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convolve.py
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convolve.py
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from __future__ import print_function
import matplotlib.pyplot as plt
import matplotlib
import numpy as np
from scipy import ndimage as nd
from skimage import data
from skimage.util import img_as_float
from skimage.filter import gabor_kernel
from skimage.feature import hog
from skimage import data, color, exposure
# Includes code modified from http://scikit-image.org/docs/dev/auto_examples/plot_gabor.html#example-plot-gabor-py
image = img_as_float(data.load('/Users/davidharris/Downloads/untitled.png'))
# prepare filter bank kernels
kernels = []
for theta in (4, 3, 2, 1):
theta = theta / 4. * np.pi
for sigma in (1, 3):
for frequency in (0.05, 0.25):
kernel = np.real(gabor_kernel(frequency, theta=theta,
sigma_x=sigma, sigma_y=sigma))
kernels.append(kernel)
brick = img_as_float(data.load('/Users/davidharris/Downloads/untitled.png'))
outputs = [nd.convolve(brick, kernel, mode='nearest') for kernel in kernels]
print(outputs)