-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathRGB_code
77 lines (57 loc) · 1.63 KB
/
RGB_code
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
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
# -*- coding: utf-8 -*-
"""
Spyder Editor
This is a temporary script file.
"""
import cv2
import numpy as np
import os
import sys
import time
def load_img_list(dataset):
if dataset == 'MSRA-B':
path = '/home/wj/wj/leftImg8bit/train/bochum'
elif dataset == 'HKU-IS':
path = 'dataset/HKU-IS/imgs'
elif dataset == 'DUT-OMRON':
path = 'dataset/DUT-OMRON/DUT-OMRON-image'
elif dataset == 'PASCAL-S':
path = 'dataset/PASCAL-S/pascal'
elif dataset == 'NTI':
path = 'dataset/NTI/images'
elif dataset == 'ECSSD':
path = 'dataset/ECSSD/images'
imgs = os.listdir(path)
return path, imgs
if __name__ == "__main__":
datasets = ['MSRA-B']
#['MSRA-B', 'HKU-IS', 'DUT-OMRON','PASCAL-S', 'ECSSD', 'NTI']
sumval=0
num=0
sumbiao=0
mx = 0
mn = 0
for dataset in datasets:
path, imgs = load_img_list(dataset)
for f_img in imgs:
num=num+1
img = cv2.imread(os.path.join(path, f_img))
w,h,s=img.shape
val = img.sum()/(w*h*s)
mx=mx+img.max()
mn=mn+img.min()
sumval=sumval+val
biao=0
for k in range(s):
for i in range(w):
for j in range(h):
biao=biao+abs(img.item(i,j,k)-val)
biao=biao/(w*h*s)
sumbiao=sumbiao+biao
print(val,biao)
mx=mx/num
mn=mn/num
sumval=sumval/num
sumbiao=sumbiao/num
print()
print(sumval,sumbiao,num)