def test_unsupervised(self):
"""Test the BetterLoader Unsupervised call using the default parameters"""
index_json = "./examples/sample_index_unsupervised.json"
basepath = "./examples/sample_dataset/"
batch_size = 2
metadata = collate_metadata()
better_loader = UnsupervisedBetterLoader(
basepath=basepath,
base_experiment_details=["simclr", 1, (150, 150)],
index_json_path=index_json,
dataset_metadata=metadata,
)
dataloaders, sizes = better_loader.fetch_segmented_dataloaders(
batch_size=batch_size)
assert dataloaders is not None
assert sizes["train"] == 4
assert sizes["test"] == 2
assert sizes["val"] == 2
def test_complex_metadata(self):
index_json = "./examples/sample_index.json"
basepath = "./examples/sample_dataset/"
batch_size = 2
dataset_metadata = collate_metadata()
loader = BetterLoader(
basepath=basepath,
index_json_path=index_json,
dataset_metadata=dataset_metadata,
)
dataloaders, sizes = loader.fetch_segmented_dataloaders(
batch_size=batch_size, transform=None)
assert dataloaders is not None
assert sizes["train"] == 4
assert sizes["test"] == 2
assert sizes["val"] == 2
from betterloader import UnsupervisedBetterLoader
from betterloader.defaults import collate_metadata
from PIL import Image
index_json = "./sample_index_unsupervised.json"
basepath = "./sample_dataset/"
batch_size = 2
metadata = collate_metadata()
better_loader = UnsupervisedBetterLoader(
basepath=basepath,
base_experiment_details=["simclr", 1, (150, 150)],
index_json_path=index_json,
dataset_metadata=metadata,
)
dataloaders, sizes = better_loader.fetch_segmented_dataloaders(
batch_size=batch_size)
for i, ((xp1, xp2), _) in enumerate(dataloaders["train"]):
print(i)
print(xp1.shape)