Hi all, I was hoping the community may be able to help me. I want to convert rgb values to their L*A*B* value but I'm not sure of the best way to do so so the setup will scale when the dataframe size increases.
I saw on stackoverflow that skimage's conversion method http://scikit-image.org/docs/dev/api/skimage.color.html?highlight=rgb2lab#skimage.color.rgb2lab was suggested to be faster than alternatives but I'm having trouble understanding how to use my dataframe as the input instead of an image and if the conversion is successful how I can store the LAB values back into the dataframe. At the moment my dataframe has a shape (827, 8) where Rgb_r, Rgb_g, Rgb_b are the column names I'm interested in, you could think of the dataframe of 827 individual pixels with associated metadata. Is it possible to pass a pandas dataframe to scikit-image color.rgb2.lab or should I do row by row calculates for the situation where the number of rows increases to possibly 200,000 or more Hope you can help me Michael
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