Metadata-Version: 1.2
Name: coloranalysis
Version: 1.2.0
Summary: coloranalysis is a package for calculating area of one or more colors in an image, provided the HEX codes.
Home-page: https://github.com/sravyadhulipala/coloranalysis
Author: Sravya Sree Dhulipala
Author-email: shravs.15feb@gmail.com
License: MIT
Description: # **coloranalysis**
        coloranalysis is a python package for calculating the percentage of area covered by one or more colors in an image.
        
        ### **Prerequisites**
        numpy, opencv and matplotlib are required to execute coloranalysis, you can download them using the following commands:
        ```
        pip install numpy
        pip install opencv-python
        pip install matplotlib
        ```
        
        ### **Installing**
        You can either clone or download this repository, or use this command:
        ```
        pip install coloranalysis
        ```
        
        ### **Usage**
        
        See [this notebook](https://github.com/sravyadhulipala/coloranalysis/blob/master/example/colorAreasExample.ipynb) for an example program on how to use this package. However, reading this document entirely is recommended.
        
        Let us consider this image of a rainbow. 
        
        <img src=https://github.com/sravyadhulipala/coloranalysis/blob/master/example/IPTestRainbow.jpg width="400" height="200">
        
        To know the area covered by red color, or the area covered by multiple colors in the image, we should get the HEX codes using a [colorpicker.](https://imagecolorpicker.com/)
        
        In the above image, HEX codes of all colors are: ["#FE0000", "#FD6400", "#FFFF02", "#008101", "#0000FE", "#4B0081", "#BC31FD"]
        
        Import colorArea, the class that calculates the area of the colors we want, as follows. 
        ```
        from coloranalysis.colors import colorAreas
        ```
        *colorAreas takes no arguments.*
        
        **getArea** 
        
        *returns* a list of the percentages of area covered by the given colors.
        
        *arguments* 
        
        - **hexColours**: A list of strings representing the HEX codes.
        - **path**: A string specifying the path of the image.
        - **diff**: An integer to determine the lower and upper boundaries of the given colors, in the HSV color space.
        
        *hexColours - colour with a 'u'*
        
        For a digital image as above, the recommended *diff* value is 10. While the recommended *diff* value for images of real-life objects is 30-50. 
        For more information on HSV color space, see [this link.](https://www.linuxtopia.org/online_books/graphics_tools/gimp_advanced_guide/gimp_guide_node51.html)
        
        **detectColor**
        
        *returns* a tuple with 'mask' and 'result' representing the pixels that match a single color
        
        *arguments*
        - **colour**: Values of the color in HSV color space, in the range H[0-360], S[0-100], V[0-100]
        - **img**: A numpy array returned by cv2.imread()
        - **hsv_img**: A numpy array returned by cv2.cvtColor()
        - **diff**: An integer to determine the lower and upper boundaries of the given colors, in the HSV color space.
        
        *colour - colour with a 'u'*
        
        'mask' and 'result' can be used to visualize the presence of the color in the given image
        
        **convertHEXColours**
        
        *returns* a tuple with two lists representing values of the colors in HSV colorspace and RGB colorspace respectively.
        
        *arguments* 
        - **hexColours**: A list of strings representing the HEX codes.
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Intended Audience :: Developers
Requires-Python: >=3.5
