Metadata-Version: 2.1
Name: plums
Version: 0.5.1
Summary: Playground ML Unified Microlib Set: The Playground ML python toolbox package
Home-page: UNKNOWN
Author: Airbus DS GEO
Author-email: jeffaudi.airbus@gmail.com
License: MIT
Description: # ![PLUMS](docs/source/_static/plums.png)
        
        **PL**aygroundML **U**nified **M**icrolib **S**et : The **Playground ML** python *toolbox* package
        
        [![pyversions](https://img.shields.io/badge/python-3.6%20%7C%203.7%20%7C%203.8%20%7C%203.9-informational)](https://github.com/airbusgeo/playground-plums)
        [![License](https://img.shields.io/badge/License-MIT-green)](https://choosealicense.com/licenses/mit/)
        
        
        The Plums library set aims to defined a common set of packages to be used by people involved in thePlaygroundML team.
        
        Those packages puropose is to set a unique baseline to help make the code base more unified and avoid countless reimplementation of the same tools which in turns make people waste time and make the code base herd to understand,
        debug and reuse.
        
        Installation is simple with *PyPI* repository:
        
        ```bash
        pip install plums
        ```
        
        [TODO]
        More information on installation can be found in the [Getting Started](https://playground-plums.readthedocs.io/en/latest/content/getting_started.html) section of the documentation.
        
        Documentation and tests specific dependencies can be installed with the ``docs`` and ``tests`` extra keywords respectively.
        
        ## Packages
        
        ### Commons
        
        The Plums **commons** package aims to offer a set of lightweight highly
        reusable classes and utilities for all other packages.
        
        To import do:
        
        ```python
        import plums.commons
        ```
        
        ### Plot
        
        The Plums **plot** package aims to offer a set of lightweight highly
        reusable classes and utilities for visualizing detection and segmentation
        results.
        
        To import do:
        
        ```python
        import plums.plot
        ```
        
        ### Model
        
        The Plums **model** package aims to offer a framework-agnostic model
        format specification (the **P**lums **M**odel **F**ormat) along with its
        python representation and helper implementation to ease integration into
        producer and consumer codebases.
        
        To import do:
        
        ```python
        import plums.model
        ```
        
        ### Dataflow
        
        **I/O** operations and efficient *dataset* iteration and indexing
        handling.
        
        To import do:
        
        ```python
        import plums.dataflow
        ```
        
        -------------------------------------------------------------------
        
        ## Objectives
        
        ### Dataflow
        
        Dataflow elements to speedup future developements: e.g. `Dataset` classes, `Sampler` and/or `Dataloader` (?) and handle augmentation (`imgaug`, `albumentation`, `pure numpy` ?)
        
        * Python representation of data elements (e.g. `Annotation`, `Feature`, `Image`, `Datapoint`...)
        * `Dataset` classes for playground datasets
        * `TranformedDataset`-like classes to manipulate, combine and transform (e.g. augmentations) datasets in an online fashion
        * `Sampler` and `BatchSampler` classes to port PyTorch functionalities into Keras and build upon them
        
        ### Data-preparation
        
        * Loop through datasets in a multi-threaded or multi-processed fashion
        * Some convenient data-preparation functions such as image transformations or annotations refinement
        * Some convenient statistic and analysis tools
        
        ### Visualisation
        
        * Plot annotation on image
        * Handle single image and image grids
        * Plot differentials and/or superposition of annotations on same images
        * Handle multiple color code mode, e.g.:
        	* By label
        	* By confidence
        	* By size
        	* By type (in differential plotting)
        	* And possibly combination of examples above (e.g. Color by label and shades by confidence)
        
        ### Model Format (UMF like ?)
        
        * Python representation of a model and its format components
        * IO functionalities, e.g.:
        	* Save a model (as collect disparate resources into a coherent model directory w/ metadata)
        	* Load a model (as create a Python model representation w/ metadata from a model directory)
        	* Verify an existing model directory
        	* Copy and/or prune a model
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: docs
Provides-Extra: lint
Provides-Extra: tests
