[96354c]: / tests / dataset / loaders / test_brats_dataset.py

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import time
import pytest
from src.dataset.loaders.brats_dataset import BratsDataset
from src.dataset.patient import Patient
@pytest.fixture("function")
def dataset():
data = [Patient(idx="", center="", grade="", patient="BraTS20_Training_001", patch_name="BraTS20_Training_001",
size=[240, 240, 155] , data_path="/Users/lauramora/Documents/MASTER/TFM/Data/2020/train/no_patch/",
train=True)]*10
return data
def test_dataset_no_patch(dataset):
brats_dataset = BratsDataset(dataset, None, (240, 240, 155), compute_patch=False)
start = time.time()
modalities, segmentation = brats_dataset.__getitem__(0)
print("\n Time: ", time.time()-start)
assert modalities.shape == (4, 240, 240, 155)
assert segmentation.shape == (240, 240, 155)
def test_dataset_random_distribution(dataset):
from src.dataset.patching import random_distribution
brats_dataset = BratsDataset(dataset, random_distribution, (128, 128, 128), compute_patch=True)
start = time.time()
modalities, segmentation = brats_dataset.__getitem__(0)
print("\n Time: ", time.time()-start)
assert modalities.shape == (4, 128, 128, 128)
assert segmentation.shape == (128, 128, 128)
def test_dataset_random_tumor_distribution(dataset):
from src.dataset.patching import random_tumor_distribution
brats_dataset = BratsDataset(dataset, random_tumor_distribution, (128, 128, 128), compute_patch=True)
start = time.time()
modalities, segmentation = brats_dataset.__getitem__(0)
print("\n Time: ", time.time()-start)
assert modalities.shape == (4, 128, 128, 128)
assert segmentation.shape == (128, 128, 128)
def test_dataset_random_tumor_distribution_multiple_calls(dataset):
from src.dataset.patching import random_tumor_distribution
brats_dataset = BratsDataset(dataset, random_tumor_distribution, (128, 128, 128),
compute_patch=True)
start = time.time()
for idx in range(0, 5):
modalities, segmentation = brats_dataset.__getitem__(idx)
print("\n Time: ", time.time() - start)