Metadata-Version: 2.1
Name: selective_search
Version: 0.1.0a0
Summary: Selective Search in Python
Home-page: https://github.com/ChenjieXu/selective_search
Author: Chenjie Xu
Author-email: cxuscience@gmail.com
License: MIT
Description: # Selective Search
        
        [![PyPI](https://img.shields.io/pypi/v/selective_search)](https://pypi.org/project/selective-search/)
        [![Travis Build Status](https://travis-ci.org/ChenjieXu/selective_search.svg?branch=master)](https://travis-ci.org/ChenjieXu/selective_search)
        [![Codacy grade](https://img.shields.io/codacy/grade/8d5b9ce875004d458bdf570f4d719472)](https://www.codacy.com/manual/ChenjieXu/selective_search)
        
        This is a full implementation of selective search in Python. The implementation is typically based on this paper[[1]](#Uijlings). It have three selective search modes according to various diversification strategies as in the paper.
        
        ## Installation
        Installing from [PyPI](https://pypi.org/project/selective-search/) is recommended :
        ```
        $ pip install selective-search
        ```
        It is also possible to install the latest version from [Github source](https://github.com/ChenjieXu/selective_search/):
        ```
        $ git clone https://github.com/ChenjieXu/selective_search.git
        $ cd selective_search
        $ python setup.py install
        ```
        
        ## Quick Start
        
        ```python
        import skimage.io
        from selective_search import selective_search
        
        # Load image as NumPy array from image files
        image = skimage.io.imread('path/to/image')
        
        # Run selective search using single mode
        boxes = selective_search(image, mode='single')
        ```
        For detailed examples, refer [this](https://github.com/ChenjieXu/selective_search/tree/master/examples) part of the repository.
        
        ## Search Mode
        | Mode    | Color Spaces        | Similarity Measures | Starting Regions (k) | Number of Combinations |
        |---------|---------------------|---------------------|----------------------|------------------------|
        | single  | HSV                 | CTSF                | 100                  | 1                      |
        | fast    | HSV, Lab            | CTSF, TSF           | 50, 100              | 8                      |
        | quality | HSV, Lab, rgI, H, I | CTSF, TSF, F, S     | 50, 100, 150, 300    | 80                     |
        
        ## References
        \[1\] <a name="Uijlings"> [J. R. R. Uijlings et al., Selective Search for Object Recognition, IJCV, 2013](https://ivi.fnwi.uva.nl/isis/publications/bibtexbrowser.php?key=UijlingsIJCV2013&bib=all.bib)
        
Keywords: rcnn
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Description-Content-Type: text/markdown
