Read and write ImageJ ROI format
Project description
Roifile is a Python library to read, write, create, and plot ImageJ ROIs, an undocumented and ImageJ application specific format to store regions of interest, geometric shapes, paths, text, and whatnot for image overlays.
- Author:
- License:
BSD 3-Clause
- Version:
2022.7.29
- DOI:
10.5281/zenodo.6941603
Installation
Install the roifile package and common dependencies from the Python Package Index:
python -m pip install -U roifile tifffile matplotlib
Requirements
This release has been tested with the following requirements and dependencies (other versions may work):
Tifffile 2022.7.28 (optional)
Matplotlib 3.4.3 (optional)
Revisions
2022.7.29
Update metadata.
2022.3.18
Fix creating ROIs from float coordinates exceeding int16 range (#7).
Fix bottom-right bounds in ImagejRoi.frompoints.
2022.2.2
Add type hints.
Change ImagejRoi to dataclass.
Drop support for Python 3.7 and numpy < 1.19 (NEP29).
2021.6.6
Add enums for point types and sizes.
2020.11.28
Support group attribute.
Add roiread and roiwrite functions (#3).
Use UUID as default name of ROI in ImagejRoi.frompoints (#2).
2020.8.13
Support writing to ZIP file.
Support os.PathLike file names.
2020.5.28
Fix int32 to hex color conversion.
Fix coordinates of closing path.
Fix reading TIFF files with no overlays.
2020.5.1
Split positions from counters.
2020.2.12
Initial release.
Notes
The ImageJ ROI format cannot store integer coordinate values outside the range of -32768 to 32767 (16-bit signed).
Other Python packages handling ImageJ ROIs:
Examples
Create a new ImagejRoi instance from an array of x, y coordinates:
>>> roi = ImagejRoi.frompoints([[1.1, 2.2], [3.3, 4.4], [5.5, 6.6]]) >>> roi.roitype = ROI_TYPE.POINT >>> roi.options |= ROI_OPTIONS.SHOW_LABELS
Export the instance to an ImageJ ROI formatted byte string or file:
>>> out = roi.tobytes() >>> out[:4] b'Iout' >>> roi.tofile('_test.roi')
Read the ImageJ ROI from the file and verify the content:
>>> roi2 = ImagejRoi.fromfile('_test.roi') >>> roi2 == roi True >>> roi.roitype == ROI_TYPE.POINT True >>> roi.subpixelresolution True >>> roi.coordinates() array([[1.1, 2.2], [3.3, 4.4], [5.5, 6.6]], dtype=float32) >>> roi.left, roi.top, roi.right, roi.bottom (1, 2, 7, 8)
Plot the ROI using matplotlib:
>>> roi.plot()
View the overlays stored in a ROI, ZIP, or TIFF file from a command line:
python -m roifile _test.roi
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