Python library for reading and writing image data with special handlers for bio-formats from Allen Institute for Cell Science.
Project description
AICSImageIO
A Python library for reading and writing image data with specific support for handling bio-formats.
Features
- Supports reading metadata and imaging data from file path or buffered bytes for:
CZI
OME-TIFF
TIFF
- Any additional format supported by
imageio
- Supports writing metadata and imaging data for:
OME-TIFF
TIFF
- Any additional format supported by
imageio
Disclaimer:
This package is under heavy revision in preparation for version 3.0.0 release. The quick start below is representative of how to interact with the package under 3.0.0 and not under the current stable release.
Quick Start
from aicsimageio import AICSImage, imread
# For numpy array of image data
im = imread("/path/to/your/file_or_buffer.ome.tiff")
# For AICSImage object that
im = AICSImage("/path/to/your/file_or_buffer.ome.tiff")
# Image data is stored in `data` attribute
im.data # returns the image data numpy array
# Image metadata is stored in `metadata` attribute
im.metadata # returns whichever metadata parser best suites the file format
Notes
- Image data numpy arrays are always returned as six dimensional in dimension order
STCZYX
orScene
,Time
,Channel
,Z
,Y
, andX
. - Each file format may use a different metadata parser it is dependent on the reader's implementation.
Installation
Stable Release: pip install aicsimageio
Development Head: pip install git+https://github.com/AllenCellModeling/aicsimageio.git
Development
See CONTRIBUTING.md for information related to developing the code.
Free software: BSD-3-Clause
Project details
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