60 lines
2.0 KiB
Python
60 lines
2.0 KiB
Python
#!/usr/bin/env python
|
||
# -*- encoding: utf-8 -*-
|
||
'''
|
||
@File : affinity.py
|
||
@Contact : zpyovo@hotmail.com
|
||
@License : (C)Copyright 2018-2019, Lab501-TransferLearning-SCUT
|
||
@Description :
|
||
|
||
@Modify Time @Author @Version @Desciption
|
||
------------ ------- -------- -----------
|
||
2022/3/12 9:18 PM Pengyu Zhang 1.0 None
|
||
'''
|
||
|
||
from __future__ import absolute_import
|
||
from __future__ import division
|
||
from __future__ import print_function
|
||
import torch
|
||
import torch.nn.functional as F
|
||
import numpy as np
|
||
import cv2
|
||
def eightway_total_diff(arr):
|
||
# 对输入数组进行填充，每边填充1个元素
|
||
padded_arr = np.pad(arr, pad_width=1, mode='edge')
|
||
|
||
# 获取填充后数组的尺寸
|
||
h, w = padded_arr.shape
|
||
|
||
# 初始化输出数组，用于存储总差值
|
||
diff_array = np.zeros((h-2, w-2))
|
||
|
||
# 遍历每个元素（不包括填充的边界）
|
||
for y in range(1, h-1):
|
||
for x in range(1, w-1):
|
||
total_diff = 0 # 初始化当前元素的总差值
|
||
# 计算每个方向的差值
|
||
for dy in range(-1, 2):
|
||
for dx in range(-1, 2):
|
||
if dy == 0 and dx == 0:
|
||
# 排除中心点自身
|
||
continue
|
||
# 直接使用填充后的坐标计算差值
|
||
diff = abs(padded_arr[y, x] - padded_arr[y+dy, x+dx])
|
||
# 如果差值小于0，则置为0
|
||
total_diff += max(diff, 0)
|
||
# 将总差值存储在输出数组中
|
||
diff_array[y-1, x-1] = total_diff
|
||
return diff_array.astype(int)
|
||
|
||
def roi_affinity_siml(X_ter,X_str):
|
||
X_ter = np.array(X_ter)
|
||
X_str = np.array(X_str)
|
||
X_ter_diffs = eightway_total_diff(X_ter / X_ter.max())
|
||
X_str_diffs = eightway_total_diff(X_str / X_str.max())
|
||
# 计算差异
|
||
difference = cv2.absdiff(X_ter_diffs, X_str_diffs)
|
||
mean_diff = np.mean(difference)
|
||
# 计算相似度
|
||
similarity = max((1 - mean_diff) * 100, 0)
|
||
return similarity
|