def testNewAndWriteCrop():
imagePath = datastore.fetch('sample_image.ptif')
source = large_image.open(imagePath)
out = large_image_source_vips.new()
assert out.crop is None
out.crop = 10, 10, 2000, 2000
assert out.crop is not None
out.crop = None
assert out.crop is None
with pytest.raises(TileSourceError):
out.crop = -1, -1, -1, -1
out.crop = 10, 10, 2000, 2000
for tile in source.tileIterator(
format=large_image.constants.TILE_FORMAT_NUMPY,
region=dict(right=4000, bottom=2000),
):
out.addTile(tile['tile'], x=tile['x'], y=tile['y'])
tmpdir = tempfile.mkdtemp()
outputPath = os.path.join(tmpdir, 'temp.tiff')
try:
out.write(outputPath)
result = large_image.open(outputPath)
resultMetadata = result.getMetadata()
assert resultMetadata['sizeX'] == 2000
assert resultMetadata['sizeY'] == 1990
finally:
shutil.rmtree(tmpdir)
def testNewAndWrite():
imagePath = datastore.fetch('sample_image.ptif')
source = large_image.open(imagePath)
out = large_image_source_vips.new()
for tile in source.tileIterator(
format=large_image.constants.TILE_FORMAT_NUMPY,
region=dict(right=4000, bottom=2000),
):
out.addTile(tile['tile'], x=tile['x'], y=tile['y'])
assert out.bandFormat == pyvips.enums.BandFormat.UCHAR
assert out.bandRanges['min'][0] > 10
assert out.mm_x is None
assert out.mm_y is None
out.mm_x = source.getNativeMagnification()['mm_x']
out.mm_y = source.getNativeMagnification()['mm_y']
assert out.mm_x == 0.00025
assert out.mm_y == 0.00025
tmpdir = tempfile.mkdtemp()
outputPath = os.path.join(tmpdir, 'temp.tiff')
try:
out.write(outputPath)
assert os.path.getsize(outputPath) > 50000
result = large_image.open(outputPath)
resultMetadata = result.getMetadata()
assert resultMetadata['sizeX'] == 4000
finally:
shutil.rmtree(tmpdir)
def testTileOverlap():
testDir = os.path.dirname(os.path.realpath(__file__))
imagePath = os.path.join(testDir, 'test_files', 'test_orient1.tif')
ts = large_image.open(imagePath)
assert [(tiles['x'], tiles['x'] + tiles['width'], tiles['width'],
tiles['tile_overlap']['left'], tiles['tile_overlap']['right'])
for tiles in ts.tileIterator(tile_size=dict(width=75, height=180),
tile_overlap=dict(x=60))] == [
(0, 75, 75, 0, 30),
(15, 90, 75, 30, 30),
(30, 105, 75, 30, 30),
(45, 120, 75, 30, 0),
]
assert [(tiles['x'], tiles['x'] + tiles['width'], tiles['width'],
tiles['tile_overlap']['left'], tiles['tile_overlap']['right'])
for tiles in ts.tileIterator(tile_size=dict(width=75, height=180),
tile_overlap=dict(x=60, edges=True))
] == [
(0, 45, 45, 0, 30),
(0, 60, 60, 15, 30),
(0, 75, 75, 30, 30),
(15, 90, 75, 30, 30),
(30, 105, 75, 30, 30),
(45, 120, 75, 30, 30),
(60, 120, 60, 30, 15),
(75, 120, 45, 30, 0),
]
def testConvertToAperio(tmpdir):
imagePath = datastore.fetch('huron.image2_jpeg2k.tif')
outputPath = os.path.join(tmpdir, 'out.svs')
large_image_converter.convert(imagePath, outputPath, format='aperio')
source = large_image.open(outputPath)
assert 'openslide' in source.name
assert 'label' in source.getAssociatedImagesList()
def testConvertMultiframeToAperio(tmpdir):
imagePath = datastore.fetch('sample.ome.tif')
outputPath = os.path.join(tmpdir, 'out.tiff')
large_image_converter.convert(imagePath,
outputPath,
format='aperio',
compression='jp2k')
source = large_image.open(outputPath)
assert 'label' in source.getAssociatedImagesList()
def testNewAndWriteLossless():
imagePath = datastore.fetch('sample_image.ptif')
source = large_image.open(imagePath)
out = large_image_source_vips.new()
for tile in source.tileIterator(
format=large_image.constants.TILE_FORMAT_NUMPY,
region=dict(right=4000, bottom=2000),
):
out.addTile(tile['tile'], x=tile['x'], y=tile['y'])
tmpdir = tempfile.mkdtemp()
outputPath = os.path.join(tmpdir, 'temp.tiff')
try:
out.write(outputPath, lossy=False)
assert os.path.getsize(outputPath) > 50000
result = large_image.open(outputPath)
resultMetadata = result.getMetadata()
assert resultMetadata['sizeX'] == 4000
finally:
shutil.rmtree(tmpdir)
def testTileOverlapWithRegionOffset():
imagePath = datastore.fetch('sample_image.ptif')
ts = large_image.open(imagePath)
tileIter = ts.tileIterator(region=dict(left=10000,
top=10000,
width=6000,
height=6000),
tile_size=dict(width=1936, height=1936),
tile_overlap=dict(x=400, y=400))
firstTile = next(tileIter)
assert firstTile['tile_overlap']['right'] == 200
def testNewAndWriteJPEG():
imagePath = datastore.fetch('sample_image.ptif')
source = large_image.open(imagePath)
# Update this if it doesn't direct to vips source
out = large_image.new()
for tile in source.tileIterator(
format=large_image.constants.TILE_FORMAT_NUMPY,
region=dict(right=4000, bottom=2000),
):
out.addTile(tile['tile'], x=tile['x'], y=tile['y'])
tmpdir = tempfile.mkdtemp()
outputPath = os.path.join(tmpdir, 'temp.jpeg')
try:
out.write(outputPath, vips_kwargs=dict(Q=80))
assert os.path.getsize(outputPath) > 50000
image = open(outputPath, 'rb').read()
assert image[:len(utilities.JPEGHeader)] == utilities.JPEGHeader
finally:
shutil.rmtree(tmpdir)
def testLazyTileRelease():
imagePath = datastore.fetch('sample_image.ptif')
ts = large_image.open(imagePath)
tiles = list(
ts.tileIterator(scale={'magnification': 2.5},
format=large_image.constants.TILE_FORMAT_IMAGE,
encoding='PNG'))
assert isinstance(tiles[5], large_image.tilesource.tiledict.LazyTileDict)
assert super(large_image.tilesource.tiledict.LazyTileDict,
tiles[5]).__getitem__('tile') is None
data = tiles[5]['tile']
assert len(tiles[5]['tile']) > 0
assert super(large_image.tilesource.tiledict.LazyTileDict,
tiles[5]).__getitem__('tile') is not None
tiles[5].release()
assert super(large_image.tilesource.tiledict.LazyTileDict,
tiles[5]).__getitem__('tile') is None
assert tiles[5]['tile'] == data
def _py_read_chunk_pixels(
self,
chunk_top,
chunk_left,
chunk_bottom,
chunk_right,
filename,
returned_magnification,
factor,
):
"""
Read from disk all the pixel data for a specific chunk of the
whole slide.
"""
filename = filename.numpy().decode("utf-8")
chunk_top = math.floor(chunk_top.numpy() / factor.numpy() + 0.01)
chunk_left = math.floor(chunk_left.numpy() / factor.numpy() + 0.01)
chunk_bottom = math.floor(chunk_bottom.numpy() / factor.numpy() + 0.01)
chunk_right = math.floor(chunk_right.numpy() / factor.numpy() + 0.01)
returned_magnification = returned_magnification.numpy()
import large_image
ts = large_image.open(filename)
chunk = ts.getRegion(
scale=dict(magnification=returned_magnification),
format=large_image.constants.TILE_FORMAT_NUMPY,
region=dict(
left=chunk_left,
top=chunk_top,
width=chunk_right - chunk_left,
height=chunk_bottom - chunk_top,
units="mag_pixels",
),
)[0]
# Do we want to support other than RGB and/or other than uint8?!!!
return tf.convert_to_tensor(chunk[..., :3], dtype=tf.uint8)
def testGetDummyTileSource():
source = large_image.open('large_image://dummy')
assert isinstance(source, large_image_source_dummy.DummyTileSource)
def testClassRepr():
imagePath = datastore.fetch('sample_image.ptif')
ts = large_image.open(imagePath)
assert 'sample_image.ptif' in repr(ts)
def testBaseFileNotFound():
with pytest.raises(large_image.exceptions.TileSourceFileNotFoundError):
large_image.open('nosuchfile')
with pytest.raises(large_image.exceptions.TileSourceFileNotFoundError):
large_image.open('nosuchfile.ext')
def __call__(self, slide):
"""
Add level, target_magnification, scan_magnification,
read_magnification, returned_magnification,
number_pixel_rows_for_slide, and
number_pixel_columns_for_slide fields to a slide dictionary.
"""
# Check values.
if "filename" not in slide:
raise ValueError('slide["filename"] must be already set.')
filename = slide["filename"]
# Do the work.
if not re.compile(r"\.zarr$").search(filename):
import large_image
# read whole-slide image file and create large_image object
ts = large_image.open(filename)
# scan_magnification = highest available magnification from source
scan_magnification = float(
ts.getNativeMagnification()["magnification"])
if self.magnification_source == "exact":
# Use the tile-source level that large_image is willing to interpolate
# for us.
preferred_levels = [
ts.getLevelForMagnification(self.target_magnification,
rounding=False)
]
else: # self.magnification_source in ["scan", "native"]
# Use one of the tile-source levels that is stored in the image file.
preferred_levels = list(
set(
ts.getPreferredLevel(level)
for level in range(ts.levels)))
preferred_levels.sort(reverse=True)
if self.magnification_source == "scan":
# Keep only the maximum tile-source level
preferred_levels = preferred_levels[0:1]
estimated_magnifications = np.array([
float(ts.getMagnificationForLevel(level)["magnification"])
for level in preferred_levels
])
# Find best tile-source level to use
(level,
returned_magnification) = self._get_level_and_magnifications(
self.target_magnification, estimated_magnifications)
# Rather than as the index into preferred_levels, change level to be the
# value that large_image uses
level = preferred_levels[level]
# If large_image is resampling a native level for us, it is starting with
# the preferred level that is the least one that is not smaller than the
# resampled level.
read_magnification = float(
ts.getMagnificationForLevel(
min([
ts.getPreferredLevel(i) for i in range(ts.levels)
if i >= level
]))["magnification"])
slide["target_magnification"] = self.target_magnification
slide["scan_magnification"] = scan_magnification
slide["read_magnification"] = read_magnification
slide["returned_magnification"] = returned_magnification
# We don't want to walk off the right or bottom of the slide so we are
# conservative as to how many pixels large_image will return for us.
# 1) large_image starts with an image that is of
# read_magnification; we compute the dimensions for read_magnification
# with math.floor from the dimensions of scan_magnification (i.e.,
# ts.sizeX and ts.sizeY) to be conservative.
# 2) large_image or external software may resampled from the
# read_magnification to the target_magnification; we compute dimensions
# for the target_magnification with math.floor from the
# read_magnification to be conservative.
number_pixel_rows_for_slide = ts.sizeY
number_pixel_columns_for_slide = ts.sizeX
if scan_magnification != read_magnification:
number_pixel_rows_for_slide = math.floor(
number_pixel_rows_for_slide * read_magnification /
scan_magnification)
number_pixel_columns_for_slide = math.floor(
number_pixel_columns_for_slide * read_magnification /
scan_magnification)
if read_magnification != self.target_magnification:
number_pixel_rows_for_slide = math.floor(
number_pixel_rows_for_slide * self.target_magnification /
read_magnification)
number_pixel_columns_for_slide = math.floor(
number_pixel_columns_for_slide *
self.target_magnification / read_magnification)
else:
import zarr
import openslide as os
# read whole-slide image and create zarr objects
store = zarr.DirectoryStore(filename)
source_group = zarr.open(store, mode="r")
# scan_magnification = highest available magnification from source
scan_magnification = float(
source_group.attrs[os.PROPERTY_NAME_OBJECTIVE_POWER])
preferred_levels = list(
range(0, source_group.attrs["level_downsamples"]))
if self.magnification_source == "scan":
preferred_levels = [
np.argmin(source_group.attrs["level_downsamples"])
]
# calculate magnifications of levels
estimated_magnifications = np.array(
scan_magnification /
source_group.attrs["level_downsamples"][level]
for level in preferred_levels)
# Find best native level to use
(level,
returned_magnification) = self._get_level_and_magnifications(
self.target_magnification, estimated_magnifications)
# Rather than as the index into preferred_levels, change level to be the
# value that zarr uses
level = preferred_levels[level]
slide["target_magnification"] = self.target_magnification
slide["scan_magnification"] = scan_magnification
slide["read_magnification"] = returned_magnification
slide["returned_magnification"] = returned_magnification
# get slide number_pixel_columns_for_slide, number_pixel_rows_for_slide at
# desired magnification. (Note that number_pixel_rows_for_slide is before
# number_pixel_columns_for_slide)
number_pixel_rows_for_slide, number_pixel_columns_for_slide = source_group[
format(level)].shape[0:2]
if (self.magnification_source == "exact"
and self.target_magnification != returned_magnification):
raise ValueError(
f"Couldn't find magnification {self.target_magnification}X in Zarr storage."
)
slide["level"] = level
# Note that slide size is defined by the requested magnification, which may not
# be the same as the magnification for the selected level. To get the slide
# size for the magnification that we are using, these values must later be
# multiplied by returned_magnification / target_magnification.
slide["number_pixel_rows_for_slide"] = number_pixel_rows_for_slide
slide[
"number_pixel_columns_for_slide"] = number_pixel_columns_for_slide