karolzak

###################### unet ############################
from keras.models import Model
from keras.layers import *


def upsample_conv(filters, kernel_size, strides, padding):
    return Conv2DTranspose(filters, kernel_size, strides=strides, padding=padding)


def upsample_simple(filters, kernel_size, strides, padding):

karolzak

import numpy as np
import matplotlib.pyplot as plt


def mask_to_red(mask, img_size=1024):
    '''
    Converts binary segmentation mask from white to red color.
    Also adds alpha channel to make black background transparent.
    '''
    c1 = mask.reshape(img_size,img_size)

karolzak

def get_patches(img_arr, size=256, stride=256):
    '''
    Takes single image or array of images and returns
    crops using sliding window method.
    If stride < size it will do overlapping.
    '''
    # check size and stride
    if size % stride != 0: 
        raise ValueError('size % stride must be equal 0')