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from cv2 import resize, INTER_LANCZOS4, INTER_AREA
from skimage.color import rgb2gray
import numpy as np
from scipy.ndimage.filters import gaussian_filter
from skimage.filters import threshold_otsu
import matplotlib.pyplot as plt
class XDoGSketcher:
def __init__(self, gamma = 0.95, phi = 89.25, eps = -0.1, k = 8, sigma = 0.5, mult = 1):
self.params = {}
self.params['gamma'] = gamma
self.params['phi'] = phi
self.params['eps'] = eps
self.params['k'] = k
self.params['sigma'] = sigma
self.params['mult'] = mult
def _xdog(self, im, **transform_params):
# Source : https://github.com/CemalUnal/XDoG-Filter
# Reference : XDoG: An eXtended difference-of-Gaussians compendium including advanced image stylization
# Link : http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.365.151&rep=rep1&type=pdf
if im.shape[2] == 3:
im = rgb2gray(im)
imf1 = gaussian_filter(im, transform_params['sigma'])
imf2 = gaussian_filter(im, transform_params['sigma'] * transform_params['k'])
imdiff = imf1 - transform_params['gamma'] * imf2
imdiff = (imdiff < transform_params['eps']) * 1.0 \
+ (imdiff >= transform_params['eps']) * (1.0 + np.tanh(transform_params['phi'] * imdiff))
imdiff -= imdiff.min()
imdiff /= imdiff.max()
th = threshold_otsu(imdiff)
imdiff = imdiff >= th
imdiff = imdiff.astype('float32')
return imdiff
def get_sketch(self, image, **kwargs):
current_params = self.params.copy()
for key in kwargs.keys():
if key in current_params.keys():
current_params[key] = kwargs[key]
result_image = self._xdog(image, **current_params)
return result_image
def get_sketch_with_resize(self, image, **kwargs):
if 'mult' in kwargs.keys():
mult = kwargs['mult']
else:
mult = self.params['mult']
temp_image = resize(image, (image.shape[1] * mult, image.shape[0] * mult), interpolation = INTER_LANCZOS4)
temp_image = self.get_sketch(temp_image, **kwargs)
image = resize(temp_image, (image.shape[1], image.shape[0]), interpolation = INTER_AREA)
return image
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