def test_values(self):
datalist = [
{
"image": "spleen_19.nii.gz",
"label": "spleen_label_19.nii.gz"
},
{
"image": "spleen_31.nii.gz",
"label": "spleen_label_31.nii.gz"
},
]
transform = Compose([
DataStatsd(keys=["image", "label"],
data_shape=False,
value_range=False,
data_value=True),
SimulateDelayd(keys=["image", "label"], delay_time=0.1),
])
dataset = CacheDataset(data=datalist,
transform=transform,
cache_rate=0.5,
cache_num=1)
dataloader = DataLoader(dataset=dataset, batch_size=2, num_workers=2)
for d in dataloader:
self.assertEqual(d["image"][0], "spleen_19.nii.gz")
self.assertEqual(d["image"][1], "spleen_31.nii.gz")
self.assertEqual(d["label"][0], "spleen_label_19.nii.gz")
self.assertEqual(d["label"][1], "spleen_label_31.nii.gz")
def test_shape(self):
expected_shape = (128, 128, 128)
test_image = nib.Nifti1Image(
np.random.randint(0, 2, size=[128, 128, 128]), np.eye(4))
test_data = []
with tempfile.TemporaryDirectory() as tempdir:
for i in range(6):
nib.save(test_image,
os.path.join(tempdir, f"test_image{str(i)}.nii.gz"))
test_data.append(
{"image": os.path.join(tempdir, f"test_image{i}.nii.gz")})
test_transform = Compose([
LoadImaged(keys="image"),
SimulateDelayd(keys="image", delay_time=1e-7)
])
data_iterator = _Stream(test_data)
with self.assertRaises(TypeError): # Dataset doesn't work
dataset = Dataset(data=data_iterator, transform=test_transform)
for _ in dataset:
pass
dataset = IterableDataset(data=data_iterator,
transform=test_transform)
for d in dataset:
self.assertTupleEqual(d["image"].shape, expected_shape)
num_workers = 2 if sys.platform == "linux" else 0
dataloader = DataLoader(dataset=dataset,
batch_size=3,
num_workers=num_workers)
for d in dataloader:
self.assertTupleEqual(d["image"].shape[1:], expected_shape)
def test_shape(self):
expected_shape = (128, 128, 128)
test_image = nib.Nifti1Image(
np.random.randint(0, 2, size=[128, 128, 128]), np.eye(4))
test_data = list()
with tempfile.TemporaryDirectory() as tempdir:
for i in range(6):
nib.save(test_image,
os.path.join(tempdir, f"test_image{str(i)}.nii.gz"))
test_data.append({
"image":
os.path.join(tempdir, f"test_image{str(i)}.nii.gz")
})
test_transform = Compose([
LoadImaged(keys="image"),
SimulateDelayd(keys="image", delay_time=1e-7),
])
test_stream = _Stream(data=test_data,
dbpath=os.path.join(tempdir, "countDB"))
dataset = IterableDataset(data=test_stream,
transform=test_transform)
for d in dataset:
self.assertTupleEqual(d["image"].shape, expected_shape)
test_stream.reset()
dataloader = DataLoader(dataset=dataset,
batch_size=3,
num_workers=2)
for d in dataloader:
self.assertTupleEqual(d["image"].shape[1:], expected_shape)
def setUp(self):
super().setUp()
self.datalist = [
{"image": "spleen_19.nii.gz", "label": "spleen_label_19.nii.gz"},
{"image": "spleen_31.nii.gz", "label": "spleen_label_31.nii.gz"},
]
self.transform = Compose([SimulateDelayd(keys=["image", "label"], delay_time=0.1)])
def test_shape(self, expected_shape):
test_image = nib.Nifti1Image(
np.random.randint(0, 2, size=[128, 128, 128]), np.eye(4))
tempdir = tempfile.mkdtemp()
nib.save(test_image, os.path.join(tempdir, "test_image1.nii.gz"))
nib.save(test_image, os.path.join(tempdir, "test_label1.nii.gz"))
nib.save(test_image, os.path.join(tempdir, "test_extra1.nii.gz"))
nib.save(test_image, os.path.join(tempdir, "test_image2.nii.gz"))
nib.save(test_image, os.path.join(tempdir, "test_label2.nii.gz"))
nib.save(test_image, os.path.join(tempdir, "test_extra2.nii.gz"))
test_data = [
{
"image": os.path.join(tempdir, "test_image1.nii.gz"),
"label": os.path.join(tempdir, "test_label1.nii.gz"),
"extra": os.path.join(tempdir, "test_extra1.nii.gz"),
},
{
"image": os.path.join(tempdir, "test_image2.nii.gz"),
"label": os.path.join(tempdir, "test_label2.nii.gz"),
"extra": os.path.join(tempdir, "test_extra2.nii.gz"),
},
]
test_transform = Compose([
LoadNiftid(keys=["image", "label", "extra"]),
SimulateDelayd(keys=["image", "label", "extra"],
delay_time=[1e-7, 1e-6, 1e-5]),
])
dataset_precached = PersistentDataset(data=test_data,
transform=test_transform,
cache_dir=tempdir)
data1_precached = dataset_precached[0]
data2_precached = dataset_precached[1]
dataset_postcached = PersistentDataset(data=test_data,
transform=test_transform,
cache_dir=tempdir)
data1_postcached = dataset_postcached[0]
data2_postcached = dataset_postcached[1]
shutil.rmtree(tempdir)
self.assertTupleEqual(data1_precached["image"].shape, expected_shape)
self.assertTupleEqual(data1_precached["label"].shape, expected_shape)
self.assertTupleEqual(data1_precached["extra"].shape, expected_shape)
self.assertTupleEqual(data2_precached["image"].shape, expected_shape)
self.assertTupleEqual(data2_precached["label"].shape, expected_shape)
self.assertTupleEqual(data2_precached["extra"].shape, expected_shape)
self.assertTupleEqual(data1_postcached["image"].shape, expected_shape)
self.assertTupleEqual(data1_postcached["label"].shape, expected_shape)
self.assertTupleEqual(data1_postcached["extra"].shape, expected_shape)
self.assertTupleEqual(data2_postcached["image"].shape, expected_shape)
self.assertTupleEqual(data2_postcached["label"].shape, expected_shape)
self.assertTupleEqual(data2_postcached["extra"].shape, expected_shape)
def test_shape(self, expected_shape):
test_image = nib.Nifti1Image(
np.random.randint(0, 2, size=[128, 128, 128]), np.eye(4))
with tempfile.TemporaryDirectory() as tempdir:
nib.save(test_image, os.path.join(tempdir, "test_image1.nii.gz"))
nib.save(test_image, os.path.join(tempdir, "test_label1.nii.gz"))
nib.save(test_image, os.path.join(tempdir, "test_extra1.nii.gz"))
nib.save(test_image, os.path.join(tempdir, "test_image2.nii.gz"))
nib.save(test_image, os.path.join(tempdir, "test_label2.nii.gz"))
nib.save(test_image, os.path.join(tempdir, "test_extra2.nii.gz"))
test_data = [
{
"image": os.path.join(tempdir, "test_image1.nii.gz"),
"label": os.path.join(tempdir, "test_label1.nii.gz"),
"extra": os.path.join(tempdir, "test_extra1.nii.gz"),
},
{
"image": os.path.join(tempdir, "test_image2.nii.gz"),
"label": os.path.join(tempdir, "test_label2.nii.gz"),
"extra": os.path.join(tempdir, "test_extra2.nii.gz"),
},
]
test_transform = Compose([
LoadNiftid(keys=["image", "label", "extra"]),
SimulateDelayd(keys=["image", "label", "extra"],
delay_time=[1e-7, 1e-6, 1e-5]),
])
dataset = Dataset(data=test_data, transform=test_transform)
data1 = dataset[0]
data2 = dataset[1]
self.assertTupleEqual(data1["image"].shape, expected_shape)
self.assertTupleEqual(data1["label"].shape, expected_shape)
self.assertTupleEqual(data1["extra"].shape, expected_shape)
self.assertTupleEqual(data2["image"].shape, expected_shape)
self.assertTupleEqual(data2["label"].shape, expected_shape)
self.assertTupleEqual(data2["extra"].shape, expected_shape)
dataset = Dataset(
data=test_data,
transform=LoadNiftid(keys=["image", "label", "extra"]))
data1_simple = dataset[0]
data2_simple = dataset[1]
self.assertTupleEqual(data1_simple["image"].shape, expected_shape)
self.assertTupleEqual(data1_simple["label"].shape, expected_shape)
self.assertTupleEqual(data1_simple["extra"].shape, expected_shape)
self.assertTupleEqual(data2_simple["image"].shape, expected_shape)
self.assertTupleEqual(data2_simple["label"].shape, expected_shape)
self.assertTupleEqual(data2_simple["extra"].shape, expected_shape)
def test_shape(self, expected_shape):
test_image = nib.Nifti1Image(
np.random.randint(0, 2, size=[128, 128, 128]), np.eye(4))
tempdir = tempfile.mkdtemp()
nib.save(test_image, os.path.join(tempdir, 'test_image1.nii.gz'))
nib.save(test_image, os.path.join(tempdir, 'test_label1.nii.gz'))
nib.save(test_image, os.path.join(tempdir, 'test_extra1.nii.gz'))
nib.save(test_image, os.path.join(tempdir, 'test_image2.nii.gz'))
nib.save(test_image, os.path.join(tempdir, 'test_label2.nii.gz'))
nib.save(test_image, os.path.join(tempdir, 'test_extra2.nii.gz'))
test_data = [{
'image': os.path.join(tempdir, 'test_image1.nii.gz'),
'label': os.path.join(tempdir, 'test_label1.nii.gz'),
'extra': os.path.join(tempdir, 'test_extra1.nii.gz')
}, {
'image': os.path.join(tempdir, 'test_image2.nii.gz'),
'label': os.path.join(tempdir, 'test_label2.nii.gz'),
'extra': os.path.join(tempdir, 'test_extra2.nii.gz')
}]
test_transform = Compose([
LoadNiftid(keys=['image', 'label', 'extra']),
SimulateDelayd(keys=['image', 'label', 'extra'],
delay_time=[1e-7, 1e-6, 1e-5])
])
dataset = Dataset(data=test_data, transform=test_transform)
data1 = dataset[0]
data2 = dataset[1]
self.assertTupleEqual(data1['image'].shape, expected_shape)
self.assertTupleEqual(data1['label'].shape, expected_shape)
self.assertTupleEqual(data1['extra'].shape, expected_shape)
self.assertTupleEqual(data2['image'].shape, expected_shape)
self.assertTupleEqual(data2['label'].shape, expected_shape)
self.assertTupleEqual(data2['extra'].shape, expected_shape)
dataset = Dataset(
data=test_data,
transform=LoadNiftid(keys=['image', 'label', 'extra']))
data1_simple = dataset[0]
data2_simple = dataset[1]
self.assertTupleEqual(data1_simple['image'].shape, expected_shape)
self.assertTupleEqual(data1_simple['label'].shape, expected_shape)
self.assertTupleEqual(data1_simple['extra'].shape, expected_shape)
self.assertTupleEqual(data2_simple['image'].shape, expected_shape)
self.assertTupleEqual(data2_simple['label'].shape, expected_shape)
self.assertTupleEqual(data2_simple['extra'].shape, expected_shape)
import os
import tempfile
import unittest
import nibabel as nib
import numpy as np
from parameterized import parameterized
from monai.data import PersistentDataset, json_hashing
from monai.transforms import Compose, LoadImaged, SimulateDelayd, Transform
TEST_CASE_1 = [
Compose([
LoadImaged(keys=["image", "label", "extra"]),
SimulateDelayd(keys=["image", "label", "extra"],
delay_time=[1e-7, 1e-6, 1e-5]),
]),
(128, 128, 128),
]
TEST_CASE_2 = [
[
LoadImaged(keys=["image", "label", "extra"]),
SimulateDelayd(keys=["image", "label", "extra"],
delay_time=[1e-7, 1e-6, 1e-5]),
],
(128, 128, 128),
]
TEST_CASE_3 = [None, (128, 128, 128)]
