def test_inplace_save_writes_only_updated_data(self):
src_mask_cat = MaskCategories.generate(3, include_background=False)
expected = Dataset.from_iterable(
[
DatasetItem(1,
subset='a',
image=np.ones((2, 1, 3)),
annotations=[Mask(np.ones((2, 1)), label=2)]),
DatasetItem(2, subset='a', image=np.ones((3, 2, 3))),
DatasetItem(2, subset='b'),
],
categories=Camvid.make_camvid_categories(
OrderedDict([
('background', (0, 0, 0)),
('a', src_mask_cat.colormap[0]),
('b', src_mask_cat.colormap[1]),
])))
with TestDir() as path:
dataset = Dataset.from_iterable(
[
DatasetItem(1,
subset='a',
image=np.ones((2, 1, 3)),
annotations=[Mask(np.ones((2, 1)), label=1)]),
DatasetItem(2, subset='b'),
DatasetItem(3,
subset='c',
image=np.ones((2, 2, 3)),
annotations=[Mask(np.ones((2, 2)), label=0)]),
],
categories={
AnnotationType.label:
LabelCategories.from_iterable(['a', 'b']),
AnnotationType.mask: src_mask_cat
})
dataset.export(path, 'camvid', save_images=True)
dataset.put(DatasetItem(2, subset='a', image=np.ones((3, 2, 3))))
dataset.remove(3, 'c')
dataset.save(save_images=True)
self.assertEqual(
{'a', 'aannot', 'a.txt', 'b.txt', 'label_colors.txt'},
set(os.listdir(path)))
self.assertEqual({'1.jpg', '2.jpg'},
set(os.listdir(osp.join(path, 'a'))))
compare_datasets(self,
expected,
Dataset.import_from(path, 'camvid'),
require_images=True)
def test_can_write_and_parse_meta_file(self):
src_label_map = Camvid.CamvidLabelMap
with TestDir() as test_dir:
source_dataset = Dataset.from_iterable(
[], categories=Camvid.make_camvid_categories(src_label_map))
CamvidConverter.convert(source_dataset,
test_dir,
save_dataset_meta=True)
dst_label_map = parse_meta_file(test_dir)
self.assertEqual(src_label_map, dst_label_map)
def categories(self):
label_map = OrderedDict()
label_map['background'] = None
label_map['a'] = None
label_map['b'] = None
return Camvid.make_camvid_categories(label_map)
def categories(self):
return Camvid.make_camvid_categories()
def categories(self):
label_map = OrderedDict()
label_map['background'] = (0, 0, 0)
label_map['label_1'] = (1, 2, 3)
label_map['label_2'] = (3, 2, 1)
return Camvid.make_camvid_categories(label_map)