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Merged
bhashemian merged 6 commits into from
Mar 27, 2021
Merged

Update SmartCachePatchWSIDataset and add unittests #1853

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c3998a4
Add unittests for SmartCachePatchWSIDataset
bhashemian Mar 26, 2021
87dce90
Turn off shuffle for SmartCachePatchWSIDataset
bhashemian Mar 26, 2021
2c2ba18
Merge branch 'master' into smartcache_wsi_dataset_unittests
bhashemian Mar 26, 2021
c9a2fb4
Merge branch 'master' into smartcache_wsi_dataset_unittests
bhashemian Mar 26, 2021
34085cd
Merge branch 'master' into smartcache_wsi_dataset_unittests
bhashemian Mar 26, 2021
7ef9a35
Merge branch 'master' into smartcache_wsi_dataset_unittests
bhashemian Mar 27, 2021
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1 change: 1 addition & 0 deletions monai/apps/pathology/datasets.py
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Original file line number Diff line number Diff line change
Expand Up @@ -158,4 +158,5 @@ def __init__(
num_init_workers=num_init_workers,
num_replace_workers=num_replace_workers,
progress=progress,
shuffle=False,
)
168 changes: 168 additions & 0 deletions tests/test_smartcache_patch_wsi_dataset.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,168 @@
import os
import unittest
from unittest import skipUnless
from urllib import request

import numpy as np
from numpy.testing import assert_array_equal
from parameterized import parameterized

from monai.apps.pathology.datasets import SmartCachePatchWSIDataset
from monai.utils import optional_import

_, has_cim = optional_import("cucim")

FILE_URL = "http://openslide.cs.cmu.edu/download/openslide-testdata/Generic-TIFF/CMU-1.tiff"

TEST_CASE_0 = [
FILE_URL,
{
"data": [
{"image": "./CMU-1.tiff", "location": [0, 0], "label": [0]},
{"image": "./CMU-1.tiff", "location": [0, 0], "label": [1]},
{"image": "./CMU-1.tiff", "location": [0, 0], "label": [2]},
{"image": "./CMU-1.tiff", "location": [0, 0], "label": [3]},
],
"region_size": (1, 1),
"grid_shape": (1, 1),
"patch_size": 1,
"transform": lambda x: x,
"image_reader_name": "cuCIM",
"replace_rate": 0.5,
"cache_num": 2,
"num_init_workers": 1,
"num_replace_workers": 1,
},
[
{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[0]]])},
{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[1]]])},
{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[1]]])},
{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[2]]])},
{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[2]]])},
{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[3]]])},
{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[3]]])},
{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[0]]])},
],
]

TEST_CASE_1 = [
FILE_URL,
{
"data": [
{"image": "./CMU-1.tiff", "location": [0, 0], "label": [[0, 0]]},
{"image": "./CMU-1.tiff", "location": [0, 0], "label": [[1, 1]]},
{"image": "./CMU-1.tiff", "location": [0, 0], "label": [[2, 2]]},
],
"region_size": (1, 1),
"grid_shape": (1, 1),
"patch_size": 1,
"transform": lambda x: x,
"image_reader_name": "cuCIM",
"replace_rate": 0.5,
"cache_num": 2,
"num_init_workers": 1,
"num_replace_workers": 1,
},
[
{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[0, 0]]])},
{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[1, 1]]])},
{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[1, 1]]])},
{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[2, 2]]])},
{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[2, 2]]])},
{"image": np.array([[[239]], [[239]], [[239]]], dtype=np.uint8), "label": np.array([[[0, 0]]])},
],
]

TEST_CASE_2 = [
FILE_URL,
{
"data": [
{"image": "./CMU-1.tiff", "location": [10004, 20004], "label": [0, 0, 0, 0]},
{"image": "./CMU-1.tiff", "location": [10004, 20004], "label": [1, 1, 1, 1]},
{"image": "./CMU-1.tiff", "location": [10004, 20004], "label": [2, 2, 2, 2]},
],
"region_size": (8, 8),
"grid_shape": (2, 2),
"patch_size": 1,
"transform": lambda x: x,
"image_reader_name": "cuCIM",
"replace_rate": 0.5,
"cache_num": 2,
"num_init_workers": 1,
"num_replace_workers": 1,
},
[
{"image": np.array([[[247]], [[245]], [[248]]], dtype=np.uint8), "label": np.array([[[0]]])},
{"image": np.array([[[245]], [[247]], [[244]]], dtype=np.uint8), "label": np.array([[[0]]])},
{"image": np.array([[[246]], [[246]], [[246]]], dtype=np.uint8), "label": np.array([[[0]]])},
{"image": np.array([[[246]], [[246]], [[246]]], dtype=np.uint8), "label": np.array([[[0]]])},
{"image": np.array([[[247]], [[245]], [[248]]], dtype=np.uint8), "label": np.array([[[1]]])},
{"image": np.array([[[245]], [[247]], [[244]]], dtype=np.uint8), "label": np.array([[[1]]])},
{"image": np.array([[[246]], [[246]], [[246]]], dtype=np.uint8), "label": np.array([[[1]]])},
{"image": np.array([[[246]], [[246]], [[246]]], dtype=np.uint8), "label": np.array([[[1]]])},
{"image": np.array([[[247]], [[245]], [[248]]], dtype=np.uint8), "label": np.array([[[1]]])},
{"image": np.array([[[245]], [[247]], [[244]]], dtype=np.uint8), "label": np.array([[[1]]])},
{"image": np.array([[[246]], [[246]], [[246]]], dtype=np.uint8), "label": np.array([[[1]]])},
{"image": np.array([[[246]], [[246]], [[246]]], dtype=np.uint8), "label": np.array([[[1]]])},
{"image": np.array([[[247]], [[245]], [[248]]], dtype=np.uint8), "label": np.array([[[2]]])},
{"image": np.array([[[245]], [[247]], [[244]]], dtype=np.uint8), "label": np.array([[[2]]])},
{"image": np.array([[[246]], [[246]], [[246]]], dtype=np.uint8), "label": np.array([[[2]]])},
{"image": np.array([[[246]], [[246]], [[246]]], dtype=np.uint8), "label": np.array([[[2]]])},
{"image": np.array([[[247]], [[245]], [[248]]], dtype=np.uint8), "label": np.array([[[2]]])},
{"image": np.array([[[245]], [[247]], [[244]]], dtype=np.uint8), "label": np.array([[[2]]])},
{"image": np.array([[[246]], [[246]], [[246]]], dtype=np.uint8), "label": np.array([[[2]]])},
{"image": np.array([[[246]], [[246]], [[246]]], dtype=np.uint8), "label": np.array([[[2]]])},
{"image": np.array([[[247]], [[245]], [[248]]], dtype=np.uint8), "label": np.array([[[0]]])},
{"image": np.array([[[245]], [[247]], [[244]]], dtype=np.uint8), "label": np.array([[[0]]])},
{"image": np.array([[[246]], [[246]], [[246]]], dtype=np.uint8), "label": np.array([[[0]]])},
{"image": np.array([[[246]], [[246]], [[246]]], dtype=np.uint8), "label": np.array([[[0]]])},
],
]


class TestSmartCachePatchWSIDataset(unittest.TestCase):
@parameterized.expand(
[
TEST_CASE_0,
TEST_CASE_1,
TEST_CASE_2,
]
)
@skipUnless(has_cim, "Requires CuCIM")
def test_read_patches(self, file_url, input_parameters, expected):
self.camelyon_data_download(file_url)
dataset = SmartCachePatchWSIDataset(**input_parameters)
self.assertEqual(len(dataset), input_parameters["cache_num"])
total_num_samples = len(input_parameters["data"])
num_epochs = int(
np.ceil(total_num_samples / (input_parameters["cache_num"] * input_parameters["replace_rate"]))
)

dataset.start()
i = 0
for _ in range(num_epochs):
for j in range(len(dataset)):
samples = dataset[j]
n_patches = len(samples)
self.assert_samples_expected(samples, expected[i : i + n_patches])
i += n_patches
dataset.update_cache()
dataset.shutdown()

def camelyon_data_download(self, file_url):
filename = os.path.basename(file_url)
if not os.path.exists(filename):
print(f"Test image [{filename}] does not exist. Downloading...")
request.urlretrieve(file_url, filename)
return filename

def assert_samples_expected(self, samples, expected):
for i in range(len(samples)):
self.assertTupleEqual(samples[i]["label"].shape, expected[i]["label"].shape)
self.assertTupleEqual(samples[i]["image"].shape, expected[i]["image"].shape)
self.assertIsNone(assert_array_equal(samples[i]["label"], expected[i]["label"]))
self.assertIsNone(assert_array_equal(samples[i]["image"], expected[i]["image"]))


if __name__ == "__main__":
unittest.main()