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import cv2
import numpy as np
from PIL import Image
import requests
# Difference of Gaussians applied to img input
def dog(img,size=(0,0),k=1.6,sigma=0.5,gamma=1):
img1 = cv2.GaussianBlur(img,size,sigma)
img2 = cv2.GaussianBlur(img,size,sigma*k)
return (img1-gamma*img2)
# Threshold the dog image, with dog(sigma,k) > 0 ? 1(255):0(0)
def edge_dog(img,sigma=0.5,k=200,gamma=0.98):
aux = dog(img,sigma=sigma,k=k,gamma=0.98)
for i in range(0,aux.shape[0]):
for j in range(0,aux.shape[1]):
if(aux[i,j] > 0):
aux[i,j] = 255
else:
aux[i,j] = 0
return aux
# garygrossi xdog version
def xdog_garygrossi(img,sigma=0.5,k=200, gamma=0.98,epsilon=0.1,phi=10):
aux = dog(img,sigma=sigma,k=k,gamma=gamma)/255
for i in range(0,aux.shape[0]):
for j in range(0,aux.shape[1]):
if(aux[i,j] >= epsilon):
aux[i,j] = 1
else:
ht = np.tanh(phi*(aux[i][j] - epsilon))
aux[i][j] = 1 + ht
return aux*255
def hatchBlend(image):
xdogImage = xdog(image,sigma=1,k=200, gamma=0.5,epsilon=-0.5,phi=10)
hatchTexture = cv2.imread('./imgs/hatch.jpg', cv2.CV_LOAD_IMAGE_GRAYSCALE)
hatchTexture = cv2.resize(hatchTexture,(image.shape[1],image.shape[0]))
alpha = 0.120
return (1-alpha)*xdogImage + alpha*hatchTexture
# version of xdog inspired by article
def xdog(img,sigma=0.5,k=1.6, gamma=1,epsilon=1,phi=1):
aux = dog(img,sigma=sigma,k=k,gamma=gamma)/255
for i in range(0,aux.shape[0]):
for j in range(0,aux.shape[1]):
if(aux[i,j] < epsilon):
aux[i,j] = 1*255
else:
aux[i,j] = 255*(1 + np.tanh(phi*(aux[i,j])))
return aux
def to_sketch(img_orig, sigma=0.3, k=4.5, gamma=0.95, epsilon=-1, phi=10e15, area_min=2):
img_cnts = []
img = cv2.cvtColor(np.array(img_orig), cv2.COLOR_RGB2GRAY)
img_xdog = xdog(img, sigma=sigma, k=k, gamma=gamma, epsilon=epsilon, phi=phi).astype(np.uint8)
new_img = np.zeros_like(img_xdog)
thresh = cv2.threshold(img_xdog, 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
cnts = cv2.findContours(thresh.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
area = cv2.contourArea(c)
if area > area_min:
img_cnts.append(c)
return Image.fromarray(255 - cv2.drawContours(new_img, img_cnts, -1, (255,255,255), -1))
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