Metadata-Version: 2.1
Name: chia
Version: 2.0rc16
Summary: Concept Hierarchies for Incremental and Active Learning
Home-page: https://github.com/cvjena/chia
Author: Clemens-Alexander Brust
Author-email: clemens-alexander.brust@uni-jena.de
License: UNKNOWN
Description: # CHIA: Concept Hierarchies for Incremental and Active Learning
        ![PyPI](https://img.shields.io/pypi/v/chia)
        ![PyPI - License](https://img.shields.io/pypi/l/chia)
        ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/chia)
        ![Code Climate maintainability](https://img.shields.io/codeclimate/maintainability/cvjena/chia)
        ![codecov](https://codecov.io/gh/cvjena/chia/branch/main/graph/badge.svg)
        
        CHIA is a collection of methods and helper functions centered around hierarchical classification in a lifelong learning environment.
        It forms the basis for some of the experiments and tools developed at [Computer Vision Group Jena](http://www.inf-cv.uni-jena.de/).
        
        ## Requirements
        CHIA depends on:
        * python-configuration == 0.7.1
        * nltk ~= 3.5
        * imageio ~= 2.6
        * pillow ~= 7.1.0
        * gputil ~= 1.4.0
        * networkx ~= 2.4
        * numpy ~= 1.18.5
        * tensorflow-addons == 0.11.1
        * tensorflow == 2.3.0
        
        Optional dependencies:
        
        * tables ~= 3.6.1
        * pandas ~= 1.0.4
        * sacred ~= 0.8.1
        * pyqt5 ~= 5.15.0
        * scikit-image ~= 0.17.2
        * scikit-learn ~= 0.23.1
        * scipy == 1.4.1
        * matplotlib ~= 3.2.1
        
        ## Installation
        To install, simply run:
        ```bash
        pip install chia
        ```
        or clone this repository, and run:
        ```bash
        pip install -U pip setuptools
        python setup.py develop
        ```
        
        We also include the shell script `quick-venv.sh`, which creates a virtual environment and install CHIA for you.
        
        ## Getting Started
        To run the [example experiment](examples/experiment.py) which makes sure that everything works, use the following command:
        ```bash
        python examples/experiment.py examples/configuration.json
        ```
        After a few minutes, the last lines of output should look like this:
        ```text
        [DEBUG] [ExceptionShroud]: Leaving exception shroud without exception
        [SHUTDOWN] [Experiment] Successful: True
        ```
        
        ## Citation
        If you use CHIA for your research, kindly cite:
        > Brust, C. A., & Denzler, J. (2019, November). Integrating domain knowledge: using hierarchies to improve deep classifiers. In Asian Conference on Pattern Recognition (pp. 3-16). Springer, Cham.
        
        You can refer to the following BibTeX:
        ```bibtex
        @inproceedings{Brust2019IDK,
        author = {Clemens-Alexander Brust and Joachim Denzler},
        booktitle = {Asian Conference on Pattern Recognition (ACPR)},
        title = {Integrating Domain Knowledge: Using Hierarchies to Improve Deep Classifiers},
        year = {2019},
        }
        ```
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: GPU
Classifier: Operating System :: POSIX :: Linux
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.7
Description-Content-Type: text/markdown
