An active learning plugin for fine tuning of deep learning models.
Project description
Active Learning tools for ML models fine-tuning
Active learning tools for fine-tuning ML models
A plugin for running a complete active learning workflow
This napari plugin was generated with Cookiecutter using @napari's cookiecutter-napari-plugin template.
Installation
You can install napari-activelearning via pip:
pip install napari-activelearning
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 MIT license, "napari-activelearning" is free and open source software
Issues
If you encounter any problems, please [file an issue] along with a detailed description.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file napari_activelearning-0.0.2.tar.gz.
File metadata
- Download URL: napari_activelearning-0.0.2.tar.gz
- Upload date:
- Size: 45.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9637f7336f1b6c34562702299e44775d00c83485eae7fee21ab3700c71c6cc3c
|
|
| MD5 |
b19c72e8ae50c8130834a1dd08883000
|
|
| BLAKE2b-256 |
9aa8d4c7cd95eb9a6b5a3fef39c0a138551f75a27904fa94f77bee5cfb208abd
|
File details
Details for the file napari_activelearning-0.0.2-py3-none-any.whl.
File metadata
- Download URL: napari_activelearning-0.0.2-py3-none-any.whl
- Upload date:
- Size: 44.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
86a0ecb31fd2b2f171b63900a6248d560ffbd4932f66feafa01332344a069949
|
|
| MD5 |
45e83760820d01cad51ea5fabffea54c
|
|
| BLAKE2b-256 |
fdc217de094164357c6505141ef2c99f42b9908b3251a6e926a0d9a217d83290
|
