blob: 8da5c5e99633404f5616d3b83adae1a634083863 (
plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
|
import numpy as np
from PIL import Image
class TiffReader(object):
def imread(self, filename):
return np.asarray(Image.open(filename))
###############################################################################
def printParametersToString(pars):
txt = r''
for key, value in pars.items():
if key == 'algorithm':
txt += "{0} = {1}".format(key, value.__name__)
elif key == 'input':
txt += "{0} = {1}".format(key, np.shape(value))
elif key == 'refdata':
txt += "{0} = {1}".format(key, np.shape(value))
else:
txt += "{0} = {1}".format(key, value)
txt += '\n'
return txt
def nrmse(im1, im2):
rmse = np.sqrt(np.sum((im2 - im1) ** 2) / float(im1.size))
max_val = max(np.max(im1), np.max(im2))
min_val = min(np.min(im1), np.min(im2))
return 1 - (rmse / (max_val - min_val))
def rmse(im1, im2):
rmse = np.sqrt(np.sum((im1 - im2) ** 2) / float(im1.size))
return rmse
###############################################################################
|