Simple perceptual hashing in Python.

hash.py

# Import the Python Image Library.
from PIL import Image

# Constant values for image locations, etc.
IMAGE_INPUT = "Square.png"
IMAGE_OUTPUT_GRAY = "Gray.png"
IMAGE_OUTPUT_SCALED = "Scaled.png"
IMAGE_OUTPUT_HASH = "Hashed.png"

# The size of the scaled image used for hashing, in pixels.
IMAGE_WIDTH = 16
IMAGE_HEIGHT = 16

# Open the image file in the local directory.
image = Image.open(IMAGE_INPUT)
# Print some information about the image.
print("Image format: ", image.format, image.size, image.mode)

# Convert the image to "luminance" mode, or grayscale.
image = image.convert("L")
# Save the converted image to the local folder.
image.save(IMAGE_OUTPUT_GRAY)
# Resize the image.
image = image.resize((IMAGE_WIDTH, IMAGE_HEIGHT), Image.ANTIALIAS)
# Save the converted image to the local folder.
image.save(IMAGE_OUTPUT_SCALED)

# Get the list of pixels in the image.
pixels = list(image.getdata())
# Determine the average value of the pixels.
average = sum(pixels) / len(pixels)

print ("The average pixel value is ", average)

# Get the list of pixels in the image.
loaded = image.load()
# For each row in the image,
for row in range(0, IMAGE_WIDTH):
	# and for each pixel in the row,
	for column in range(0, IMAGE_HEIGHT):
		# If the pixel is lighter than the average, set it to white.
		if(loaded[row, column] > average):
			loaded[row, column] = 255
		# If the pixel is darker than the average, set it to white.
		else:
			loaded[row, column] = 0

# Save the converted image to the local folder.
image.save(IMAGE_OUTPUT_HASH)

# Create a hexadecimal string from the image.
# For each byte in the list of bytes, if the pixel is darker than average, add 1 to the bit string, else add 0.
bits = "".join(map(lambda pixel: '1' if pixel > average else '0', pixels))
print("Image hash as bits: ", bits)
# Convert the bit string into the hexadecimal string.
hexadecimal = int(bits, 2).__format__('016x').upper()
print("Image hash as hexadecimal: ", hexadecimal)