From e8506d069a37e8fd73dcd2ea2cc479a012631688 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E8=92=8B=E8=8B=A5=E6=84=9A?= <1846536882@qq.com>
Date: Fri, 11 Nov 2022 13:31:39 +0800
Subject: [PATCH] =?UTF-8?q?=E5=88=A0=E9=99=A4=20'plugins/filter=5Fcollecti?=
 =?UTF-8?q?on/bilater.py'?=
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---
 plugins/filter_collection/bilater.py | 135 ---------------------------
 1 file changed, 135 deletions(-)
 delete mode 100644 plugins/filter_collection/bilater.py

diff --git a/plugins/filter_collection/bilater.py b/plugins/filter_collection/bilater.py
deleted file mode 100644
index 498337d..0000000
--- a/plugins/filter_collection/bilater.py
+++ /dev/null
@@ -1,135 +0,0 @@
-# from misc import AlgFrontend
-# from osgeo import gdal, gdal_array
-# from skimage.filters import rank
-# from skimage.morphology import  rectangle
-# from filter_collection import FILTER
-# from PyQt5.QtWidgets import QDialog, QAction
-# from PyQt5 import QtCore, QtGui, QtWidgets
-# from rscder.utils.project import PairLayer, Project, RasterLayer, ResultPointLayer
-# import os
-# from datetime import datetime
-
-
-
-# import cv2 as cv
-# import numpy as np
-
-# cv.namedWindow("image")
-# #d表示滤波窗口的直径
-# #sigmaSpace表示空间域方差，以及边缘处理方式
-# #sigmaColor表示像素域方差
-# cv.createTrackbar("d","image",0,255,print)
-# cv.createTrackbar("sigmaColor","image",0,255,print)
-# cv.createTrackbar("sigmaSpace","image",0,255,print)
-# img = cv.imread("test-data/BBB.tif",0)
-# while(1):
-#       d = cv.getTrackbarPos("d","image")
-#       sigmaColor = cv.getTrackbarPos("sigmaColor","image")
-#       sigmaSpace = cv.getTrackbarPos("sigmaSpace","image")
-#       result_img = cv.bilateralFilter(img,d,sigmaColor,sigmaSpace)
-#       cv.imshow("result",result_img)
-#       k = cv.waitKey(1) & 0xFF
-#       if k ==27:
-#          break
-# cv.destroyAllWindows()
-
-
-
-import os
-import cv2
-import numpy as np
-
-def BilateralFilter_11(img_path='test-data/BBB.tif'):
-    img_src=cv2.imread(img_path)
-    img=cv2.resize(src=img_src,dsize=(1020,1020))
-    img=cv2.bilateralFilter(img,5,110,110)
-    cv2.imshow('img',img)
-    cv2.imshow('img_src',img_src)
-    cv2.waitKey(0)
-    cv2.destroyAllWindows()
-
-
-# def detectBilateralFilter():
-#     cap=cv2.VideoCapture(0)
-#     while cap.isOpened():
-#         OK,frame=cap.read()
-#         img_src = cv2.imread(frame)
-#         img = cv2.resize(src=img_src, dsize=(450, 450))
-#         img = cv2.bilateralFilter(img, 10, 150, 150)
-#         cv2.imshow('img', img)
-#         if cv2.waitKey(1)&0XFF==27:
-#             break
-#     cap.release()
-#     cv2.destroyAllWindows()
-
-if __name__ == '__main__':
-    print('Pycharm')
-#     BilateralFilter_11()
-#     detectBilateralFilter()
-    BilateralFilter_11()
-
-
-
-
-#
-
-
-
-# import numpy as np
-# from scipy import signal
-# import cv2
-# import random
-# import math
-# #双边滤波
-
-
-# def getClosenessWeight(sigma_g,H,W):
-#     r,c=np.mgrid[0:H:1,0:W:1]
-#     r -= (H - 1) // 2
-#     c -= int(W - 1) // 2
-#     closeWeight=np.exp(-0.5*(np.power(r,2)+np.power(c,2))/math.pow(sigma_g,2))
-#     return closeWeight
-
-# def bfltGray(I,H,W,sigma_g,sigma_d):
-#     #构建空间距离权重模板
-#     closenessWeight=getClosenessWeight(sigma_g,H,W)
-#     #模板的中心点位置
-#     cH = (H - 1) // 2 #//表示整数除法
-#     cW = (W - 1) // 2
-#     #图像矩阵的行数和列数
-#     rows,cols=I.shape
-#     #双边滤波后的结果
-#     bfltGrayImage=np.zeros(I.shape,np.float32)
-#     for r in range(rows):
-#         for c in range(cols):
-#             pixel=I[r][c]
-#             #判断边界
-#             rTop=0 if r-cH<0 else r-cH
-#             rBottom=rows-1 if r+cH>rows-1 else r+cH
-#             cLeft=0 if c-cW<0 else c-cW
-#             cRight=cols-1 if c+cW>cols-1 else c+cW
-#             # 权重模板作用的区域
-#             region=I[rTop:rBottom+1,cLeft:cRight+1]
-#             #构建灰度值相似性的权重因子
-#             similarityWeightTemp=np.exp(-0.5*np.power(region-pixel,2.0)/math.pow(sigma_d,2))
-#             #similarityWeightTemp = np.exp(-0.5 * np.power(region - pixel, 2.0) / math.pow(sigma_d, 2))
-#             closenessWeightTemp=closenessWeight[rTop-r+cH:rBottom-r+cH+1,cLeft-c+cW:cRight-c+cW+1]
-#             #两个权重模板相乘
-#             weightTemp=similarityWeightTemp*closenessWeightTemp
-#             #归一化权重模板
-#             weightTemp=weightTemp/np.sum(weightTemp)
-#             #权重模板和对应的领域值相乘求和
-#             bfltGrayImage[r][c]=np.sum(region*weightTemp)
-#     return bfltGrayImage
-
-
-# if __name__=='__main__':   ##启动语句
-#     a= cv2.imread('test-data/BBB.tif', cv2.IMREAD_UNCHANGED)  # 路径名中不能有中文，会出错,cv2.
-#     image1 = cv2.split(a)[0]#蓝通道
-#     cv2.imshow("image1",image1)
-#     image1=image1/255.0
-#     #双边滤波
-#     bfltImage=bfltGray(image1,3,3,19,0.2)
-#     cv2.imshow("增强后图",bfltImage)
-#     cv2.waitKey(0)
-#     cv2.destroyAllWindows()