# -*- coding: utf-8 -*-
from MyHybridImages import myHybridImages
import matplotlib.pyplot as plt
import matplotlib.image as maping
if __name__=='__main__':
low_Image=maping.imread('dog.bmp')
high_Image=maping.imread('cat.bmp')
hybridImage=myHybridImages(low_Image,8,high_Image,4)
print(hybridImage)
plt.imshow(hybridImage)
plt.show()
# zll_image=maping.imread('IMG_2197.jpeg')
# print(zll_image.shape)
cat = np.array(Image.open("data/cat.bmp"))
dog = np.array(Image.open("data/dog.bmp"))
# high_cat = np.array(Image.open("data/high_frequencies.bmp"))
# low_dog = np.array(Image.open("data/low_frequencies.bmp"))
# notes_hybrid = np.array(Image.open("data/cat_hybrid_image_scales.bmp"))
# einstein = np.array(Image.open("data/einstein.bmp"))
# marilyn = np.array(Image.open("data/marilyn.bmp"))
donald = np.array(Image.open("data/Donald.bmp"))
kim = np.array(Image.open("data/kim_smile.bmp"))
brent = np.array(Image.open("data/hybrid_creation.bmp"))
# human = np.array(Image.open("data/human.bmp"))
# robot = np.array(Image.open("data/robot.bmp"))
# hybrid = myHybridImages(donald, 3, kim, 4)
# hybrid1 = resize(hybrid, (202, 190, 3))
# hybrid2 = resize(hybrid, (101, 95, 3))
# hybrid3 = resize(hybrid, (50, 47, 3))
# hybrid4 = resize(hybrid, (24, 25, 3))
#
test1 = myHybridImages(dog, 6, cat, 8)
img = Image.fromarray(test1)
img.show()
print(test1 == brent)
def hybrid(sigs):
sig1, sig2 = sigs
test = myHybridImages(im1, sig1, im2, sig2)
cv2.imwrite(str(file_dir / f'output/hybrid_{sig1}_{sig2}.png'), test)
import math
import numpy as np
from scipy import signal
from scipy import ndimage
import imageio
import matplotlib.pyplot as plt
from PIL import Image
import scipy.misc
from MyConvolution import convolve
from MyHybridImages import myHybridImages, makeGaussianKernel
img = imageio.imread('batman.PNG')
mix = imageio.imread('jocker.PNG')
res = myHybridImages(mix[:, :, 0:3], 9, img[:, :, 0:3], 9)
out = (res - res.min()) / (res.max() - res.min()) * 255
out = out.astype(np.uint8)
imageio.imwrite('test.png', out)
from scipy.ndimage import gaussian_filter
import cv2
from pathlib import Path
from itertools import permutations
from multiprocessing import Pool
from MyHybridImages import myHybridImages
file_dir = Path(__file__).resolve().parent
im1 = cv2.imread(str(file_dir / 'trump_real.png'))
im2 = cv2.imread(str(file_dir / 'trump_simpson.png'))
def hybrid(sigs):
sig1, sig2 = sigs
test = myHybridImages(im1, sig1, im2, sig2)
cv2.imwrite(str(file_dir / f'output/hybrid_{sig1}_{sig2}.png'), test)
# if __name__ == '__main__':
# with Pool(3) as p:
# p.map(hybrid, list(permutations(range(1, 21), 2)))
sig1, sig2 = 5, 6
test = myHybridImages(im1, sig1, im2, sig2)
cv2.imwrite(str(file_dir / f'hybrid_{sig1}_{sig2}.png'), test)