File size: 35,219 Bytes
09a3fa9 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import os.path as osp
from unittest.mock import MagicMock
import pytest
import torch
from mmengine.dataset import (BaseDataset, ClassBalancedDataset, Compose,
ConcatDataset, RepeatDataset, force_full_init)
from mmengine.registry import DATASETS, TRANSFORMS
def function_pipeline(data_info):
return data_info
@TRANSFORMS.register_module()
class CallableTransform:
def __call__(self, data_info):
return data_info
@TRANSFORMS.register_module()
class NotCallableTransform:
pass
@DATASETS.register_module()
class CustomDataset(BaseDataset):
pass
class TestBaseDataset:
def setup(self):
self.data_info = dict(
filename='test_img.jpg', height=604, width=640, sample_idx=0)
self.imgs = torch.rand((2, 3, 32, 32))
self.ori_meta = BaseDataset.METAINFO
self.ori_parse_data_info = BaseDataset.parse_data_info
BaseDataset.parse_data_info = MagicMock(return_value=self.data_info)
self.pipeline = MagicMock(return_value=dict(imgs=self.imgs))
def teardown(self):
BaseDataset.METAINFO = self.ori_meta
BaseDataset.parse_data_info = self.ori_parse_data_info
def test_init(self):
# test the instantiation of self.base_dataset
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json')
assert dataset._fully_initialized
assert hasattr(dataset, 'data_list')
assert hasattr(dataset, 'data_address')
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path=''),
ann_file='annotations/dummy_annotation.json')
assert dataset._fully_initialized
assert hasattr(dataset, 'data_list')
assert hasattr(dataset, 'data_address')
# test the instantiation of self.base_dataset with
# `serialize_data=False`
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json',
serialize_data=False)
assert dataset._fully_initialized
assert hasattr(dataset, 'data_list')
assert not hasattr(dataset, 'data_address')
assert len(dataset) == 3
assert dataset.get_data_info(0) == self.data_info
# test the instantiation of self.base_dataset with lazy init
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json',
lazy_init=True)
assert not dataset._fully_initialized
assert not dataset.data_list
# test the instantiation of self.base_dataset if ann_file is not
# existed.
with pytest.raises(FileNotFoundError):
BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/not_existed_annotation.json')
# Use the default value of ann_file, i.e., ''
with pytest.raises(TypeError):
BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'))
# test the instantiation of self.base_dataset when the ann_file is
# wrong
with pytest.raises(ValueError):
BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/annotation_wrong_keys.json')
with pytest.raises(TypeError):
BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/annotation_wrong_format.json')
with pytest.raises(TypeError):
BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path=['img']),
ann_file='annotations/annotation_wrong_format.json')
# test the instantiation of self.base_dataset when `parse_data_info`
# return `list[dict]`
BaseDataset.parse_data_info = MagicMock(
return_value=[self.data_info,
self.data_info.copy()])
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json')
dataset.pipeline = self.pipeline
assert dataset._fully_initialized
assert hasattr(dataset, 'data_list')
assert hasattr(dataset, 'data_address')
assert len(dataset) == 6
assert dataset[0] == dict(imgs=self.imgs)
assert dataset.get_data_info(0) == self.data_info
# test the instantiation of self.base_dataset when `parse_data_info`
# return unsupported data.
with pytest.raises(TypeError):
BaseDataset.parse_data_info = MagicMock(return_value='xxx')
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json')
with pytest.raises(TypeError):
BaseDataset.parse_data_info = MagicMock(
return_value=[self.data_info, 'xxx'])
BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json')
# test the instantiation of self.base_dataset without `ann_file`
BaseDataset.parse_data_info = self.ori_parse_data_info
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='',
serialize_data=False,
lazy_init=True)
assert not dataset.ann_file
def test_meta(self):
# test dataset.metainfo with setting the metainfo from annotation file
# as the metainfo of self.base_dataset.
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json')
assert dataset.metainfo == dict(
dataset_type='test_dataset', task_name='test_task', empty_list=[])
# test dataset.metainfo with setting METAINFO in self.base_dataset
dataset_type = 'new_dataset'
BaseDataset.METAINFO = dict(
dataset_type=dataset_type, classes=('dog', 'cat'))
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json')
assert dataset.metainfo == dict(
dataset_type=dataset_type,
task_name='test_task',
classes=('dog', 'cat'),
empty_list=[])
# test dataset.metainfo with passing metainfo into self.base_dataset
metainfo = dict(classes=('dog', ), task_name='new_task')
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json',
metainfo=metainfo)
assert BaseDataset.METAINFO == dict(
dataset_type=dataset_type, classes=('dog', 'cat'))
assert dataset.metainfo == dict(
dataset_type=dataset_type,
task_name='new_task',
classes=('dog', ),
empty_list=[])
# reset `base_dataset.METAINFO`, the `dataset.metainfo` should not
# change
BaseDataset.METAINFO['classes'] = ('dog', 'cat', 'fish')
assert BaseDataset.METAINFO == dict(
dataset_type=dataset_type, classes=('dog', 'cat', 'fish'))
assert dataset.metainfo == dict(
dataset_type=dataset_type,
task_name='new_task',
classes=('dog', ),
empty_list=[])
# test dataset.metainfo with passing metainfo containing a file into
# self.base_dataset
metainfo = dict(
classes=osp.join(
osp.dirname(__file__), '../data/meta/classes.txt'))
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json',
metainfo=metainfo)
assert dataset.metainfo == dict(
dataset_type=dataset_type,
task_name='test_task',
classes=['dog'],
empty_list=[])
# test dataset.metainfo with passing unsupported metainfo into
# self.base_dataset
with pytest.raises(TypeError):
metainfo = 'dog'
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json',
metainfo=metainfo)
# test dataset.metainfo with passing metainfo into self.base_dataset
# and lazy_init is True
metainfo = dict(classes=('dog', ))
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json',
metainfo=metainfo,
lazy_init=True)
# 'task_name' and 'empty_list' not in dataset.metainfo
assert dataset.metainfo == dict(
dataset_type=dataset_type, classes=('dog', ))
# test whether self.base_dataset.METAINFO is changed when a customize
# dataset inherit self.base_dataset
# test reset METAINFO in ToyDataset.
class ToyDataset(BaseDataset):
METAINFO = dict(xxx='xxx')
assert ToyDataset.METAINFO == dict(xxx='xxx')
assert BaseDataset.METAINFO == dict(
dataset_type=dataset_type, classes=('dog', 'cat', 'fish'))
# test update METAINFO in ToyDataset.
class ToyDataset(BaseDataset):
METAINFO = copy.deepcopy(BaseDataset.METAINFO)
METAINFO['classes'] = ('bird', )
assert ToyDataset.METAINFO == dict(
dataset_type=dataset_type, classes=('bird', ))
assert BaseDataset.METAINFO == dict(
dataset_type=dataset_type, classes=('dog', 'cat', 'fish'))
@pytest.mark.parametrize('lazy_init', [True, False])
def test_length(self, lazy_init):
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json',
lazy_init=lazy_init)
if not lazy_init:
assert dataset._fully_initialized
assert hasattr(dataset, 'data_list')
assert len(dataset) == 3
else:
# test `__len__()` when lazy_init is True
assert not dataset._fully_initialized
assert not dataset.data_list
# call `full_init()` automatically
assert len(dataset) == 3
assert dataset._fully_initialized
assert hasattr(dataset, 'data_list')
def test_compose(self):
# test callable transform
transforms = [function_pipeline]
compose = Compose(transforms=transforms)
assert (self.imgs == compose(dict(img=self.imgs))['img']).all()
# test transform build from cfg_dict
transforms = [dict(type='CallableTransform')]
compose = Compose(transforms=transforms)
assert (self.imgs == compose(dict(img=self.imgs))['img']).all()
# test return None in advance
none_func = MagicMock(return_value=None)
transforms = [none_func, function_pipeline]
compose = Compose(transforms=transforms)
assert compose(dict(img=self.imgs)) is None
# test repr
repr_str = f'Compose(\n' \
f' {none_func}\n' \
f' {function_pipeline}\n' \
f')'
assert repr(compose) == repr_str
# non-callable transform will raise error
with pytest.raises(TypeError):
transforms = [dict(type='NotCallableTransform')]
Compose(transforms)
# transform must be callable or dict
with pytest.raises(TypeError):
Compose([1])
# when the input transform is None, do nothing
compose = Compose(None)
assert (compose(dict(img=self.imgs))['img'] == self.imgs).all()
compose = Compose([])
assert (compose(dict(img=self.imgs))['img'] == self.imgs).all()
@pytest.mark.parametrize('lazy_init', [True, False])
def test_getitem(self, lazy_init):
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json',
lazy_init=lazy_init)
dataset.pipeline = self.pipeline
if not lazy_init:
assert dataset._fully_initialized
assert hasattr(dataset, 'data_list')
assert dataset[0] == dict(imgs=self.imgs)
else:
# Test `__getitem__()` when lazy_init is True
assert not dataset._fully_initialized
assert not dataset.data_list
# Call `full_init()` automatically
assert dataset[0] == dict(imgs=self.imgs)
assert dataset._fully_initialized
assert hasattr(dataset, 'data_list')
# Test with test mode
dataset.test_mode = False
assert dataset[0] == dict(imgs=self.imgs)
# Test cannot get a valid image.
dataset.prepare_data = MagicMock(return_value=None)
with pytest.raises(Exception):
dataset[0]
# Test get valid image by `_rand_another`
def fake_prepare_data(idx):
if idx == 0:
return None
else:
return 1
dataset.prepare_data = fake_prepare_data
dataset[0]
dataset.test_mode = True
with pytest.raises(Exception):
dataset[0]
@pytest.mark.parametrize('lazy_init', [True, False])
def test_get_data_info(self, lazy_init):
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json',
lazy_init=lazy_init)
if not lazy_init:
assert dataset._fully_initialized
assert hasattr(dataset, 'data_list')
assert dataset.get_data_info(0) == self.data_info
else:
# test `get_data_info()` when lazy_init is True
assert not dataset._fully_initialized
assert not dataset.data_list
# call `full_init()` automatically
assert dataset.get_data_info(0) == self.data_info
assert dataset._fully_initialized
assert hasattr(dataset, 'data_list')
# Test parse_data_info with `data_prefix`
BaseDataset.parse_data_info = self.ori_parse_data_info
data_root = osp.join(osp.dirname(__file__), '../data/')
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json')
data_info = dataset.get_data_info(0)
assert data_info['img_path'] == osp.join(data_root, 'imgs',
'test_img.jpg')
def test_force_full_init(self):
with pytest.raises(AttributeError):
class ClassWithoutFullInit:
@force_full_init
def foo(self):
pass
class_without_full_init = ClassWithoutFullInit()
class_without_full_init.foo()
def test_full_init(self):
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json',
lazy_init=True)
dataset.pipeline = self.pipeline
# test `full_init()` when lazy_init is True
assert not dataset._fully_initialized
assert not dataset.data_list
# call `full_init()` manually
dataset.full_init()
assert dataset._fully_initialized
assert hasattr(dataset, 'data_list')
assert len(dataset) == 3
assert dataset[0] == dict(imgs=self.imgs)
assert dataset.get_data_info(0) == self.data_info
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json',
lazy_init=False)
dataset.pipeline = self.pipeline
assert dataset._fully_initialized
assert hasattr(dataset, 'data_list')
assert len(dataset) == 3
assert dataset[0] == dict(imgs=self.imgs)
assert dataset.get_data_info(0) == self.data_info
# test the instantiation of self.base_dataset when passing indices
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path=''),
ann_file='annotations/dummy_annotation.json')
dataset_sliced = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path=''),
ann_file='annotations/dummy_annotation.json',
indices=1)
assert dataset_sliced[0] == dataset[0]
assert len(dataset_sliced) == 1
@pytest.mark.parametrize(
'lazy_init, serialize_data',
([True, False], [False, True], [True, True], [False, False]))
def test_get_subset_(self, lazy_init, serialize_data):
# Test positive int indices.
indices = 2
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path=''),
ann_file='annotations/dummy_annotation.json',
lazy_init=lazy_init,
serialize_data=serialize_data)
dataset_copy = copy.deepcopy(dataset)
dataset_copy.get_subset_(indices)
assert len(dataset_copy) == 2
for i in range(len(dataset_copy)):
ori_data = dataset[i]
assert dataset_copy[i] == ori_data
# Test negative int indices.
indices = -2
dataset_copy = copy.deepcopy(dataset)
dataset_copy.get_subset_(indices)
assert len(dataset_copy) == 2
for i in range(len(dataset_copy)):
ori_data = dataset[i + 1]
ori_data['sample_idx'] = i
assert dataset_copy[i] == ori_data
# If indices is 0, return empty dataset.
dataset_copy = copy.deepcopy(dataset)
dataset_copy.get_subset_(0)
assert len(dataset_copy) == 0
# Test list indices with positive element.
indices = [1]
dataset_copy = copy.deepcopy(dataset)
ori_data = dataset[1]
ori_data['sample_idx'] = 0
dataset_copy.get_subset_(indices)
assert len(dataset_copy) == 1
assert dataset_copy[0] == ori_data
# Test list indices with negative element.
indices = [-1]
dataset_copy = copy.deepcopy(dataset)
ori_data = dataset[2]
ori_data['sample_idx'] = 0
dataset_copy.get_subset_(indices)
assert len(dataset_copy) == 1
assert dataset_copy[0] == ori_data
# Test empty list.
indices = []
dataset_copy = copy.deepcopy(dataset)
dataset_copy.get_subset_(indices)
assert len(dataset_copy) == 0
# Test list with multiple positive indices.
indices = [0, 1, 2]
dataset_copy = copy.deepcopy(dataset)
dataset_copy.get_subset_(indices)
for i in range(len(dataset_copy)):
ori_data = dataset[i]
ori_data['sample_idx'] = i
assert dataset_copy[i] == ori_data
# Test list with multiple negative indices.
indices = [-1, -2, 0]
dataset_copy = copy.deepcopy(dataset)
dataset_copy.get_subset_(indices)
for i in range(len(dataset_copy)):
ori_data = dataset[len(dataset) - i - 1]
ori_data['sample_idx'] = i
assert dataset_copy[i] == ori_data
with pytest.raises(TypeError):
dataset.get_subset_(dict())
@pytest.mark.parametrize(
'lazy_init, serialize_data',
([True, False], [False, True], [True, True], [False, False]))
def test_get_subset(self, lazy_init, serialize_data):
# Test positive indices.
indices = 2
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path=''),
ann_file='annotations/dummy_annotation.json',
lazy_init=lazy_init,
serialize_data=serialize_data)
dataset_sliced = dataset.get_subset(indices)
assert len(dataset_sliced) == 2
assert dataset_sliced[0] == dataset[0]
for i in range(len(dataset_sliced)):
assert dataset_sliced[i] == dataset[i]
# Test negative indices.
indices = -2
dataset_sliced = dataset.get_subset(indices)
assert len(dataset_sliced) == 2
for i in range(len(dataset_sliced)):
ori_data = dataset[i + 1]
ori_data['sample_idx'] = i
assert dataset_sliced[i] == ori_data
# If indices is 0 or empty list, return empty dataset.
assert len(dataset.get_subset(0)) == 0
assert len(dataset.get_subset([])) == 0
# test list indices.
indices = [1]
dataset_sliced = dataset.get_subset(indices)
ori_data = dataset[1]
ori_data['sample_idx'] = 0
assert len(dataset_sliced) == 1
assert dataset_sliced[0] == ori_data
# Test list with multiple positive index.
indices = [0, 1, 2]
dataset_sliced = dataset.get_subset(indices)
for i in range(len(dataset_sliced)):
ori_data = dataset[i]
ori_data['sample_idx'] = i
assert dataset_sliced[i] == ori_data
# Test list with multiple negative index.
indices = [-1, -2, 0]
dataset_sliced = dataset.get_subset(indices)
for i in range(len(dataset_sliced)):
ori_data = dataset[len(dataset) - i - 1]
ori_data['sample_idx'] = i
assert dataset_sliced[i] == ori_data
def test_rand_another(self):
# test the instantiation of self.base_dataset when passing num_samples
dataset = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path=''),
ann_file='annotations/dummy_annotation.json',
indices=1)
assert dataset._rand_another() >= 0
assert dataset._rand_another() < len(dataset)
class TestConcatDataset:
def setup(self):
dataset = BaseDataset
# create dataset_a
data_info = dict(filename='test_img.jpg', height=604, width=640)
dataset.parse_data_info = MagicMock(return_value=data_info)
imgs = torch.rand((2, 3, 32, 32))
self.dataset_a = dataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json')
self.dataset_a.pipeline = MagicMock(return_value=dict(imgs=imgs))
# create dataset_b
data_info = dict(filename='gray.jpg', height=288, width=512)
dataset.parse_data_info = MagicMock(return_value=data_info)
imgs = torch.rand((2, 3, 32, 32))
self.dataset_b = dataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json')
self.dataset_b.pipeline = MagicMock(return_value=dict(imgs=imgs))
# test init
self.cat_datasets = ConcatDataset(
datasets=[self.dataset_a, self.dataset_b])
def test_init(self):
# Test build dataset from cfg.
dataset_cfg_b = dict(
type=CustomDataset,
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json')
cat_datasets = ConcatDataset(datasets=[self.dataset_a, dataset_cfg_b])
cat_datasets.datasets[1].pipeline = self.dataset_b.pipeline
assert len(cat_datasets) == len(self.cat_datasets)
for i in range(len(cat_datasets)):
assert (cat_datasets.get_data_info(i) ==
self.cat_datasets.get_data_info(i))
assert (cat_datasets[i] == self.cat_datasets[i])
with pytest.raises(TypeError):
ConcatDataset(datasets=[0])
with pytest.raises(TypeError):
ConcatDataset(
datasets=[self.dataset_a, dataset_cfg_b], ignore_keys=1)
def test_full_init(self):
# test init with lazy_init=True
self.cat_datasets.full_init()
assert len(self.cat_datasets) == 6
self.cat_datasets.full_init()
self.cat_datasets._fully_initialized = False
self.cat_datasets[1]
assert len(self.cat_datasets) == 6
with pytest.raises(NotImplementedError):
self.cat_datasets.get_subset_(1)
with pytest.raises(NotImplementedError):
self.cat_datasets.get_subset(1)
dataset_b = BaseDataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json',
metainfo=dict(classes=('cat')))
# Regardless of order, different meta information without
# `ignore_keys` will raise error.
with pytest.raises(ValueError):
ConcatDataset(datasets=[self.dataset_a, dataset_b])
with pytest.raises(ValueError):
ConcatDataset(datasets=[dataset_b, self.dataset_a])
# `ignore_keys` does not contain different meta information keys will
# raise error.
with pytest.raises(ValueError):
ConcatDataset(
datasets=[self.dataset_a, dataset_b], ignore_keys=['a'])
# Different meta information with `ignore_keys` will not raise error.
cat_datasets = ConcatDataset(
datasets=[self.dataset_a, dataset_b], ignore_keys='classes')
cat_datasets.full_init()
assert len(cat_datasets) == 6
cat_datasets.full_init()
cat_datasets._fully_initialized = False
cat_datasets[1]
assert len(cat_datasets.metainfo) == 3
assert len(cat_datasets) == 6
def test_metainfo(self):
assert self.cat_datasets.metainfo == self.dataset_a.metainfo
def test_length(self):
assert len(self.cat_datasets) == (
len(self.dataset_a) + len(self.dataset_b))
def test_getitem(self):
assert (
self.cat_datasets[0]['imgs'] == self.dataset_a[0]['imgs']).all()
assert (self.cat_datasets[0]['imgs'] !=
self.dataset_b[0]['imgs']).all()
assert (
self.cat_datasets[-1]['imgs'] == self.dataset_b[-1]['imgs']).all()
assert (self.cat_datasets[-1]['imgs'] !=
self.dataset_a[-1]['imgs']).all()
def test_get_data_info(self):
assert self.cat_datasets.get_data_info(
0) == self.dataset_a.get_data_info(0)
assert self.cat_datasets.get_data_info(
0) != self.dataset_b.get_data_info(0)
assert self.cat_datasets.get_data_info(
-1) == self.dataset_b.get_data_info(-1)
assert self.cat_datasets.get_data_info(
-1) != self.dataset_a.get_data_info(-1)
def test_get_ori_dataset_idx(self):
assert self.cat_datasets._get_ori_dataset_idx(3) == (
1, 3 - len(self.dataset_a))
assert self.cat_datasets._get_ori_dataset_idx(-1) == (
1, len(self.dataset_b) - 1)
with pytest.raises(ValueError):
assert self.cat_datasets._get_ori_dataset_idx(-10)
class TestRepeatDataset:
def setup(self):
dataset = BaseDataset
data_info = dict(filename='test_img.jpg', height=604, width=640)
dataset.parse_data_info = MagicMock(return_value=data_info)
imgs = torch.rand((2, 3, 32, 32))
self.dataset = dataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json')
self.dataset.pipeline = MagicMock(return_value=dict(imgs=imgs))
self.repeat_times = 5
# test init
self.repeat_datasets = RepeatDataset(
dataset=self.dataset, times=self.repeat_times)
def test_init(self):
# Test build dataset from cfg.
dataset_cfg = dict(
type=CustomDataset,
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json')
repeat_dataset = RepeatDataset(
dataset=dataset_cfg, times=self.repeat_times)
repeat_dataset.dataset.pipeline = self.dataset.pipeline
assert len(repeat_dataset) == len(self.repeat_datasets)
for i in range(len(repeat_dataset)):
assert (repeat_dataset.get_data_info(i) ==
self.repeat_datasets.get_data_info(i))
assert (repeat_dataset[i] == self.repeat_datasets[i])
with pytest.raises(TypeError):
RepeatDataset(dataset=[0], times=5)
def test_full_init(self):
self.repeat_datasets.full_init()
assert len(
self.repeat_datasets) == self.repeat_times * len(self.dataset)
self.repeat_datasets.full_init()
self.repeat_datasets._fully_initialized = False
self.repeat_datasets[1]
assert len(self.repeat_datasets) == \
self.repeat_times * len(self.dataset)
with pytest.raises(NotImplementedError):
self.repeat_datasets.get_subset_(1)
with pytest.raises(NotImplementedError):
self.repeat_datasets.get_subset(1)
def test_metainfo(self):
assert self.repeat_datasets.metainfo == self.dataset.metainfo
def test_length(self):
assert len(
self.repeat_datasets) == len(self.dataset) * self.repeat_times
def test_getitem(self):
for i in range(self.repeat_times):
assert self.repeat_datasets[len(self.dataset) *
i] == self.dataset[0]
def test_get_data_info(self):
for i in range(self.repeat_times):
assert self.repeat_datasets.get_data_info(
len(self.dataset) * i) == self.dataset.get_data_info(0)
class TestClassBalancedDataset:
def setup(self):
dataset = BaseDataset
data_info = dict(filename='test_img.jpg', height=604, width=640)
dataset.parse_data_info = MagicMock(return_value=data_info)
imgs = torch.rand((2, 3, 32, 32))
dataset.get_cat_ids = MagicMock(return_value=[0])
self.dataset = dataset(
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json')
self.dataset.pipeline = MagicMock(return_value=dict(imgs=imgs))
self.repeat_indices = [0, 0, 1, 1, 1]
# test init
self.cls_banlanced_datasets = ClassBalancedDataset(
dataset=self.dataset, oversample_thr=1e-3)
self.cls_banlanced_datasets.repeat_indices = self.repeat_indices
def test_init(self):
# Test build dataset from cfg.
dataset_cfg = dict(
type=CustomDataset,
data_root=osp.join(osp.dirname(__file__), '../data/'),
data_prefix=dict(img_path='imgs'),
ann_file='annotations/dummy_annotation.json')
cls_banlanced_datasets = ClassBalancedDataset(
dataset=dataset_cfg, oversample_thr=1e-3)
cls_banlanced_datasets.repeat_indices = self.repeat_indices
cls_banlanced_datasets.dataset.pipeline = self.dataset.pipeline
assert len(cls_banlanced_datasets) == len(self.cls_banlanced_datasets)
for i in range(len(cls_banlanced_datasets)):
assert (cls_banlanced_datasets.get_data_info(i) ==
self.cls_banlanced_datasets.get_data_info(i))
assert (
cls_banlanced_datasets[i] == self.cls_banlanced_datasets[i])
with pytest.raises(TypeError):
ClassBalancedDataset(dataset=[0], times=5)
def test_full_init(self):
self.cls_banlanced_datasets.full_init()
self.cls_banlanced_datasets.repeat_indices = self.repeat_indices
assert len(self.cls_banlanced_datasets) == len(self.repeat_indices)
# Reinit `repeat_indices`.
self.cls_banlanced_datasets._fully_initialized = False
self.cls_banlanced_datasets.repeat_indices = self.repeat_indices
assert len(self.cls_banlanced_datasets) != len(self.repeat_indices)
with pytest.raises(NotImplementedError):
self.cls_banlanced_datasets.get_subset_(1)
with pytest.raises(NotImplementedError):
self.cls_banlanced_datasets.get_subset(1)
def test_metainfo(self):
assert self.cls_banlanced_datasets.metainfo == self.dataset.metainfo
def test_length(self):
assert len(self.cls_banlanced_datasets) == len(self.repeat_indices)
def test_getitem(self):
for i in range(len(self.repeat_indices)):
assert self.cls_banlanced_datasets[i] == self.dataset[
self.repeat_indices[i]]
def test_get_data_info(self):
for i in range(len(self.repeat_indices)):
assert self.cls_banlanced_datasets.get_data_info(
i) == self.dataset.get_data_info(self.repeat_indices[i])
def test_get_cat_ids(self):
for i in range(len(self.repeat_indices)):
assert self.cls_banlanced_datasets.get_cat_ids(
i) == self.dataset.get_cat_ids(self.repeat_indices[i])
|