def test_detection_dataset_init_basic(
tiny_od_data_path,
od_data_path_labels,
tiny_od_mask_data_path,
tiny_od_keypoint_data_path,
):
""" Tests that initialization of the Detection Dataset works. """
data = DetectionDataset(tiny_od_data_path)
validate_detection_dataset(data, od_data_path_labels)
assert len(data.test_ds) == 19
assert len(data.train_ds) == 20
# test random seed
data = DetectionDataset(tiny_od_data_path, seed=9)
data2 = DetectionDataset(tiny_od_data_path, seed=9)
assert data.train_dl.dataset.indices == data2.train_dl.dataset.indices
assert data.test_dl.dataset.indices == data2.test_dl.dataset.indices
# test mask data
data = DetectionDataset(
tiny_od_mask_data_path, mask_dir="segmentation-masks"
)
validate_detection_dataset(data, od_data_path_labels)
assert len(data.test_ds) == 15
assert len(data.train_ds) == 16
# test keypoint data
data = DetectionDataset(
tiny_od_keypoint_data_path,
keypoint_meta={
"labels": [
"lid_left_top",
"lid_right_top",
"lid_left_bottom",
"lid_right_bottom",
"left_bottom",
"right_bottom",
],
"skeleton": [
[0, 1],
[0, 2],
[1, 3],
[2, 3],
[2, 4],
[3, 5],
[4, 5],
],
"hflip_inds": [1, 0, 3, 2, 5, 4],
},
)
validate_milkbottle_keypoint_tiny_dataset(data)
assert len(data.test_ds) == 15
assert len(data.train_ds) == 16
def test_detection_dataset_init_train_pct(
tiny_od_data_path,
od_data_path_labels,
tiny_od_mask_data_path,
tiny_od_keypoint_data_path,
):
""" Tests that initialization with train_pct."""
data = DetectionDataset(tiny_od_data_path, train_pct=0.75)
validate_detection_dataset(data, od_data_path_labels)
assert len(data.test_ds) == 9
assert len(data.train_ds) == 30
# test mask data
data = DetectionDataset(
tiny_od_mask_data_path, train_pct=0.75, mask_dir="segmentation-masks"
)
validate_detection_dataset(data, od_data_path_labels)
assert len(data.test_ds) == 7
assert len(data.train_ds) == 24
# test keypoint data
data = DetectionDataset(
tiny_od_keypoint_data_path,
train_pct=0.75,
keypoint_meta={
"labels": [
"lid_left_top",
"lid_right_top",
"lid_left_bottom",
"lid_right_bottom",
"left_bottom",
"right_bottom",
],
"skeleton": [
[0, 1],
[0, 2],
[1, 3],
[2, 3],
[2, 4],
[3, 5],
[4, 5],
],
"hflip_inds": [1, 0, 3, 2, 5, 4],
},
)
validate_milkbottle_keypoint_tiny_dataset(data)
assert len(data.test_ds) == 7
assert len(data.train_ds) == 24
def tiny_od_detection_keypoint_dataset(tiny_od_keypoint_data_path):
""" returns a basic detection keypoint dataset. """
return DetectionDataset(
tiny_od_keypoint_data_path,
keypoint_meta={
"labels": [
"lid_left_top",
"lid_right_top",
"lid_left_bottom",
"lid_right_bottom",
"left_bottom",
"right_bottom",
],
"skeleton": [
[0, 1],
[0, 2],
[1, 3],
[2, 3],
[2, 4],
[3, 5],
[4, 5],
],
"hflip_inds": [1, 0, 3, 2, 5, 4],
},
)
def test_detection_dataset_init_train_pct(tiny_od_data_path,
od_data_path_labels):
""" Tests that initialization with train_pct."""
data = DetectionDataset(tiny_od_data_path, train_pct=0.75)
validate_detection_dataset(data, od_data_path_labels)
assert len(data.test_ds) == 9
assert len(data.train_ds) == 30
def test_detection_dataset_init_train_pct(tiny_od_data_path,
od_data_path_labels,
tiny_od_mask_data_path):
""" Tests that initialization with train_pct."""
data = DetectionDataset(tiny_od_data_path, train_pct=0.75)
validate_detection_dataset(data, od_data_path_labels)
assert len(data.test_ds) == 9
assert len(data.train_ds) == 30
# test mask data
data = DetectionDataset(tiny_od_mask_data_path,
train_pct=0.75,
mask_dir="segmentation-masks")
validate_detection_dataset(data, od_data_path_labels)
assert len(data.test_ds) == 7
assert len(data.train_ds) == 24
def test_detection_dataset_init_basic(tiny_od_data_path, od_data_path_labels,
tiny_od_mask_data_path):
""" Tests that initialization of the Detection Dataset works. """
data = DetectionDataset(tiny_od_data_path)
validate_detection_dataset(data, od_data_path_labels)
assert len(data.test_ds) == 19
assert len(data.train_ds) == 20
# test random seed
data = DetectionDataset(tiny_od_data_path, seed=9)
data2 = DetectionDataset(tiny_od_data_path, seed=9)
assert data.train_dl.dataset.indices == data2.train_dl.dataset.indices
assert data.test_dl.dataset.indices == data2.test_dl.dataset.indices
# test mask data
data = DetectionDataset(tiny_od_mask_data_path,
mask_dir="segmentation-masks")
validate_detection_dataset(data, od_data_path_labels)
assert len(data.test_ds) == 15
assert len(data.train_ds) == 16
def test_detection_dataset_init_anno_im_dirs(func_tiny_od_data_path,
od_data_path_labels):
""" Tests that initialization with renamed anno/im dirs.
NOTE: this test doesn't use the normal tiny_od_data_path fixture since it
modifies the files in it. instead it uses the function level fixture.
"""
data_path = Path(func_tiny_od_data_path)
new_anno_dir_name = "bounding_boxes"
new_im_dir_name = "photos"
anno_dir = data_path / "annotations"
anno_dir.rename(data_path / new_anno_dir_name)
im_dir = data_path / "images"
im_dir.rename(data_path / new_im_dir_name)
data = DetectionDataset(str(data_path),
anno_dir=new_anno_dir_name,
im_dir=new_im_dir_name)
validate_detection_dataset(data, od_data_path_labels)
def od_detection_mask_dataset(tiny_od_mask_data_path):
""" returns a basic detection mask dataset. """
return DetectionDataset(tiny_od_mask_data_path,
mask_dir="segmentation-masks")
def od_detection_dataset(tiny_od_data_path):
""" returns a basic detection dataset. """
return DetectionDataset(tiny_od_data_path)
def basic_detection_dataset(tiny_od_data_path) -> DetectionDataset:
return DetectionDataset(tiny_od_data_path)
def test_detection_dataset_init_basic(tiny_od_data_path, od_data_path_labels):
""" Tests that initialization of the Detection Dataset works. """
data = DetectionDataset(tiny_od_data_path)
validate_detection_dataset(data, od_data_path_labels)
assert len(data.test_ds) == 19
assert len(data.train_ds) == 20