1.2.1 Input - Console

To use the application provide a path to the image that the application should extract colors from. In the following example the image is in the folder we are executing the command and the name of the image is gameboy.png:

$ extcolors gameboy.png

In this example gameboy.png refers to the following image created by Rebecca Machamer.

1.2.2 Input - Script

To use the application provide a path to the image that the application should extract colors from. In the following example the image is in the folder we are executing the command and the name of the image is gameboy.png:

>>> import extcolors
>>> colors, pixel_count = extcolors.extract("gameboy.png")
>>> print(colors)
[((0, 172, 170), 386062), ((245, 245, 245), 59559), ((82, 90, 92), 17824), ((102, 184, 52), 15080), ((236, 27, 111), 1302), ((255, 180, 0), 137), ((241, 148, 185), 36)]

1.2.3 Output - Text

When the application is done it will output information about the execution. Probably the most relevant information is the [RESULT]-section that contains the extracted colors in RGB values and their occurrence rate presented in percentages.

Output based on gameboy.png:

Extracted colors:
(0, 172, 170)  :  80.43% (386062)
(245, 245, 245):  12.41% (59559)
(82, 90, 92)   :   3.71% (17824)
(102, 184, 52) :   3.14% (15080)
(236, 27, 111) :   0.27% (1302)
(255, 180, 0)  :   0.03% (137)
(241, 148, 185):   0.01% (36)

Pixels in output: 480000 of 480000

1.2.4 Output - Image

When the application is done it will also create an image in the directory where the command was executed. The image will contain the colors that where extracted sorted based on their occurrence rate, wrapping from from left to right. The image will use the name of the original image appended with a time stamp of when the execution took place.

Output based on gameboy.png:

1.4.1 Performance

When an image contains a large amount of different colors, which most do, the performance slows to a halt. If the grouping of colors is not desired/required then a workaround is to set the tolerance levels to zero. Setting the tolerance to specifically zero will make the application skip any comparisons from being made and become a simple counter resulting in much greater speeds.

Example, an image (3840x2160) containing about 340k unique colors will take two hours to complete with a tolerance level of 32 (the default value). However with a tolerance level of zero it will take ten seconds.

1.4.2 Adobe RGB Color Space Not Supported

Currently only the sRGB color space is supported when converting to CIE L*a*b*. Which means that grouped colors might not visual match as one would expect.