Matplotlib.colors.rgb_to_hsv() in Python

Last Updated : 07 Oct, 2021

Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.

matplotlib.colors.rgb_to_hsv()

The matplotlib.colors.rgb_to_hsv() function belongs to the matplotlib.colors module. The matplotlib.colors.rgb_to_hsv() function is used to convert float rgb in the range of 0 to 1 into a numpy array of hsv values.

Syntax: matplotlib.colors.rgb_to_hsv(arr)

Parameters:

arr: It is an array-like argument in the form of (…, 3) where all values must to be in the range of 0 to 1.

Returns:

hsv: It returns an ndarray in the form of (…, 3) that comprises of colors converted to hsv values within the range of 0 to 1.

Example 1:

import matplotlib.pyplot as plt 
import matplotlib.colors as mcolors 
   
  
# helper function to plot a  
# color table 
def colortable(colors, title,  
               colors_sort = True, 
               emptycols=0): 
   
    # cell dimensions 
    width = 212
    height = 22
    swatch_width = 48
    margin = 12
    topmargin = 40
   
    # Sorting colors based on hue, 
    # saturation, value and name. 
    if colors_sort is True: 
        to_hsv = sorted((tuple(mcolors.rgb_to_hsv(mcolors.to_rgb(color))), 
                         name) 
                        for name, color in colors.items()) 
        names = [name for hsv, name in to_hsv] 
    else: 
        names = list(colors) 
   
    length_of_names = len(names) 
    length_cols = 4 - emptycols 
    length_rows = length_of_names // length_cols + int(length_of_names % length_cols > 0) 
   
    width2 = width * 4 + 2 * margin 
    height2 = height * length_rows + margin + topmargin 
    dpi = 72
   
    figure, axes = plt.subplots(figsize=(width2 / dpi, height2 / dpi), 
                                dpi=dpi) 
      
    figure.subplots_adjust(margin/width2, margin/height2, 
                           (width2-margin)/width2,  
                           (height2-topmargin)/height2) 
      
    axes.set_xlim(0, width * 4) 
    axes.set_ylim(height * (length_rows-0.5), -height/2.) 
    axes.yaxis.set_visible(False) 
    axes.xaxis.set_visible(False) 
    axes.set_axis_off() 
    axes.set_title(title, fontsize=24, loc="left", pad=10) 
   
    for i, name in enumerate(names): 
        rows = i % length_rows 
        cols = i // length_rows 
        y = rows * height 
   
        swatch_start_x = width * cols 
        swatch_end_x = width * cols + swatch_width 
        text_pos_x = width * cols + swatch_width + 7
   
        axes.text(text_pos_x, y, name, fontsize=14, 
                horizontalalignment='left', 
                verticalalignment='center') 
   
        axes.hlines(y, swatch_start_x, swatch_end_x, 
                  color=colors[name], linewidth=18) 
   
    return figure 
   
colortable(mcolors.BASE_COLORS, "Base Colors", 
                colors_sort=False, emptycols=1) 
colortable(mcolors.TABLEAU_COLORS, "Tableau Palette", 
                colors_sort=False, emptycols=2) 
colortable(mcolors.CSS4_COLORS, "CSS Colors") 
   
plt.show() 

Output:

Example 2:

Image Used:

import matplotlib 
import matplotlib.pyplot as plt 
import matplotlib.image as mpimg 
  
  
image = mpimg.imread('food.jpeg') 
plt.title("Output image") 
  
  
hsv = matplotlib.colors.rgb_to_hsv(image) 
plt.imshow(hsv) 