def test_remap_labels_ignore_missing_labels_in_secondary_categories(self):
source_dataset = Dataset.from_iterable([
DatasetItem(id=1, annotations=[
Label(0),
])
], categories={
AnnotationType.label: LabelCategories.from_iterable(['a', 'b', 'c']),
AnnotationType.points: PointsCategories.from_iterable([]), # all missing
AnnotationType.mask: MaskCategories.generate(2) # no c color
})
target_dataset = Dataset.from_iterable([
DatasetItem(id=1, annotations=[
Label(0),
]),
], categories={
AnnotationType.label: LabelCategories.from_iterable(['d', 'e', 'f']),
AnnotationType.points: PointsCategories.from_iterable([]),
AnnotationType.mask: MaskCategories.generate(2)
})
actual = transforms.RemapLabels(source_dataset,
mapping={ 'a': 'd', 'b': 'e', 'c': 'f' }, default='delete')
compare_datasets(self, target_dataset, actual)
def test_remap_labels(self):
src_dataset = Dataset.from_iterable(
[
DatasetItem(
id=1,
annotations=[
# Should be remapped
Label(1),
Bbox(1, 2, 3, 4, label=2),
Mask(image=np.array([1]), label=3),
# Should be kept
Polygon([1, 1, 2, 2, 3, 4], label=4),
PolyLine([1, 3, 4, 2, 5, 6])
])
],
categories={
AnnotationType.label:
LabelCategories.from_iterable('label%s' % i for i in range(5)),
AnnotationType.mask:
MaskCategories(colormap=mask_tools.generate_colormap(5)),
})
dst_dataset = Dataset.from_iterable(
[
DatasetItem(id=1,
annotations=[
Label(1),
Bbox(1, 2, 3, 4, label=0),
Mask(image=np.array([1]), label=1),
Polygon([1, 1, 2, 2, 3, 4], label=2),
PolyLine([1, 3, 4, 2, 5, 6], label=None)
]),
],
categories={
AnnotationType.label:
LabelCategories.from_iterable(['label0', 'label9', 'label4']),
AnnotationType.mask:
MaskCategories(
colormap={
k: v
for k, v in mask_tools.generate_colormap(5).items()
if k in {0, 1, 3, 4}
})
})
actual = transforms.RemapLabels(src_dataset,
mapping={
'label1': 'label9',
'label2': 'label0',
'label3': 'label9',
},
default='keep')
compare_datasets(self, dst_dataset, actual)
def test_remap_labels(self):
src_dataset = Dataset.from_iterable([
DatasetItem(id=1, annotations=[
# Should be remapped
Label(1),
Bbox(1, 2, 3, 4, label=2),
Mask(image=np.array([1]), label=3),
# Should be deleted
Polygon([1, 1, 2, 2, 3, 4], label=4),
# Should be kept
PolyLine([1, 3, 4, 2, 5, 6]),
Bbox(4, 3, 2, 1, label=5),
])
], categories={
AnnotationType.label: LabelCategories.from_iterable(
f'label{i}' for i in range(6)),
AnnotationType.mask: MaskCategories(
colormap=mask_tools.generate_colormap(6)),
AnnotationType.points: PointsCategories.from_iterable(
[(i, [str(i)]) for i in range(6)])
})
dst_dataset = Dataset.from_iterable([
DatasetItem(id=1, annotations=[
Label(1),
Bbox(1, 2, 3, 4, label=0),
Mask(image=np.array([1]), label=1),
PolyLine([1, 3, 4, 2, 5, 6], label=None),
Bbox(4, 3, 2, 1, label=2),
]),
], categories={
AnnotationType.label: LabelCategories.from_iterable(
['label0', 'label9', 'label5']),
AnnotationType.mask: MaskCategories(colormap={
i: v for i, v in enumerate({
k: v for k, v in mask_tools.generate_colormap(6).items()
if k in { 0, 1, 5 }
}.values())
}),
AnnotationType.points: PointsCategories.from_iterable(
[(0, ['0']), (1, ['1']), (2, ['5'])])
})
actual = transforms.RemapLabels(src_dataset, mapping={
'label1': 'label9', # rename & join with new label9 (from label3)
'label2': 'label0', # rename & join with existing label0
'label3': 'label9', # rename & join with new label9 (from label1)
'label4': '', # delete the label and associated annotations
# 'label5' - unchanged
}, default='keep')
compare_datasets(self, dst_dataset, actual)
def test_remap_labels_delete_unspecified(self):
source_dataset = Dataset.from_iterable(
[DatasetItem(id=1, annotations=[Label(0)])], categories=['label0'])
target_dataset = Dataset.from_iterable([
DatasetItem(id=1),
],
categories=[])
actual = transforms.RemapLabels(source_dataset,
mapping={},
default='delete')
compare_datasets(self, target_dataset, actual)
def test_remap_labels_delete_unspecified(self):
source_dataset = Dataset.from_iterable([
DatasetItem(id=1, annotations=[
Label(0, id=0), # will be removed
Label(1, id=1),
Bbox(1, 2, 3, 4, label=None),
])
], categories=['label0', 'label1'])
target_dataset = Dataset.from_iterable([
DatasetItem(id=1, annotations=[
Label(0, id=1),
]),
], categories=['label1'])
actual = transforms.RemapLabels(source_dataset,
mapping={ 'label1': 'label1' }, default='delete')
compare_datasets(self, target_dataset, actual)
def test_remap_labels_delete_unspecified(self):
class SrcExtractor(Extractor):
def __iter__(self):
return iter([DatasetItem(id=1, annotations=[Label(0)])])
def categories(self):
label_cat = LabelCategories()
label_cat.add('label0')
return {AnnotationType.label: label_cat}
class DstExtractor(Extractor):
def __iter__(self):
return iter([DatasetItem(id=1, annotations=[])])
def categories(self):
return {AnnotationType.label: LabelCategories()}
actual = transforms.RemapLabels(SrcExtractor(),
mapping={},
default='delete')
compare_datasets(self, DstExtractor(), actual)
def test_remap_labels(self):
class SrcExtractor(Extractor):
def __iter__(self):
return iter([
DatasetItem(
id=1,
annotations=[
# Should be remapped
Label(1),
Bbox(1, 2, 3, 4, label=2),
Mask(image=np.array([1]), label=3),
# Should be kept
Polygon([1, 1, 2, 2, 3, 4], label=4),
PolyLine([1, 3, 4, 2, 5, 6], label=None)
]),
])
def categories(self):
label_cat = LabelCategories()
label_cat.add('label0')
label_cat.add('label1')
label_cat.add('label2')
label_cat.add('label3')
label_cat.add('label4')
mask_cat = MaskCategories(
colormap=mask_tools.generate_colormap(5))
return {
AnnotationType.label: label_cat,
AnnotationType.mask: mask_cat,
}
class DstExtractor(Extractor):
def __iter__(self):
return iter([
DatasetItem(id=1,
annotations=[
Label(1),
Bbox(1, 2, 3, 4, label=0),
Mask(image=np.array([1]), label=1),
Polygon([1, 1, 2, 2, 3, 4], label=2),
PolyLine([1, 3, 4, 2, 5, 6], label=None)
]),
])
def categories(self):
label_cat = LabelCategories()
label_cat.add('label0')
label_cat.add('label9')
label_cat.add('label4')
mask_cat = MaskCategories(
colormap={
k: v
for k, v in mask_tools.generate_colormap(5).items()
if k in {0, 1, 3, 4}
})
return {
AnnotationType.label: label_cat,
AnnotationType.mask: mask_cat,
}
actual = transforms.RemapLabels(SrcExtractor(),
mapping={
'label1': 'label9',
'label2': 'label0',
'label3': 'label9',
},
default='keep')
compare_datasets(self, DstExtractor(), actual)
