soravux

import cv2 

#from scipy.ndimage import gaussian_filter, uniform_filter
from cupyx.scipy.ndimage import gaussian_filter, uniform_filter
#import numpy as np
import cupy as np # don't laugh


# inspired by https://www.youtube.com/watch?v=X-iSQQgOd1A

soravux

soravux

import atexit
import time
import subprocess
from io import BytesIO

import PIL.Image
import numpy as np
from matplotlib import pyplot as plt

soravux

soravux

import numpy as np
from scipy.misc import imread, imsave

from matplotlib import pyplot as plt


# Get a linear version of the images
target_im = (imread("lighting_gt.png").astype('float32') / 255.)**2.2 # Poor man un-sRGB
source_im = (imread("warped_0150.png").astype('float32') / 255.)**2.2

soravux

from __future__ import print_function
import os
from tqdm import tqdm
import numpy as np
import argparse
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torchvision import datasets, transforms

soravux

#!/usr/bin/env python3


VERSION = "v0.2.0"

"""
Copyright (c) 2013 devunt
Permission is hereby granted, free of charge, to any person
obtaining a copy of this software and associated documentation
files (the "Software"), to deal in the Software without

soravux

import sys 
import csv 

import numpy as np
from scipy.misc import imread


output_file = 'sharpnesses.txt'
imgs = sys.argv[1:]

soravux

import tensorflow as tf

# To use : model.add(ResizeImage(<an input shape>))
# e.g.:    model.add(ResizeImage(model.layers[0].output_shape[1:3]))


class ResizeImage(Layer):
    def __init__(self, output_dim, **kwargs):
        self.output_dim = output_dim
        super().__init__(**kwargs)

soravux

Adding a bunny lit with an environment map to a background using Blender's Cycles renderer.