def convert(now):
print()
img = input('Enter the filename for the output image: ')
print()
directory = img
# To create the folder in sketches of that filename
# And this folder will contain all images as transition to sketch
parent_dir = f'.\\ImageToSketch\\sketches'
path = os.path.join(parent_dir, directory)
try:
os.mkdir(path)
except OSError as error:
print(error)
image = cv2.imread(now)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
cv2.imwrite(f"{path}\\{img}(gray).png", gray)
inverted = 255 - gray
cv2.imwrite(f"{path}\\{img}(inverted).png", inverted)
blurred = cv2.GaussianBlur(inverted, (21, 21), 0)
cv2.imwrite(f"{path}\\{img}(blured).png", blurred)
inverted_blurred = 255 - blurred
pencil_sketch = cv2.divide(gray, inverted_blurred, scale=256.0)
cv2.imwrite(f"{path}\\{img}(final).png", pencil_sketch)
print()
print(f'You can find the image here: {path}\\{img}(final).png')
def rgb_to_sketch(pic_name):
#img_rgb = cv2.imread(args["image"])
img_rgb = cv2.imread(pic_name)
#print(img_rgb.shape)
img_gray = cv2.cvtColor(img_rgb, cv2.COLOR_BGR2GRAY) ##转为灰度图
##可改变图片的尺寸，只设置h或者只设置w就会按照等比例放大或缩小；若都指定，则按照指定的大小变换
img_gray = myutils.resize(img_gray, height=500)
img_blur = cv2.GaussianBlur(img_gray, ksize=(21, 21), sigmaX=0,
sigmaY=0) ##高斯滤波
##可改变scale的值来改变生成效果，scale越小，会让一些原本比较亮的区域变得更加清晰
img_blend = cv2.divide(img_gray, img_blur, scale=225) ##图像相除实现素描效果
return img_blend
def Convert(sketch):
#Read the image which will be in gray already
img = cv2.imread('portrait.png')
#Invert the grayscaled image
inv_gray_image = 255 - img
#Blurr the image
Blurred_image = cv2.GaussianBlur(inv_gray_image, (21, 21), 0)
#Invert the blurred image
inv_blur = 255 - Blurred_image
#Divide the original gray image with the inverted blurred image and put in a variable
sketch = cv2.divide(img, inv_blur, scale=256)
#Return the variable
return sketch
def img_calc(img1, img2, method):
if method == "add":
return cv.add(img1, img2)
elif method == "sub":
return cv.subtract(img1, img2)
elif method == "multi":
return cv.multiply(img1, img2)
elif method == "divide":
return cv.divide(img1, img2)
elif method == "and":
return cv.bitwise_and(img1, img2)
elif method == "or":
return cv.bitwise_or(img1, img2)
elif method == "not":
return cv.bitwise_not(img1, img2)
else:
return False
def dodgeV2(image, mask):
# inverting color with 255 - ...
return cv2.divide(image, 255 - mask, scale=256)
def divide_demo(m1, m2): #除法
dst = cv.divide(m1, m2)
cv.imshow("divide result", dst)
def divide_demo(m1, m2): # 两张图片需要同样大
dst = cv.divide(m1, m2)
cv.imshow("divide_demo", dst)
import numpy as np
from cv2 import cv2 as cv
img = cv.imread('Images/Victor.png')
# Convert to gray scale
gray_image = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
# Invert the image
inv_gray_image = 255 - gray_image
# Blur the Image
Blurred_image = cv.GaussianBlur(inv_gray_image, (21, 21), 0)
# invert the blurred image
inv_blur = 255 - Blurred_image
sketch = cv.divide(gray_image, inv_blur, scale=256)
# Edge Cascade
canny = cv.Canny(img, )
imagem = cv.bitwise_not(canny)
cv.imshow('canny edges', imagem)
# Show the images
cv.imshow('Image', img)
#cv.imshow('Gray image', gray_image)
cv.imshow('Sketch', sketch)
cv.waitKey(0)
cv.destroyAllWindows()