skself

Explore methods to reduce the amount of effort required for industries to implement machine learning methods either by reducing the effort required to curate and annotate their datasets or by exploring out-of-the-box solutions like multimodal large language models or pretrained embeddings

https://github.com/thetoby9944/skself

Repository

Explore methods to reduce the amount of effort required for industries to implement machine learning methods either by reducing the effort required to curate and annotate their datasets or by exploring out-of-the-box solutions like multimodal large language models or pretrained embeddings

README.rst

This work is still under construction and grows overtime as I will continue to pursue my PhD based on the work that has been done so far on this project.



.. figure:: skself/assets/images/logo.png
   :align: center
   :alt:
   :scale: 20 %
   :width: 50px




.. image:: https://readthedocs.org/projects/skself/badge/?version=latest
    :target: https://tfds-defect-detection.readthedocs.io/en/latest/README.html
    :alt: Documentation Status
.. image:: https://img.shields.io/pypi/v/skself
   :target: https://pypi.org/project/tfds-defect-detection/
.. image:: https://img.shields.io/pypi/pyversions/skself
   :alt: PyPI - Python Version

========================================
skself
========================================

**Developing Self-supervised Systems in an industrial Setting**

The goal of this project is to explore methods to reduce the amount of effort required for industries to implement machine learning methods either by reducing the effort required to curate and annotate their datasets or by exploring out-of-the-box solutions like multimodal large language models or pretrained embeddings.



.. admonition:: Features

    - Lazy Labels:: 

         skself.partial_annotations.lazy_model.LazySegmentationModel

    - GPT Anomaly Detection::

         skself.partial_annotations MLLMANO.ipynb

    - Embedding Training::

         skself.embedding_training.embedding_benchmark.Baseline

         
         

         
+----------------------------------------+--------------------------------------------------------------------------+---------------------------------------------------------------------+
| Method                                 | Paper                                                                    | Link                                                                |
+========================================+==========================================================================+=====================================================================+
| Partial Annotations                    | Lazy Labels for Chicken Segmentation                                     | https://www.sciencedirect.com/science/article/pii/S1877050923014163 |
+----------------------------------------+--------------------------------------------------------------------------+---------------------------------------------------------------------+
| Multimodal Large Language Models       | Low-shot Visual Anomaly Detection with Multimodal Large Language Models  | in press                                                            |
+----------------------------------------+--------------------------------------------------------------------------+---------------------------------------------------------------------+
| Embedding Training                     |                                                                          | under review                                                        |
+----------------------------------------+--------------------------------------------------------------------------+---------------------------------------------------------------------+





Install
-------

Create a new python=3.9 env and install `skself` from pip

.. code-block:: bash

    pip install git+https://github.com/thetoby9944/skself.git


Examples
-------


To directly jump into the code look at the sample notebook

|Open in Colab|


.. |Open in Colab| image:: https://img.shields.io/badge/Open%20In-Colab-orange?style=for-the-badge&logo=data:image/png;base64,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
   :target: https://colab.research.google.com/drive/1KGR3EeF6eV-dgO07DZ_NCqSgrAJbzhCs?usp=sharing





Cite
----


If this project helped you during your work:
Until a publication is available, please cite as

Tobias Schiele et al. (2023). skself https://github.com/thetoby9944/skself.


.. code-block:: latex

   @misc{Schiele2019,
       author = {Tobias Schiele, Daria Kern, Prof. Dr. Ulrich Klauck},
       title = {Skself},
       year = {2022},
       publisher = {GitHub},
       journal = {GitHub repository},
       howpublished = {\url{https://github.com/thetoby9944/skself}},
   }


This work is funded by

.. figure:: skself/assets/images/acks.jpeg
   :align: center
   :alt:
   :scale: 20 %

until July 2024 and will receive continued personal updates and maintenance over the course of my PhD until January 2025.

Owner

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
  - family-names: Schiele
    given-names: Tobias
  - family-names: Kern
    given-names: Daria
  - family-names: Klauck
    given-names: Ulrich
title: "skself - Self-supervised learning sklearn-style"
version: 0.1.0
date-released: 2022-10-11

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