Photo effects

Photo_Effects_Relplot_Seaborn_1.py

from PIL import Image
import numpy as np
import matplotlib.pyplot as pyplot
import pandas as pd
from datetime import datetime
import seaborn as sns

ini = datetime.now()

fle = "Cosmonaut" # File name

img  = Image.open("C:\\Users\\Rober\\Desktop\\"+fle+".png") # Works only with png files 

def conv(arr) : # convertion functions - treats the image array to be used in Seaborn scatteplot func.
    mtz = pd.DataFrame()

    XL = []
    YL = []
    SL = []

    for y in range(0,len(arr)) :
       for x in range(0,len(arr[0])) : 
          YL.append(y)
          XL.append(x)
          SL.append(arr[y][x])

    mtz["Y"] = XL
    mtz["X"] = YL
    mtz["S"] = SL
    
    return mtz


h = img.size[0]
v = img.size[1]

R,G,B = img.split()

s = 3 # size of the block(resolution) - smaller number equals to longer time processing 

rsizeArr_R = np.asarray(R.resize((int(h/s),int(v/s))))  # Red channel
rsizeArr_G = np.asarray(G.resize((int(h/s),int(v/s))))  # Green channel
rsizeArr_B = np.asarray(B.resize((int(h/s),int(v/s))))  # Blue channel

r = 100 # proportion, [higher/lower] number equals to [smaller/larger] image

bkg = "black" # background color
pyplot.rcParams['figure.facecolor']  = bkg
pyplot.rcParams['savefig.facecolor'] = bkg

fig, g = pyplot.subplots(figsize=(h/r,v/r))
pyplot.subplots_adjust(top = 1.00, left = 0.00, right = 1.00,  bottom = 0.00) 


g.axis("off")

#Calling the conversion function
Arr_r = conv(rsizeArr_R)
Arr_b = conv(rsizeArr_B)
Arr_g = conv(rsizeArr_G)


# 3 color plotting block

sz = (1,9) # minimum and maximum size of the marker
sns.scatterplot(x="Y", y="X",alpha = 0.99,
                     hue="S", size="S",legend = False,
                     palette="Oranges_r", sizes=sz,
                     data=Arr_r, marker = "8", edgecolor=None)

sz = (1,6)
sns.scatterplot(x="Y", y="X",alpha = 0.60,
                     hue="S", size="S",legend = False,
                     palette="Blues_r", sizes=sz,
                     data=Arr_b, marker = "8", edgecolor=None)

sz = (0.5,4)
sns.scatterplot(x="Y", y="X",alpha = 0.15,
                     hue="S", size="S",legend = False,
                     palette="Greens_r", sizes=sz,
                     data=Arr_g, marker = "8", edgecolor=None)


# This block was set to reproduce more or less the original image, but it is a trial and error process.
# The first color (red channel) has a stronger size marker range and alpha (transparency), the others : 
# the color after is plot on top of the previous one, so must be compensated.
#
# You can try other backgoung color, block size, palletes, sizes, markers, or even how many channels to 
# plot - the imagination is the limit.
#
# For reasosn that I do not know, the marker 's' (square) "leakes" over the plot so I avoid it. 
# 
# Put a time counting that might be useful when you test different resolutions (block sizes).


pyplot.grid(False) 
pyplot.ylim(int(v/s),-1) 
pyplot.xlim(-1,int(h/s)) 
pyplot.show()

fim = datetime.now()

print(fim-ini)