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Open images as numpy arrays using SCIFIO and Bio-Formats
#!/usr/bin/env python
#
# scifio.py - Open images as numpy arrays using SCIFIO and Bio-Formats.
#
# -- Settings --
max_mem_mb = '6144'
scifio_lifesci = False
bio_formats = True
# -- Bill of Materials --
imagej_version = '2.0.0-rc-71'
scifio_version = '0.38.2'
scifio_bf_compat_version = '4.0.0'
scifio_lifesci_version = '0.9.0'
bio_formats_version = '6.3.0'
# -- Functions --
def dtype_from_meta(image_meta):
FormatTools = autoclass('io.scif.util.FormatTools')
endianness = '<' if image_meta.isLittleEndian() else '>'
pixel_types = {
FormatTools.INT8: 'i1',
FormatTools.UINT8: 'u1',
FormatTools.INT16: 'i2',
FormatTools.UINT16: 'u2',
FormatTools.INT32: 'i4',
FormatTools.UINT32: 'u4',
FormatTools.FLOAT: 'f4',
FormatTools.DOUBLE: 'f8'
}
pixel_type = pixel_types[image_meta.getPixelType()]
return endianness + pixel_type
def read_images(scifio, image_path):
import numpy
from jnius import autoclass, cast
# Initialize the SCIFIO reader.
LocationService = autoclass('org.scijava.io.location.LocationService')
location_service = cast(LocationService, scifio.get(LocationService))
image_location = location_service.resolve(image_path)
reader = scifio.initializer().initializeReader(image_location)
meta = reader.getMetadata()
images = []
# Iterate over each nD image in the dataset.
for i in range(0, reader.getImageCount()):
# Query image type and dimensions.
image_meta = meta.get(i)
dtype = dtype_from_meta(image_meta)
planar_axis_lengths = [image_meta.getAxisLength(p) for p in reversed(range(image_meta.getPlanarAxisCount()))]
all_axis_lengths = list(reversed(image_meta.getAxesLengths()))
# Iterate over each mD (m <= n; often m=2 or m=3) plane in the image.
planes = []
for p in range(0, reader.getPlaneCount(i)):
b = reader.openPlane(i, p).getBytes()
plane = numpy.frombuffer(bytes(b), dtype=dtype).reshape(planar_axis_lengths)
planes.append(plane)
image = numpy.concatenate(planes).reshape(all_axis_lengths)
images.append(image)
return images
# -- Main --
# Initialize SCIFIO with desired plugins.
import scyjava_config
scyjava_config.add_options('-Djava.awt.headless=true')
scyjava_config.add_options('-Xmx' + max_mem_mb + 'm')
endpoint = 'io.scif:scifio:{}'.format(scifio_version)
# Failed attempt to silence log4j and SLF4J warnings:
endpoint += '+org.slf4j:log4j-over-slf4j:1.7.28'
endpoint += '+org.slf4j:slf4j-simple:1.7.28'
if scifio_lifesci:
endpoint += '+io.scif:scifio-lifesci:{}'.format(scifio_lifesci_version)
if bio_formats:
endpoint += '+io.scif:scifio-bf-compat:{}'.format(scifio_bf_compat_version)
endpoint += '+ome:formats-api:{}'.format(bio_formats_version)
endpoint += '+ome:formats-bsd:{}'.format(bio_formats_version)
endpoint += '+ome:formats-gpl:{}'.format(bio_formats_version)
scyjava_config.add_repositories({'scijava.public': scyjava_config.maven_scijava_repository()})
scyjava_config.add_endpoints(endpoint)
import scyjava
from jnius import autoclass
SCIFIO = autoclass('io.scif.SCIFIO')
scifio = SCIFIO()
# Dump the class path, for debugging.
#import re
#from jnius import autoclass
#System = autoclass('java.lang.System')
#java_class_path = System.getProperty('java.class.path')
#print('Java class path:')
#for element in java_class_path.split(':'):
# print('\t' + re.sub('.*/', '', element))
# Read an image.
path = 'fiveD&pixelType=int16&axes=X,Y,Z,Channel,Time&lengths=17,7,2,3,5.fake'
#path = '/Users/curtis/data/blobs.gif'
images = read_images(scifio, path)
print('Image count = {}'.format(len(images)))
print('First image shape = {}'.format(images[0].shape))
# Clean up.
#scifio.getContext().dispose()
$ python scifio.py
log4j:WARN No appenders could be found for logger (org.bushe.swing.event.EventService).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
Image count = 1
First image shape = (5, 3, 2, 7, 17)
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