Bitmap/Histogram: Difference between revisions

=={{header|Python}}==

Makes use of the Pillow library (PIL) you can install it using pip. The code is probably not the fastest or the image I used (1960x1960) is just too big.

<lang python>from PIL import Image

# Open the image

image = Image.open("lena.jpg")

# Get the width and height of the image

width, height = image.size

# Calculate the amount of pixels

amount = width * height

# Total amount of greyscale

total = 0

# B/W image

bw_image = Image.new('L', (width, height), 0)

# Bitmap image

bm_image = Image.new('1', (width, height), 0)

for h in range(0, height):

for w in range(0, width):

r, g, b = image.getpixel((w, h))

greyscale = int((r + g + b) / 3)

total += greyscale

bw_image.putpixel((w, h), gray_scale)

# The average greyscale

avg = total / amount

black = 0

white = 1

for h in range(0, height):

for w in range(0, width):

v = bw_image.getpixel((w, h))

if v >= avg:

bm_image.putpixel((w, h), white)

else:

bm_image.putpixel((w, h), black)

bw_image.show()

bm_image.show()</lang>