earth.py

from joblib import Parallel, delayed

import numpy as np
from skimage.transform import resize

files = list(data.keys())[1:]

def coords(filename):
    filename = filename.replace('11_1024/', '').replace('.jpg', '').replace('11_', '')
    filename = filename.replace('[','').replace(']','').split('_')
    x,y = filename[0].split('-'), filename[1].split('-')
    ix, iy = [int(x[0]),int(x[1])], [int(y[0]),int(y[1])]    
    return ix,iy

def paste(y, x, img, target, size):
    target[y*size:(y+1)*size, x*size:(x+1)*size, :] = img

count_x, count_y = 800, 500
    
size = 6

water = np.array((9/255,25/255,38/255)).reshape((1,1,3))
#target = np.zeros((count_y*size,count_x*size,3))
target = np.repeat(water, (count_y*size*count_x*size), axis=0).reshape((count_y*size,count_x*size,3))
print(target.shape)

def process_file(i):    
    file = files[i]    
    cx,cy = coords(file)
    xi, yi = cx[0]//size, cy[0]//size
    x = np.clip(np.asarray(Image.open( BytesIO(data[file]) )).reshape(1024,1024,3)/255,0,1)
    x_resized = resize(x, (size, size), preserve_range=True, mode='reflect', anti_aliasing=True)
    paste(yi, xi, x_resized, target, size)

Parallel(n_jobs=40,verbose=1, require='sharedmem')(delayed(process_file)(i) for i in range(len(files)))