Python PIL | Image.histogram()

PIL is the Python Imaging Library which provides the python interpreter with image editing capabilities. The Image module provides a class with the same name which is used to represent a PIL image. The module also provides a number of factory functions, including functions to load images from files, and to create new images.

Image.histogram() Returns a histogram for the image. The histogram is returned as a list of pixel counts, one for each pixel value in the source image. If the image has more than one band, the histograms for all bands are concatenated (for example, the histogram for an “RGB” image contains 768 values).

A bi-level image (mode “1”) is treated as a greyscale (“L”) image by this method. If a mask is provided, the method returns a histogram for those parts of the image where the mask image is non-zero. The mask image must have the same size as the image, and be either a bi-level image (mode “1”) or a greyscale image (“L”).



Syntax: Image.histogram(mask=None, extrema=None)

Parameters:
mask – An optional mask.

Returns: A list containing pixel counts.

Image Used:

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from PIL import Image
  
img = Image.open(r"C:\Users\System-Pc\Desktop\tree.jpg")
r, g, b = img.split()
len(r.histogram())
### 256 ###
  
r.histogram()

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Output:

[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 3, 1, 2, 3, 4, 3, 2, 3, 10, 7, 6, 7, 13, 14, 6, 22, 9, 19, 23, 21, 29, 23, 36, 42, 32, 46, 59, 51, 53, 69, 49, 61, 64, 79, 69, 55, 66, 73, 78, 64, 82, 84, 83, 67, 85, 87, 91, 84, 87, 63, 79, 86, 86, 77, 75, 78, 85, 77, 78, 92, 83, 78, 86, 90, 97, 96, 94, 90, 94, 76, 99, 97, 113, 108, 92, 120, 124, 110, 140, 121, 124, 132, 144, 132, 145, 151, 163, 145, 147, 184, 151, 161, 177, 199, 200, 205, 218, 223, 274, 237, 245, 254, 260, 281, 299, 301, 354, 361, 335, 392, 365, 375, 389, 367, 396, 387, 415, 398, 404, 417, 404, 405, 447, 483, 493, 484, 470, 440, 473, 472, 441, 462, 467, 461, 468, 474, 438, 449, 451, 431, 468, 470, 415, 452, 407, 379, 411, 358, 383, 418, 375, 414, 376, 375, 341, 361, 340, 350, 354, 293, 318, 325, 297, 316, 287, 326, 287, 307, 289, 314, 296, 275, 262, 281, 262, 278, 268, 320, 254, 288, 279, 280, 259, 252, 257, 257, 245, 227, 231, 254, 282, 263, 248, 218, 250, 246, 232, 244, 237, 208, 217, 215, 226, 205, 223, 212, 227, 220, 213, 198, 197, 224, 193, 200, 173, 190, 184, 190, 183, 3263]

Another Example:Here used another image.

Image Used:

filter_none

edit
close

play_arrow

link
brightness_4
code

   
  
from PIL import Image
  
img = Image.open(r"C:\Users\System-Pc\Desktop\tree.jpg")
r, g, b = img.split()
len(r.histogram())
### 256 ###
  
r.histogram()

chevron_right


Output:

[970, 228, 158, 207, 258, 217, 257, 260, 256, 252, 224, 277, 247, 293, 294, 305, 303, 309, 318, 321, 343, 326, 313, 295, 346, 292, 356, 340, 305, 311, 360, 373, 350, 357, 384, 356, 325, 380, 373, 389, 355, 336, 328, 349, 364, 335, 390, 340, 343, 382, 343, 339, 351, 329, 364, 350, 356, 362, 381, 349, 386, 366, 351, 345, 357, 353, 339, 359, 387, 346, 371, 359, 319, 330, 321, 311, 300, 313, 325, 338, 322, 330, 303, 354, 335, 321, 313, 289, 286, 286, 264, 279, 267, 255, 277, 266, 297, 261, 282, 267, 254, 269, 246, 244, 265, 240, 231, 250, 210, 227, 202, 200, 217, 191, 187, 217, 199, 171, 180, 152, 195, 172, 158, 170, 177, 159, 151, 152, 143, 159, 183, 138, 169, 162, 145, 161, 147, 150, 160, 186, 163, 153, 139, 153, 149, 144, 148, 143, 167, 144, 184, 154, 160, 134, 130, 144, 176, 118, 140, 132, 115, 119, 130, 130, 120, 125, 121, 133, 105, 123, 105, 106, 92, 114, 101, 112, 103, 106, 98, 118, 110, 111, 99, 99, 107, 74, 109, 83, 94, 97, 87, 85, 88, 77, 77, 92, 94, 69, 91, 97, 71, 100, 83, 80, 83, 53, 89, 72, 68, 70, 58, 74, 67, 69, 64, 80, 81, 68, 57, 47, 60, 53, 59, 53, 64, 63, 69, 52, 48, 46, 51, 52, 41, 49, 45, 43, 41, 32, 43, 42, 47, 46, 34, 38, 39, 34, 33, 31, 21, 23, 28, 25, 15, 15, 24, 148]



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