| from functools import partial |
| import numpy as np |
| import os.path as osp |
|
|
| from unittest import TestCase |
| from datumaro.components.project import Dataset |
| from datumaro.components.extractor import (DatasetItem, |
| AnnotationType, Bbox, Mask, Polygon, LabelCategories |
| ) |
| from datumaro.components.project import Project |
| from datumaro.plugins.labelme_format import LabelMeImporter, LabelMeConverter |
| from datumaro.util.test_utils import (TestDir, compare_datasets, |
| test_save_and_load) |
|
|
|
|
| class LabelMeConverterTest(TestCase): |
| def _test_save_and_load(self, source_dataset, converter, test_dir, |
| target_dataset=None, importer_args=None): |
| return test_save_and_load(self, source_dataset, converter, test_dir, |
| importer='label_me', |
| target_dataset=target_dataset, importer_args=importer_args) |
|
|
| def test_can_save_and_load(self): |
| source_dataset = Dataset.from_iterable([ |
| DatasetItem(id='dir1/1', subset='train', |
| image=np.ones((16, 16, 3)), |
| annotations=[ |
| Bbox(0, 4, 4, 8, label=2, group=2), |
| Polygon([0, 4, 4, 4, 5, 6], label=3, attributes={ |
| 'occluded': True, |
| 'a1': 'qwe', |
| 'a2': True, |
| 'a3': 123, |
| }), |
| Mask(np.array([[0, 1], [1, 0], [1, 1]]), group=2, |
| attributes={ 'username': 'test' }), |
| Bbox(1, 2, 3, 4, group=3), |
| Mask(np.array([[0, 0], [0, 0], [1, 1]]), group=3, |
| attributes={ 'occluded': True } |
| ), |
| ] |
| ), |
| ], categories={ |
| AnnotationType.label: LabelCategories.from_iterable( |
| 'label_' + str(label) for label in range(10)), |
| }) |
|
|
| target_dataset = Dataset.from_iterable([ |
| DatasetItem(id='dir1/1', subset='train', |
| image=np.ones((16, 16, 3)), |
| annotations=[ |
| Bbox(0, 4, 4, 8, label=0, group=2, id=0, |
| attributes={ |
| 'occluded': False, 'username': '', |
| } |
| ), |
| Polygon([0, 4, 4, 4, 5, 6], label=1, id=1, |
| attributes={ |
| 'occluded': True, 'username': '', |
| 'a1': 'qwe', |
| 'a2': True, |
| 'a3': 123, |
| } |
| ), |
| Mask(np.array([[0, 1], [1, 0], [1, 1]]), group=2, |
| id=2, attributes={ |
| 'occluded': False, 'username': 'test' |
| } |
| ), |
| Bbox(1, 2, 3, 4, group=1, id=3, attributes={ |
| 'occluded': False, 'username': '', |
| }), |
| Mask(np.array([[0, 0], [0, 0], [1, 1]]), group=1, |
| id=4, attributes={ |
| 'occluded': True, 'username': '' |
| } |
| ), |
| ] |
| ), |
| ], categories={ |
| AnnotationType.label: LabelCategories.from_iterable([ |
| 'label_2', 'label_3']), |
| }) |
|
|
| with TestDir() as test_dir: |
| self._test_save_and_load( |
| source_dataset, |
| partial(LabelMeConverter.convert, save_images=True), |
| test_dir, target_dataset=target_dataset) |
|
|
|
|
| DUMMY_DATASET_DIR = osp.join(osp.dirname(__file__), 'assets', 'labelme_dataset') |
|
|
| class LabelMeImporterTest(TestCase): |
| def test_can_detect(self): |
| self.assertTrue(LabelMeImporter.detect(DUMMY_DATASET_DIR)) |
|
|
| def test_can_import(self): |
| img1 = np.ones((77, 102, 3)) * 255 |
| img1[6:32, 7:41] = 0 |
|
|
| mask1 = np.zeros((77, 102), dtype=int) |
| mask1[67:69, 58:63] = 1 |
|
|
| mask2 = np.zeros((77, 102), dtype=int) |
| mask2[13:25, 54:71] = [ |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], |
| [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0], |
| [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0], |
| [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0], |
| [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0], |
| [0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 0, 0], |
| [0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0], |
| [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0], |
| [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0], |
| [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0], |
| [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0], |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], |
| ] |
|
|
| target_dataset = Dataset.from_iterable([ |
| DatasetItem(id='example_folder/img1', image=img1, |
| annotations=[ |
| Polygon([43, 34, 45, 34, 45, 37, 43, 37], |
| label=0, id=0, |
| attributes={ |
| 'occluded': False, |
| 'username': 'admin' |
| } |
| ), |
| Mask(mask1, label=1, id=1, |
| attributes={ |
| 'occluded': False, |
| 'username': 'brussell' |
| } |
| ), |
| Polygon([30, 12, 42, 21, 24, 26, 15, 22, 18, 14, 22, 12, 27, 12], |
| label=2, group=2, id=2, |
| attributes={ |
| 'a1': True, |
| 'occluded': True, |
| 'username': 'anonymous' |
| } |
| ), |
| Polygon([35, 21, 43, 22, 40, 28, 28, 31, 31, 22, 32, 25], |
| label=3, group=2, id=3, |
| attributes={ |
| 'kj': True, |
| 'occluded': False, |
| 'username': 'anonymous' |
| } |
| ), |
| Bbox(13, 19, 10, 11, label=4, group=2, id=4, |
| attributes={ |
| 'hg': True, |
| 'occluded': True, |
| 'username': 'anonymous' |
| } |
| ), |
| Mask(mask2, label=5, group=1, id=5, |
| attributes={ |
| 'd': True, |
| 'occluded': False, |
| 'username': 'anonymous' |
| } |
| ), |
| Polygon([64, 21, 74, 24, 72, 32, 62, 34, 60, 27, 62, 22], |
| label=6, group=1, id=6, |
| attributes={ |
| 'gfd lkj lkj hi': True, |
| 'occluded': False, |
| 'username': 'anonymous' |
| } |
| ), |
| ] |
| ), |
| ], categories={ |
| AnnotationType.label: LabelCategories.from_iterable([ |
| 'window', 'license plate', 'o1', |
| 'q1', 'b1', 'm1', 'hg', |
| ]), |
| }) |
|
|
| parsed = Project.import_from(DUMMY_DATASET_DIR, 'label_me') \ |
| .make_dataset() |
| compare_datasets(self, expected=target_dataset, actual=parsed) |
