Example with 3 images:
When this URL is provided, one of possible outcomes:
http://localhost:8080/mozaika?losowo=1&rozdzielczosc=512x512&zdjecia=https://www.humanesociety.org/sites/default/files/styles/768x326/public/2018/08/kitten-440379.jpg?h=f6a7b1af&itok=vU0J0uZR,https://cdn.britannica.com/67/197567-131-1645A26E.jpg,https://images.unsplash.com/photo-1518791841217-8f162f1e1131?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&w=1000&q=80
Required libraries: http.server, numpy, opencv-python
Run server.py
In your browser type: http://localhost:8080/mozaika?losowo=Z&rozdzielczosc=XxY&zdjecia=URL1,URL2,URL3...
where:
losowo- optional parameter, if Z = 1 images places are random.rozdzielczosc- optional parameter, defines width and height. Default is 2048x2048URL1,URL2,URL3...image addresses, 1 to 9.(or copy the link above).
import cv2
import numpy as np
import random
from math import ceil
class Mozaika:
"""Class Mozaika takes 1 required attribute: list of images in cv2 format,
3 optional attributes: random image positioning, width of output image, height of output image.
Output image is stored in variable 'output_image'.
Class is looking for the least proportional image and returns it in (0,0) - top left corner if no random positioning"""
def __init__(self, image_list, losowo, w=2048, h=2048):
self.losowo = losowo # defines whether image position is random
self.w = int(w) # width of output image
self.h = int(h) # height of output image
self.output_image = 0
# variables are stored in 3 lists: image_names for sorted name strings, image_list for image in cv2 format,
# image_dict for height and width for every image
self.image_names = [] # Names of images
self.image_list = image_list # list of files (images)
if self.losowo == 1:
random.shuffle(self.image_list)
for i in range(len(self.image_list)):
self.image_names.append(f"img{i}")
self.image_dict = {}
for image in range(len(self.image_list)):
key = self.image_names[image]
h, w = self.image_list[image].shape[:2] # height, width of each image
self.image_dict[key] = [h, w]
self.how_many_images()
def how_many_images(self):
number_of_images = len(self.image_dict) # checks how many images is given
if number_of_images == 1:
self.make_square()
self.resize_huge_image()
elif number_of_images == 2:
self.rectangle_image(2)
elif number_of_images == 3 or number_of_images == 4:
self.grid2x2()
elif number_of_images > 4:
self.grid3x3()
def rectangle_image(self, images=1): # the least proportional image will become a rectangle
ratios = []
self.check_ratio()
ratios = [e[2] for e in list(self.image_dict.values())] # getting image ratio(s)
max_ratio = max(ratios)
for name, value in self.image_dict.items(): # finding highest/longest image
if value[2] == max_ratio:
name_max = name
list_index_max = self.image_names.index(name)
if images == 1: # method is called for 1 image
if self.image_dict[name_max][1] > self.image_dict[name_max][0]: # checks if width or height of the image is greater
return self.make_horizontal_rectangle(name_max, list_index_max, max_ratio), 0, name_max # return image, horizontal/vertical, name of image
elif self.image_dict[name_max][1] < self.image_dict[name_max][0]:
return self.make_vertical_rectangle(name_max, list_index_max, max_ratio), 1, name_max
elif images == 2: #it will only work if there are 2 images, creates mosaic of 2 images
i = 0
if self.image_dict[name_max][1] > self.image_dict[name_max][0]:
for name, value in self.image_dict.items(): # checks ratio the least proportional image and decides
self.make_horizontal_rectangle(name, i, value[2]) # whether images should be vertical or horizontal
i += 1
self.merge_two_images_horizontally() # merge 2 images with minimum quality loss
elif self.image_dict[name_max][1] < self.image_dict[name_max][0]:
for name, value in self.image_dict.items():
self.make_vertical_rectangle(name, i, value[2])
i += 1
self.merge_two_images_vertically()
def check_ratio(self):
# appends to dictionary height to width (or width to height) ratio
i = 0
for image in self.image_dict:
if self.image_dict[image][0] > self.image_dict[image][1]:
ratio = self.image_dict[image][0]/self.image_dict[image][1]
else:
ratio = self.image_dict[image][1]/self.image_dict[image][0]
self.image_dict[image].append(ratio)
def make_square(self):
# centralizes picture and cuts it so it becomes a square
i = 0
for image in self.image_dict.values(): # check in dictionary for width/height
if image[0] > image[1]:
cut = int((image[0] - image[1])/2)
self.image_list[i] = self.image_list[i][cut : -cut, :image[1]] # numpy operation on image
elif image[0] < image[1]:
cut = int((image[1] - image[0])/2)
self.image_list[i] = self.image_list[i][:image[0], cut : -cut]
i += 1
def make_horizontal_rectangle(self, name, list_index, ratio):
# if ratio == 2, it's perfect rectangle. Otherwise it is cut to this ratio
if ratio < 2:
cut = int( (self.image_dict[name][0] - (self.image_dict[name][0] / (2/ratio)))/2 )
return self.image_list[list_index][cut : -cut, : self.image_dict[name][1]]
elif ratio > 2:
if self.image_dict[name][1] > self.image_dict[name][0]:
cut = int( (self.image_dict[name][0] - (self.image_dict[name][0] / (ratio/2)))/2 )
return self.image_list[list_index][: self.image_dict[name][0], cut : -cut]
def make_vertical_rectangle(self, name, list_index, ratio):
if ratio < 2:
cut = int( (self.image_dict[name][1] - (self.image_dict[name][1] / (2/ratio)))/2 )
return self.image_list[list_index][: self.image_dict[name][0], cut : -cut]
elif ratio > 2:
cut = int( (self.image_dict[name][1] - (self.image_dict[name][1] / (ratio/2)))/2 )
return self.image_list[list_index][cut : -cut, : self.image_dict[name][1]]
def merge_two_images_horizontally(self):
# method takes 2 horizontal images and merges them
self.image_list[0] = cv2.resize(self.image_list[0], (self.w, int(self.h/2)))
self.image_list[1] = cv2.resize(self.image_list[1], (self.w, int(self.h/2)))
self.output_image = np.concatenate((self.image_list[0], self.image_list[1]), axis=0)
def merge_two_images_vertically(self):
# method takes 2 vertical images and merges them
self.image_list[0] = cv2.resize(self.image_list[0], (int(self.w/2), self.h))
self.image_list[1] = cv2.resize(self.image_list[1], (int(self.w/2), self.h))
self.output_image = np.concatenate((self.image_list[0], self.image_list[1]), axis=1)
def resize_huge_image(self):
# returns one image of the size of the output image
self.output_image = cv2.resize(self.image_list[0], (self.w, self.h))
def resize_big_image(self, index):
# returns one image of 2/3 width/height of the output image
name = self.image_names[index]
return cv2.resize(self.image_list[index], (int(self.w/(3/2)), int(self.h/(3/2)))), name
def resize_medium_image(self, index):
# returns one image of 1/2 width/height of the output image
return cv2.resize(self.image_list[index], (int(self.w/2), int(self.h/2)))
def resize_small_image(self, index):
# returns one image of 1/3 width/height of the output image
return cv2.resize(self.image_list[index], (int(self.w/3), int(self.h/3)))
def grid2x2(self):
placement = self.put_image2x2() # defines where to put images
decrease_h = ceil(2*(self.h/2 - int(self.h/2))) # decrease size of output image due to roundings, so there are no black spaces
decrease_w = ceil(2*(self.w/2 - int(self.w/2)))
vis = np.zeros((self.h - decrease_h, self.w - decrease_w, 3), np.uint8) # smaller image due to roundings
num = 0
for i in range(0,2): # grid 2x2, so 4 squares to fill
for k in range(0,2):
vis[i*int(self.h/2) : (i+1)*int(self.h/2), k*int(self.w/2) : (k+1)*int(self.w/2)] = placement[num]
num += 1
self.output_image = cv2.resize(vis, (self.w, self.h)) # optional, scales image to match requirements accurately
def grid3x3(self):
placement = self.put_image3x3() # defines where to put images
decrease_h = ceil(3*(self.h/3 - int(self.h/3))) # decrease size of output image due to roundings, so there are no black spaces
decrease_w = ceil(3*(self.w/3 - int(self.w/3)))
vis = np.zeros((self.h - decrease_h, self.w - decrease_w, 3), np.uint8) # smaller image due to roundings
num = 0
for i in range(0,3): # grid 3x3, so nine squares to fill
for k in range(0,3):
vis[i*int(self.h/3) : (i+1)*int(self.h/3), k*int(self.w/3) : (k+1)*int(self.w/3)] = placement[num]
num += 1
self.output_image = cv2.resize(vis, (self.w, self.h)) # optional, scales image to match requirements accurately
def put_image2x2(self):
placement = [0]*4 # it'll store images
if len(self.image_names) == 3: # to do if there are 3 images
rect_image, vertical, name = self.rectangle_image()
index = self.image_names.index(name)
self.image_list.pop(index) # deleting rectangle image from image_list, so there will be no duplicates
other_position = [e for e in range(4)] # 4 possibilities to put 1 image
if vertical: # 1 vertical image
rect_image = cv2.resize(rect_image, (int(self.w/2), self.h))
if self.losowo == 1:
position = random.randrange(0,2) # choose random position for image
else:
position = 0 # or fixed position
other_position.remove(position) # rectangle image takes 2 places
other_position.remove(position + 2)
placement[position] = rect_image[:int(self.h/2), :int(self.w/2)]
placement[position + 2] = rect_image[int(self.h/2):self.h, :int(self.w/2)]
else: # 1 horizontal image
rect_image = cv2.resize(rect_image, (self.w, int(self.h/2)))
if self.losowo == 1:
position = random.randrange(0,3,2) # possible positions are top left and bottom left
else:
position = 0
other_position.remove(position)
other_position.remove(position + 1)
placement[position] = rect_image[:int(self.h/2), :int(self.w/2)]
placement[position + 1] = rect_image[:int(self.h/2), int(self.w/2):self.w]
num = 0
for i in other_position: # after puting bigger image fill other places with smalles images
placement[i] = self.resize_medium_image(num)
num += 1
else: # 4 images
for i in range(len(self.image_list)):
placement[i] = self.resize_medium_image(i) # fill 4 places with medium images
return placement
def put_image3x3(self):
placement = [0]*9
img2x = [] # list of rectangle images
img4x = [] # list of big square images
num_img = len(self.image_names)
var = 0
var1 = 0
while num_img < 9:
if 9 - num_img < 3: # big image can't fit, increase number of takes space by making rectangles
img2x.append(self.rectangle_image())
remove_image = img2x[var][2] # get image name
self.image_dict.pop(remove_image) # delete image to avoid duplicates (there are 3 places where it is)
index = self.image_names.index(remove_image)
self.image_names.remove(remove_image)
self.image_list.pop(index)
num_img += 1
var += 1
else:
img4x.append(self.resize_big_image(0))
remove_image = img4x[var1][1] # get image name
self.image_dict.pop(remove_image) # delete image to avoid duplicates
index = self.image_names.index(remove_image)
self.image_names.remove(remove_image)
self.image_list.pop(index)
var1 += 1
num_img += 3
biash = ceil(self.h*(2/3) - int(self.h*(2/3))) # image can be to big to fit in square, need to decrease it
biasw = ceil(self.w*(2/3) - int(self.w*(2/3)))
other_position = set([e for e in range(9)]) # 9 possible places for one image
for img in img4x: # takes big image and tries to fit it
square_img = img[0]
other_position, position = self.find_big_position(other_position) # find possible position
placement[position] = square_img[:int(self.h/3), :int(self.w/3)] # top left corner of the image
placement[position + 1] = square_img[:int(self.h/3), int(self.w/3):int(self.w*(2/3)) - biasw] # top right corner
placement[position + 3] = square_img[int(self.h/3):int(self.h*(2/3)) - biash, :int(self.w/3)] # bottom left corner
placement[position + 4] = square_img[int(self.h/3):int(self.h*(2/3)) - biash, int(self.w/3):int(self.w*(2/3)) - biasw] # bottom right corner
for img in img2x: # takes rectangles and tries to fit them
rect_image, vertical = img[:2] # check if rectangle is vertical
if vertical:
rect_image = cv2.resize(rect_image, (int(self.w/3), int(self.h*(2/3))))
other_position, position = self.find_vertical_position(other_position) # checks for vertical possibilities
placement[position] = rect_image[:int(self.h/3), :int(self.w/3)]
placement[position + 3] = rect_image[int(self.h/3):int(self.h*(2/3)) - biash, :int(self.w/3)]
else:
rect_image = cv2.resize(rect_image, (int(self.w*(2/3)), int(self.h/3)))
other_position, position = self.find_horizontal_position(other_position) # checks for horizontal possibilities
placement[position] = rect_image[:int(self.h/3), :int(self.w/3)]
placement[position + 1] = rect_image[:int(self.h/3), int(self.w/3):int(self.w*(2/3)) - biasw]
num = 0
for i in other_position: # after puting bigger image fill other places with smaller images
placement[i] = self.resize_small_image(num)
num += 1
return placement
def find_big_position(self, avaiable_pos):
# find position for 2/3 width/height image
myList = avaiable_pos
mylistshifted=[x-1 for x in myList]
possible_position = [0,1,3,4] # only possible possisions for big image
intersection_set = list(set(myList) & set(mylistshifted) & set(possible_position))
if self.losowo == 1:
position = random.choice(intersection_set)
else:
position = intersection_set[0]
myList.remove(position) # removes places from other_position, so no other image can take these places
myList.remove(position + 1)
myList.remove(position + 3)
myList.remove(position + 4)
return myList, position
def find_horizontal_position(self, avaiable_pos):
# find position for horizontal rectangle image
myList = avaiable_pos
mylistshifted=[x-1 for x in myList]
possible_position = [0,1,3,4,6,7] # positions where image is not cut in half
intersection_set = list(set(myList) & set(mylistshifted) & set(possible_position))
if self.losowo == 1:
position = random.choice(intersection_set)
else:
position = intersection_set[0]
myList.remove(position) # removes places from other_position, so no other image can take these places
myList.remove(position + 1)
return myList, position
def find_vertical_position(self, avaiable_pos):
# find position vertical rectangle image
myList = avaiable_pos
mylistshifted=[x-3 for x in myList]
possible_position = [e for e in range(6)] # positions where image is not cut in half
intersection_set = list(set(myList) & set(mylistshifted) & set(possible_position))
if self.losowo == 1:
position = random.choice(intersection_set)
else:
position = intersection_set[0]
myList.remove(position) # removes places from other_position, so no other image can take these places
myList.remove(position + 3)
return myList, position
