File size: 3,779 Bytes
d21cb06 | 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 | import os.path as osp
from unittest import TestCase
import numpy as np
from datumaro.components.extractor import Bbox, DatasetItem, Points
from datumaro.components.project import Dataset, Project
from datumaro.plugins.vgg_face2_format import (VggFace2Converter,
VggFace2Importer)
from datumaro.util.test_utils import TestDir, compare_datasets
class VggFace2FormatTest(TestCase):
def test_can_save_and_load(self):
source_dataset = Dataset.from_iterable([
DatasetItem(id='1', subset='train', image=np.ones((8, 8, 3)),
annotations=[
Bbox(0, 2, 4, 2),
Points([3.2, 3.12, 4.11, 3.2, 2.11,
2.5, 3.5, 2.11, 3.8, 2.13]),
]
),
DatasetItem(id='2', subset='train', image=np.ones((10, 10, 3)),
annotations=[
Points([4.23, 4.32, 5.34, 4.45, 3.54,
3.56, 4.52, 3.51, 4.78, 3.34]),
]
),
DatasetItem(id='3', subset='val', image=np.ones((8, 8, 3))),
DatasetItem(id='4', subset='val', image=np.ones((10, 10, 3)),
annotations=[
Bbox(0, 2, 4, 2),
Points([3.2, 3.12, 4.11, 3.2, 2.11,
2.5, 3.5, 2.11, 3.8, 2.13]),
Bbox(2, 2, 1, 2),
Points([2.787, 2.898, 2.965, 2.79, 2.8,
2.456, 2.81, 2.32, 2.89, 2.3]),
]
),
DatasetItem(id='5', subset='val', image=np.ones((8, 8, 3)),
annotations=[
Bbox(2, 2, 2, 2),
]
),
], categories=[])
with TestDir() as test_dir:
VggFace2Converter.convert(source_dataset, test_dir, save_images=True)
parsed_dataset = VggFace2Importer()(test_dir).make_dataset()
compare_datasets(self, source_dataset, parsed_dataset)
def test_can_save_dataset_with_no_subsets(self):
source_dataset = Dataset.from_iterable([
DatasetItem(id='a/b/1', image=np.ones((8, 8, 3)),
annotations=[
Bbox(0, 2, 4, 2),
Points([4.23, 4.32, 5.34, 4.45, 3.54,
3.56, 4.52, 3.51, 4.78, 3.34]),
]
),
], categories=[])
with TestDir() as test_dir:
VggFace2Converter.convert(source_dataset, test_dir, save_images=True)
parsed_dataset = VggFace2Importer()(test_dir).make_dataset()
compare_datasets(self, source_dataset, parsed_dataset)
DUMMY_DATASET_DIR = osp.join(osp.dirname(__file__), 'assets', 'vgg_face2_dataset')
class VggFace2ImporterTest(TestCase):
def test_can_detect(self):
self.assertTrue(VggFace2Importer.detect(DUMMY_DATASET_DIR))
def test_can_import(self):
expected_dataset = Dataset.from_iterable([
DatasetItem(id='n000001/0001_01', subset='train',
image=np.ones((10, 15, 3)),
annotations=[
Bbox(2, 2, 1, 2),
Points([2.787, 2.898, 2.965, 2.79, 2.8,
2.456, 2.81, 2.32, 2.89, 2.3]),
]
),
DatasetItem(id='n000002/0002_01', subset='train',
image=np.ones((10, 15, 3)),
annotations=[
Bbox(1, 3, 1, 1),
Points([1.2, 3.8, 1.8, 3.82, 1.51,
3.634, 1.43, 3.34, 1.65, 3.32])
]
),
], categories=[])
dataset = Project.import_from(DUMMY_DATASET_DIR, 'vgg_face2') \
.make_dataset()
compare_datasets(self, expected_dataset, dataset)
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