Tomni is a collection of image analysis functions usefull for CytoSmart solution.
Project description
Tomni
Tomni is a python package that contains a collection of helper functions based on OpenCV and NumPy. It can be used for any python based computer vision or image analysis problem. The package simplifies the code and takes care of edge cages, everything from simplifying code like img_dim to compute optimization like labels2contours or illumination correction image processing. Tomni uses the image coordinates (same as OpenCV).
Tomni is created by CytoSMART.
The package was developed in-house to centralize the helper function for computer vision problems. In 2021, CytoSMART engineers turned it to open source, enabling researchers and educators to use it for free.
Getting Tomni
pip install tomni
License
Tomni is free for academic and educational use.
For commercial use please contact CytoSMART.
The name
The name Tomni is a combination of creator (Tom) and other CytoSMART product he was working on, the Omni. Tomni name was proposed by Denissa Daroţi, a former CytoSMART intern, who won a bet with her mentor by getting a (well deserved) 9/10 for her internship.
Features
- Bounding box fitting (bbox fitting)
- Center bounding box fit
- Custom location box fit
- Illumination correction
- Brightfield
- Fluorescence
- Contour operations
- Get center
- Approximate circle by area
- Json operation
- Add circularity property
- Scale object
- Translate object
- Make a mask
- Ellipse
- Polygon
- Shape fitting
- Rect around ellipse
- Transformers of data format
- Contours to json
- Ellipse to json
- Json 2 contours
- Json 2 label
- Labels 2 contours
- Labels 2 lists of points
Credits
Sorted alphabetically
- Coenraad Stijne
- Denisa Daroţi
- Hristo Atanasov
- Jelle van Kerkvoorde
- Kirsten Koopman
- Manon van Erp
- Marina Tzenkova
- Tom de Vries
- Tom Nijhof
History
1.11.0 (2022-04-11)
- Add inner contours to labels2contours
- Add inner contours to mask2json
1.10.0 (2022-02-17)
- Add approximate_circle_by_area to contour operations
- BUGFIX: Change type np.array to np.ndarray
- DEPRECATE: Remove simplification so python 3.8+ can be used
1.9.2 (2022-01-03)
- BUGFIX: Bufferoverflow make_mask_ellipse (again/still) remove times 2 for all values in the function
1.9.1 (2021-10-26)
- add ellipse to json2mask
- BUGFIX: Bufferoverflow make_mask_ellipse
- BUGFIX: Make make_mask_ellipse accept floats
1.9.0 (2021-10-01)
- add mask2bbox
- add contour2bbox
- add check_overlap_bbox
1.8.0 (2021-09-01)
- add mask2json
- add json2mask
1.7.4 (2021-07-02)
Upgrade/change requirements to work with python 3.9 Opencv needed fuzzy requirments Remove scikit-image from requirements by replacing the function with numpy function
1.7.3 (2021-06-23)
speedup positions2contour by replacing for-loop with numpy slicing
1.7.2 (2021-04-21)
Migrate to github
1.7.1 (2020-12-23)
updated setup file simplification<0.6
1.7.0 (2020-12-03)
added new functions
- add_area
- summary_json
- json2dict
1.6.4 (2020-11-26)
- add missing requirements in setup file
1.6.3 (2020-11-25)
- bug fix. cropping now with deepcopy
1.6.2 (2020-11-10)
-add fluo_tophat background subtraction
1.6.1 (2020-11-04)
-add accuracy to json2vgg
1.6.0 (2020-11-03)
- add json2vgg
1.5.2
- add ellipse to vgg2json 1.5.1
- fix rotation, flipping, crop import
1.5.0
add json_operations
- add crop list of jsons
- add flipping json
- add rotation json
1.4.0
- add get center point contour
- add get center point json
- add vgg2json
1.3.0
Updating of relative illumination correction.
- add (optional) smoothing step
- add (optional) resize step
- add (optional) normalization
1.2.0 (2020-07-02)
- Add translation of json functions
1.1.0 (2020-03-11)
Updating of illumination correction. Splitting into two illumination correction:
- absolute difference
- relative difference
1.0.0 (2020-03-06)
(new function)
- add_circularity
1.0.0 (2020-02-28)
Restructuring of tomni:
- Migrated Visualization to cytoBoom
- Migrated validation to manVal
- Made sure every function followed:
function_name
- init.py
- main.py
- test_function_name
- removed following function: -- channel_selecting (was only used for old cell counter) -- select_labels (complete replaceable by transformers.labels2listsOfPoints
- Added docstring to all functions
- Added typing to all functions
- Renamed everything to pep8
0.4.0 (2019-09-30)
Add transformer as category
- Add labels 2 list of points as function
0.3.3 (2019-09-17)
Draw_json (draw_json_mask_onto_image):
- rename it from draw_json_mask_onto_image to draw_json
- Make the Visualization of json shapes more dynamic.
- Callable directly from Visualization
- it return an image rather than manipulating it
- converts the color to the color type of input
0.2.1 (2019-07-24)
Remove f strings to prevent conflicts on python 3.5
0.2.0 (2019-07-09)
Visualization is now part of tomni.
STRUCTURE: BGR: All colors are Gray, BGR or BGRA. This because tomni is mostly combined with openCV usage.
FUNCTION:
- Add color converter
- Add circle draw function that works with the input of the cell counter
0.1.8 (2019-02-21)
- imdim: Function what gives the dimensions of an image from a numpy.ndarray
- ellipse_mask: creates an ellipse at a given position, with given radius length but a fixed rotation
0.0.1 (2018-10-15)
-
First release on PyPI.
ACADEMIC PUBLIC LICENSE version 1.1 Copyright (C) 2021 Preamble
This license contains the terms and conditions of using LuxConnector in noncommercial settings: at academic institutions for teaching and research use and for personal or educational purposes. You will find that this license provides noncommercial users of LuxConnector with rights that are similar to the well-known GNU General Public License, yet it retains the possibility for LuxConnector authors to financially support the development by selling commercial licenses. In fact, if you intend to use LuxConnector in a "for-profit" environment, where research is conducted to develop or enhance a product, is used in a commercial service offering, or when an entity uses LuxConnector to participate in government-funded, EU-funded, military or similar research projects, then you need to obtain a commercial license. In that case, or if you are unsure, please contact the Author info@cytosmart.com to inquire about commercial licenses.
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Initially written by Andras Varga (public domain) for OMNeT++ https://omnetpp.org/intro/license, adapted by CytoSMART TECHNOLOGIES BV. The adaptation is licensed under CC0 1.0 (Public Domain Dedication).
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