Metadata-Version: 1.2
Name: hieralb
Version: 0.1.2
Summary: Tools for managing hierarchical albums of images.
Home-page: https://github.com/roads/hieralb
Author: Brett D. Roads
Author-email: brett.roads@gmail.com
License: MIT
Description-Content-Type: UNKNOWN
Description: ===========================
        Hieralb: Hierarchical Album
        ===========================
        
        A niche package
        ---------------
        Hieralb is composed of a small set of Python functions that implement a
        consistent identification scheme for images used in visual categorization. In
        this package, a collection of images is referred to as an *album*. Within an
        album, a given image can often be categorized at multiple levels (e.g., bird,
        kingfisher, ringed kingfisher) creating a hierarchy of categories. In many
        applications, it is desirable to consider these different levels of
        categorization. Hieralb enables you to easily generate unique *image IDs* and
        *class IDs* for all possible categories. Hieralb generates a set of plain text
        files that specify the relationship between the actual images, image IDs and
        class IDs. Lastly, Hieralb provides a Python class so that the album's
        structural relationships and ID's can easily be used in other Python
        applications.
        
        Getting started
        ---------------
        These instructions provide a guick overview of what you need to do to get
        started. More detailed instructions can be found below.
        
           1. Create a new folder ``<my_album_folder>``.
           2. Create the folder ``images`` inside ``<my_album_folder>``.
           3. Inside ``images``, create appropriately named folders. The folder names will become the literal class names.
           4. Place all of your images in the appropriate folders.
           5. To create the appropriate album files run:``$ python create_album_files.py <my_album_folder> <my_album_prefix>``
        
        Installation
        ------------
        There are two ways to get Hieralb:
        
           1. Install using pip: ``pip install hieralb``
           2. Clone from Git Hub: https://github.com/roads/hieralb.git
        
        Detailed instructions
        ---------------------
        This file covers the creation and management of domain directories for use in
        applications that require organized image databases. The core organization
        principle is that an image can be classified at different levels.
        Classification levels are modeled using a hierarchical folder structure.
        
        For example, consider an album containing bird images. Let's call this album
        birds-9, since there are nine different species. Let us also assume that we want
        to capture two different levels of categorization: the *taxonomic family* and
        *taxonomic species*. The bird directory might be organized in the following way:
        
        .. code-block:: bash
        
          birds-9/
          └── bird/
              ├── Parulidae/
              │   ├── Bobolink/
              │   ├── Hooded_Oriole/
              │   └── Scott_Oriole/
              ├── Passeridae/
              │   ├── Hooded_Warbler/
              │   ├── Kentucky_Warbler/
              │   └── Magnolia Warbler/
              └── Icteridae/
                  ├── Chipping_Sparrow/
                  ├── Fox_Sparrow/
                  └── Harris_Sparrow/
        
        After arranging the ``image/`` directory to your satisfaction (with the actual
        images placed in the appropriate species folder), you can run:
        ``$ python create_album_files.py birds-9 10000000``
        
        After running the script, the album directory will contain (at least) the
        following three text files:
        
        - classes.txt
           - A file listing all the classes (from all hierarchical levels) along with
             their corresponding class_id.
           - The file is composed of two columns using a space delimeter: <class_id>
             <class_name>
           - The class_id begins at 0 for each album, thus the class ID is not
             unique across albums. The root class in the directory tree is assigned
             class_id 0.
        - images.txt
           - A file listing all the images and their corresponding imag_id.
           - The file is composed of two columns using a space delimeter:
             <unqiue_image_id> <image_filename>
           - The unique_image_id is constructed using a numerical prefix supplied by the
             user (e.g., 10000000) which is added to a value starting at 1 (e.g.,
             10000001, 10000002, 10000002, ...). By using a prefix, the unique_image_id
             is unique across albums. Use the prefix "0" if you don't want to use a prefix.
        - image_class0.txt
           - A file mapping each image to its finest-grained class.
           - The file is composed of two columns using a space delimeter:
             <unique_image_id> <class_id>
        - class_class.txt
           - A file listing the mapping between a child class and its parent class.
           - A file composed of two columns using a space delimeter: <child class_id>
             <parent class_id>
        
        If the ``image/`` directory is more than one level deep (i.e, it contains nested
        classes), then additional files will be created. These files will follow the
        structure:
        
        - class<n>_class<n+1>.txt
           - A file listing the mapping between a class level n and its parent level n+1.
           - A file composed of two columns using a space delimeter: <child class_id>
             <parent class_id>
           - Level zero starts at the deepest leaf node of the directory tree.
        
        Once the appropriate files have been created, you can use the Album class to load 
        the data associated with an album into convenient python object. An album object 
        can be instantied by importing passing a string containing the path to the album directory. 
        
        .. code-block:: python
        
          from hieralb import Album
          birds_9_album = Album('\birds-9')
        
        Conventions and assumptions
        ---------------------------
        - Code has only been tested using Python 3
        - Folder names should be singular within the “images” folder (e.g., use bird not birds).
        - Use underscore as a placeholder for whitespace (e.g., “Hooded_Warbler”, not
        “Hooded Warbler”). Actual spaces can not be used in folder or filenames.
        - The depth of each leaf node (from the parent node) must be the same.
        
        Versioning
        ----------
        This package folows the Semantic Versioning 2.0.0 rules (https://semver.org).
        
        Authors
        -------
        - Brett D. Roads
        See also the list of contributors who participated in this project.
        
        License
        -------
        This project is licensed under the MIT License - see the LICENSE.txt file for details.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3
