def test_invert_subselect_rows_by_indices__two_of_three_selected(self):
images = np.zeros((3, 3, 4, 1), dtype=np.uint8)
images[0, ...] = 0
images[1, ...] = 1
images[2, ...] = 2
batch = ia.BatchInAugmentation(
images=images,
keypoints=[
ia.KeypointsOnImage([ia.Keypoint(0, 0)], shape=(3, 4, 1)),
ia.KeypointsOnImage([ia.Keypoint(1, 1)], shape=(3, 4, 1)),
ia.KeypointsOnImage([ia.Keypoint(2, 2)], shape=(3, 4, 1))
])
batch_sub = batch.subselect_rows_by_indices([0, 2])
batch_sub.images[0, ...] = 10
batch_sub.images[1, ...] = 20
batch_sub.keypoints[0].keypoints[0].x = 10
batch_inv = batch.invert_subselect_rows_by_indices_([0, 2], batch_sub)
assert batch_inv.images.shape == (3, 3, 4, 1)
assert np.max(batch_inv.images[0]) == 10
assert np.max(batch_inv.images[1]) == 1
assert np.max(batch_inv.images[2]) == 20
assert batch_inv.keypoints[0].keypoints[0].x == 10
assert batch_inv.keypoints[0].keypoints[0].y == 0
assert batch_inv.keypoints[1].keypoints[0].x == 1
assert batch_inv.keypoints[1].keypoints[0].y == 1
assert batch_inv.keypoints[2].keypoints[0].x == 2
assert batch_inv.keypoints[2].keypoints[0].y == 2
def test_to_batch(self):
batch_before_aug = ia.Batch()
batch_before_aug.images_unaug = 0
batch_before_aug.heatmaps_unaug = 1
batch_before_aug.segmentation_maps_unaug = 2
batch_before_aug.keypoints_unaug = 3
batch_before_aug.bounding_boxes_unaug = 4
batch_before_aug.polygons_unaug = 5
batch_before_aug.line_strings_unaug = 6
batch_inaug = ia.BatchInAugmentation(images=10,
heatmaps=20,
segmentation_maps=30,
keypoints=40,
bounding_boxes=50,
polygons=60,
line_strings=70)
batch = batch_inaug.to_batch(batch_before_aug)
assert batch.images_unaug == 0
assert batch.heatmaps_unaug == 1
assert batch.segmentation_maps_unaug == 2
assert batch.keypoints_unaug == 3
assert batch.bounding_boxes_unaug == 4
assert batch.polygons_unaug == 5
assert batch.line_strings_unaug == 6
assert batch.images_aug == 10
assert batch.heatmaps_aug == 20
assert batch.segmentation_maps_aug == 30
assert batch.keypoints_aug == 40
assert batch.bounding_boxes_aug == 50
assert batch.polygons_aug == 60
assert batch.line_strings_aug == 70
def test_propagation_hooks_ctx(self):
def propagator(images, augmenter, parents, default):
if ia.is_np_array(images):
return False
else:
return True
hooks = ia.HooksImages(propagator=propagator)
batch = ia.BatchInAugmentation(
images=np.zeros((3, 3, 4, 1), dtype=np.uint8),
keypoints=[
ia.KeypointsOnImage([ia.Keypoint(0, 0)], shape=(3, 4, 1)),
ia.KeypointsOnImage([ia.Keypoint(1, 1)], shape=(3, 4, 1)),
ia.KeypointsOnImage([ia.Keypoint(2, 2)], shape=(3, 4, 1))
])
with batch.propagation_hooks_ctx(iaa.Identity(), hooks, []) \
as batch_prop:
assert batch_prop.images is None
assert batch_prop.keypoints is not None
assert len(batch_prop.keypoints) == 3
batch_prop.keypoints[0].keypoints[0].x = 10
assert batch.images is not None
assert batch.keypoints is not None
assert batch.keypoints[0].keypoints[0].x == 10
def test_deepcopy(self):
batch = ia.BatchInAugmentation(images=np.full((1, ), 0,
dtype=np.uint8),
heatmaps=np.full((1, ),
1,
dtype=np.uint8),
segmentation_maps=np.full(
(1, ), 2, dtype=np.uint8),
keypoints=np.full((1, ),
3,
dtype=np.uint8),
bounding_boxes=np.full((1, ),
4,
dtype=np.uint8),
polygons=np.full((1, ),
5,
dtype=np.uint8),
line_strings=np.full((1, ),
6,
dtype=np.uint8))
batch_copy = batch.deepcopy()
assert np.max(batch_copy.images) == 0
assert np.max(batch_copy.heatmaps) == 1
assert np.max(batch_copy.segmentation_maps) == 2
assert np.max(batch_copy.keypoints) == 3
assert np.max(batch_copy.bounding_boxes) == 4
assert np.max(batch_copy.polygons) == 5
assert np.max(batch_copy.line_strings) == 6
def test_fill_from_batch_in_augmentation(self):
batch = ia.BatchInAugmentation(images=1)
batch_inaug = ia.BatchInAugmentation(images=2,
heatmaps=3,
segmentation_maps=4,
keypoints=5,
bounding_boxes=6,
polygons=7,
line_strings=8)
batch = batch.fill_from_batch_in_augmentation_(batch_inaug)
assert batch.images == 2
assert batch.heatmaps == 3
assert batch.segmentation_maps == 4
assert batch.keypoints == 5
assert batch.bounding_boxes == 6
assert batch.polygons == 7
assert batch.line_strings == 8
def test_columns__with_two_columns(self):
batch = ia.BatchInAugmentation(images=[0, 0], keypoints=[1, 1])
columns = batch.columns
assert len(columns) == 2
assert columns[0].name == "images"
assert columns[1].name == "keypoints"
assert columns[0].value == [0, 0]
assert columns[1].value == [1, 1]
def test_subselect_rows_by_indices__none_selected(self):
batch = ia.BatchInAugmentation(
images=np.zeros((3, 3, 4, 1)),
keypoints=[
ia.KeypointsOnImage([ia.Keypoint(0, 0)], shape=(3, 4, 1)),
ia.KeypointsOnImage([ia.Keypoint(1, 1)], shape=(3, 4, 1)),
ia.KeypointsOnImage([ia.Keypoint(2, 2)], shape=(3, 4, 1))
])
batch_sub = batch.subselect_rows_by_indices([])
assert batch_sub.images is None
assert batch_sub.keypoints is None
def test_subselect_rows_by_indices__two_of_three_selected(self):
batch = ia.BatchInAugmentation(
images=np.zeros((3, 3, 4, 1)),
keypoints=[
ia.KeypointsOnImage([ia.Keypoint(0, 0)], shape=(3, 4, 1)),
ia.KeypointsOnImage([ia.Keypoint(1, 1)], shape=(3, 4, 1)),
ia.KeypointsOnImage([ia.Keypoint(2, 2)], shape=(3, 4, 1))
])
batch_sub = batch.subselect_rows_by_indices([0, 2])
assert batch_sub.images.shape == (2, 3, 4, 1)
assert batch_sub.keypoints[0].keypoints[0].x == 0
assert batch_sub.keypoints[0].keypoints[0].y == 0
assert batch_sub.keypoints[1].keypoints[0].x == 2
assert batch_sub.keypoints[1].keypoints[0].y == 2
def test_empty__with_columns_set(self):
kwargs = [{
"images": [2]
}, {
"heatmaps": [3]
}, {
"segmentation_maps": [4]
}, {
"keypoints": [5]
}, {
"bounding_boxes": [6]
}, {
"polygons": [7]
}, {
"line_strings": [8]
}]
for kwargs_i in kwargs:
batch = ia.BatchInAugmentation(**kwargs_i)
assert not batch.empty
def test_nb_rows__with_columns_set(self):
kwargs = [{
"images": [0]
}, {
"heatmaps": [0]
}, {
"segmentation_maps": [0]
}, {
"keypoints": [0]
}, {
"bounding_boxes": [0]
}, {
"polygons": [0]
}, {
"line_strings": [0]
}]
for kwargs_i in kwargs:
batch = ia.BatchInAugmentation(**kwargs_i)
assert batch.nb_rows == 1
def test_columns__with_columns_set(self):
kwargs = [{
"images": [0]
}, {
"heatmaps": [0]
}, {
"segmentation_maps": [0]
}, {
"keypoints": [0]
}, {
"bounding_boxes": [0]
}, {
"polygons": [0]
}, {
"line_strings": [0]
}]
for kwargs_i in kwargs:
batch = ia.BatchInAugmentation(**kwargs_i)
columns = batch.columns
assert len(columns) == 1
assert columns[0].name == list(kwargs_i.keys())[0]
def test_get_rowwise_shapes__nonimages(self):
heatmaps = [
ia.HeatmapsOnImage(np.zeros((1, 2, 1), dtype=np.float32),
shape=(1, 2, 3))
]
segmaps = [
ia.SegmentationMapsOnImage(np.zeros((1, 2, 1), dtype=np.int32),
shape=(1, 2, 3))
]
keypoints = [ia.KeypointsOnImage([ia.Keypoint(0, 0)], shape=(1, 2, 3))]
bounding_boxes = [
ia.BoundingBoxesOnImage([ia.BoundingBox(0, 1, 2, 3)],
shape=(1, 2, 3))
]
polygons = [
ia.PolygonsOnImage([ia.Polygon([(0, 0), (1, 0), (1, 1)])],
shape=(1, 2, 3))
]
line_strings = [
ia.LineStringsOnImage([ia.LineString([(0, 0), (1, 0)])],
shape=(1, 2, 3))
]
kwargs = [{
"heatmaps": heatmaps
}, {
"segmentation_maps": segmaps
}, {
"keypoints": keypoints
}, {
"bounding_boxes": bounding_boxes
}, {
"polygons": polygons
}, {
"line_strings": line_strings
}]
for kwargs_i in kwargs:
batch = ia.BatchInAugmentation(**kwargs_i)
shapes = batch.get_rowwise_shapes()
assert shapes == [(1, 2, 3)]
def test_get_column_names__with_two_columns(self):
batch = ia.BatchInAugmentation(images=[0, 0], keypoints=[1, 1])
assert batch.get_column_names() == ["images", "keypoints"]
def test_to_batch_in_augmentation(self):
batch = ia.BatchInAugmentation(images=1)
batch_inaug = batch.to_batch_in_augmentation()
assert batch_inaug is batch
def test_nb_rows__when_empty(self):
batch = ia.BatchInAugmentation()
assert batch.nb_rows == 0
def test_nb_rows__with_empty_column(self):
batch = ia.BatchInAugmentation(images=[])
assert batch.nb_rows == 0
def test_get_rowwise_shapes__images_is_multiple_arrays(self):
batch = ia.BatchInAugmentation(
images=[np.zeros((3, 4,
1)), np.zeros((4, 5, 1))])
shapes = batch.get_rowwise_shapes()
assert shapes == [(3, 4, 1), (4, 5, 1)]
def test_columns__with_empty_column(self):
batch = ia.BatchInAugmentation(images=[])
columns = batch.columns
assert len(columns) == 0
def test_columns__when_empty(self):
batch = ia.BatchInAugmentation()
assert len(batch.columns) == 0
def test_nb_rows__with_two_columns(self):
batch = ia.BatchInAugmentation(images=[0, 0], keypoints=[0, 0])
assert batch.nb_rows == 2
def test_get_rowwise_shapes__images_is_single_array(self):
batch = ia.BatchInAugmentation(images=np.zeros((2, 3, 4, 1)))
shapes = batch.get_rowwise_shapes()
assert shapes == [(3, 4, 1), (3, 4, 1)]
def test_empty__all_columns_none(self):
batch = ia.BatchInAugmentation()
assert batch.empty
