This release is a pre-release and may not be stable for production use.
napari-yapic-prediction
napari widget plugin to perform YAPiC model segmentation prediction in the napari window.
This napari plugin was generated with Cookiecutter using with @napari's cookiecutter-napari-plugin template.
Description
This napari plugin provides a widget to upload a YAPiC trained model and perform segmentation over all the present images in the napari window. The segmentation results are uploaded as napari layers into the viewer automatically with the name structure of imgename_prediction.
Installation
-
Please install either GPU or CPU version of tensorflow before installing the plugin depending on your system. One of the plugin dependency is
yapicthat currently has sensitivity to tensorflow versions. This behaviour will be removed in future. -
You can install
napari-yapic-predictionvia pip:pip install napari-yapic-prediction
Contributing
Contributions are very welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.
License
Distributed under the terms of the GNU GPL v3.0 license, "napari-yapic-prediction" is free and open source software
Issues
If you encounter any problems, please file an issue along with a detailed description.
1 maintainer
Release files for napari-yapic-prediction 0.1.dev102
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| napari-yapic-prediction-0.1.dev102.tar.gz | 4.4 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| napari_yapic_prediction-0.1.dev102-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 4.4 MB
Release files / napari-yapic-prediction-0.1.dev102.tar.gz
| Download URL | napari-yapic-prediction-0.1.dev102.tar.gz |
|---|---|
| Size | 4.4 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
01ba03289d028211e348d1df8a9f7b85951026fb1b6e4333b917295766847646
|
|
BLAKE2b-256 checksum How to use checksums |
8f35c37d4542b95dd1138f64da1b8a28f97162c103a72401fdd7a515f504e8bd
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10
|
Release files / napari_yapic_prediction-0.1.dev102-py3-none-any.whl
| Download URL | napari_yapic_prediction-0.1.dev102-py3-none-any.whl |
|---|---|
| Size | 21.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
f38f6af2ff303a2be4368650261d26c387e48834411ae5c8607c39ebae4230f4
|
|
BLAKE2b-256 checksum How to use checksums |
fc40c2a5b61358d483390884410dfa31a174c76eaf2fae25070371d166ff52e9
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.10
|
