Find most used colors in image using Python

Prerequisite: PIL

PIL is the Python Imaging Library which provides the python interpreter with image editing capabilities. It was developed by Fredrik Lundh and several other contributors. Pillow is the friendly PIL fork and an easy-to-use library developed by Alex Clark and other contributors. We’ll be working with Pillow.

Let’s understand with step-by-step implementation:

1. Read an image

For reading the image in PIL, we use Image method.

# Read an Image
img = Image.open('File Name')

2. Convert into RGB image

img.convert('RGB')

3. Get Width and Height of Image

width, height = img.size

4. Iterate through all pixels of Image and get R, G, B value from that pixel

for x in range(0, width):
    for y in range(0, height):
        r, g, b = img.getpixel((x,y))
        print(img.getpixel((x,y)))

Output:

(155, 173, 151), (155, 173, 151), (155, 173, 151), (155, 173, 151), (155, 173, 151) …

5. Initialize three variable

• r_total = 0
• g_total = 0
• b_total = 0

Iterate through all pixel and add each color to different Initialized variable.

r_total = 0
g_total = 0
b_total = 0

for x in range(0, width):
    for y in range(0, height):
        r, g, b = img.getpixel((x,y))
        r_total += r
        g_total += g
        b_total += b
print(r_total, g_total, b_total)

Output:

(29821623, 32659007, 33290689)

As we can R, G & B value is very large, here we will use count variable

Initialize One More variable

count = 0

Divide total color value by count

Below is the Implementation:

Image Used – 

Python3

# Import Module
from PIL import Image

def most_common_used_color(img):
    # Get width and height of Image
    width, height = img.size

    # Initialize Variable
    r_total = 0
    g_total = 0
    b_total = 0

    count = 0

    # Iterate through each pixel
    for x in range(0, width):
        for y in range(0, height):
            # r,g,b value of pixel
            r, g, b = img.getpixel((x, y))

            r_total += r
            g_total += g
            b_total += b
            count += 1

    return (r_total/count, g_total/count, b_total/count)

# Read Image
img = Image.open(r'C:\Users\HP\Desktop\New folder\mix_color.png')

# Convert Image into RGB
img = img.convert('RGB')

# call function
common_color = most_common_used_color(img)

print(common_color)
# Output is (R, G, B)

Output:

# Most Used color is Blue
(179.6483313253012, 196.74100602409638, 200.54631927710844)