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coloranalysis is a package for calculating area of one or more colors in an image, provided the HEX codes.

Project 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.

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