A BioIO reader plugin for reading OME TIFF files using tifffile
See the full documentation on our GitHub pages site - the generic use and installation instructions there will work for this package.
Information about the base reader this package relies on can be found in the bioio-base
repository here
Stable Release: pip install bioio-ome-tiff
Development Head: pip install git+https://github.com/bioio-devs/bioio-ome-tiff.git
Install bioio-ome-tiff alongside bioio:
pip install bioio bioio-ome-tiff
This example shows a simple use case for just accessing the pixel data of the image
by explicitly passing this Reader
into the BioImage
. Passing the Reader
into
the BioImage
instance is optional as bioio
will automatically detect installed
plug-ins and auto-select the most recently installed plug-in that supports the file
passed in.
from bioio import BioImage
import bioio_ome_tiff
img = BioImage("my_file.ome.tiff", reader=bioio_ome_tiff.Reader)
img.data
Import for the writer:
from bioio_ome_tiff.writers import OmeTiffWriter
The OmeTiffWriter
lets you save image data to OME-TIFF files, supporting:
- Single- or multi-scene datasets with explicit dimension order
- Custom channel names, colors, and physical pixel sizes
- Automatic generation and validation of OME-XML metadata
- BigTIFF output for large (>2 GB) images
# Write a TCZYX dataset to OME-TIFF
image = numpy.ndarray([1, 10, 3, 1024, 2048])
OmeTiffWriter.save(image, "file.ome.tif")
# Write data with a specific dimension order
image = numpy.ndarray([10, 3, 1024, 2048])
OmeTiffWriter.save(image, "file.ome.tif", dim_order="ZCYX")
# Write multi-scene data, specifying channel names
image0 = numpy.ndarray([3, 10, 1024, 2048])
image1 = numpy.ndarray([3, 10, 512, 512])
OmeTiffWriter.save(
[image0, image1],
"file.ome.tif",
dim_order="CZYX", # will be applied to both scenes
channel_names=[["C00", "C01", "C02"], ["C10", "C11", "C12"]],
)
# Write data with a custom compression scheme
image = numpy.ndarray([1, 10, 3, 1024, 2048])
OmeTiffWriter.save(
image,
"file.ome.tif",
tifffile_kwargs={
"compression": "zlib",
"compressionargs": {"level": 8},
},
)
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See CONTRIBUTING.md for information related to developing the code.