, False, False, False)), # 分离,左 Error
# ((69, 196, 124, 285), (130, 127, 232, 186), (True, False, True, False)), # 分离,左下 Error
((103, 212, 171, 304), (56, 90, 170, 209), (False, False, True, False)), # 分离,下
# ((124, 367, 222, 415), (60, 221, 123, 358), (False, True, True, False)), # 分离,右下 Error
# ((172, 130, 230, 268), (101, 149, 164, 289), (False, True, False, False)), # 分离,右 Error
])
def test_bbox_relative_pos(box1: tuple, box2: tuple, target_box: tuple) -> None:
assert target_box == bbox_relative_pos(box1, box2)
# 计算两个矩形框的距离
"""
受bbox_relative_pos方法的影响,左右相反,这里计算结果全部受影响,在错误的基础上计算出了正确的结果
"""
@pytest.mark.parametrize("box1, box2, target_num", [
# (None, None, "Error"), # Error
((80, 90, 249, 200), (183, 100, 240, 155), 0.0), # 包含
((142, 109, 238, 164), (134, 211, 224, 270), 47.0), # 分离,上
((103, 212, 171, 304), (56, 90, 170, 209), 3.0), # 分离,下
((101, 149, 164, 289), (172, 130, 230, 268), 8.0), # 分离,左
((172, 130, 230, 268), (101, 149, 164, 289), 8.0), # 分离,右
((80.3, 90.8, 249.0, 200.5), (183.8, 100.6, 240.2, 155.1), 0.0), # 包含
((142.3, 109.5, 238.9, 164.2), (134.4, 211.2, 224.8, 270.1), 47.0), # 分离,上
((103.5, 212.6, 171.1, 304.8), (56.1, 90.9, 170.6, 209.2), 3.4), # 分离,下
((101.1, 149.3, 164.9, 289.0), (172.1, 130.1, 230.5, 268.5), 7.2), # 分离,左
((172.1, 130.3, 230.1, 268.1), (101.2, 149.9, 164.3, 289.1), 7.8), # 分离,右
((124.3, 81.1, 222.5, 173.8), (60.3, 221.5, 123.0, 358.9), 47.717711596429254), # 分离,右上
((51.2, 69.31, 192.5, 147.9), (205.0, 198.1, 282.98, 297.09), 51.73287156151299), # 分离,左上
((124.3, 367.1, 222.9, 415.7), (60.9, 221.4, 123.2, 358.6), 8.570880934886448), # 分离,右下
((69.9, 196.2, 124.1, 285.7), (130.0, 127.3, 232.6, 186.1), 11.69700816448377), # 分离,左下
])
def test_bbox_distance(box1: tuple, box2: tuple, target_num: float) -> None:
assert target_num - bbox_distance(box1, box2) < 1
@pytest.mark.skip(reason="skip")
# 根据bucket_name获取s3配置ak,sk,endpoint
def test_get_s3_config() -> None:
bucket_name = os.getenv('bucket_name')
target_data = os.getenv('target_data')
assert convert_string_to_list(target_data) == list(get_s3_config(bucket_name))
def convert_string_to_list(s):
cleaned_s = s.strip("'")
items = cleaned_s.split(',')
cleaned_items = [item.strip() for item in items]
return cleaned_items