Detect edges in colour photos

minimal-edge-detection.py

"""
Minimalist RGB edge detection w/ NumPy, PIL
Authored by Eric Easthope
MIT License
"""

from numpy import asarray, pi, pad, zeros
from numpy.fft import fft2, ifft2
from PIL.Image import open, fromarray

# Open image as Numpy array
image = asarray(open("foo.png"))

# Define edge filtering kernel
kernel = asarray([
    [-1, -1, -1],
    [-1, 10 * pi, -1],
    [-1, -1, -1]
])

# Add padding to kernel
padded_kernel = pad(
    kernel,
    ((0, image.shape[0] - kernel.shape[0]), (0, image.shape[1] - kernel.shape[1])),
)

# Check that padded kernel has same shape as image
assert padded_kernel.shape[:2] == image.shape[:2]

# Filter image for all three RGB channels
filtered_image = zeros(shape=image.shape)
for i in range(3):
    # Filter colour channel using Fourier Transform with padded kernel
    channel = ifft2(fft2(image[:, :, i]) * fft2(padded_kernel)).real

    # Zero values not in RGB colour range
    channel[channel < 0] = 0
    channel[channel > 255] = 0

    filtered_image[:, :, i] = channel

# Get and show filtered image from Numpy array
fromarray(filtered_image.astype("uint8")).show()