filter
This commit is contained in:
parent
80dc7781e3
commit
84d888dc07
4
ECD.py
4
ECD.py
@ -1,8 +1,8 @@
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import os
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import sys
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'libs'))
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os.environ['PROJ_LIB'] = os.path.join(os.path.dirname(__file__), 'share/proj')
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os.environ['GDAL_DATA'] = os.path.join(os.path.dirname(__file__), 'share')
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# os.environ['PROJ_LIB'] = os.path.join(os.path.dirname(__file__), 'share/proj')
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# os.environ['GDAL_DATA'] = os.path.join(os.path.dirname(__file__), 'share')
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os.environ['ECD_BASEDIR'] = os.path.dirname(__file__)
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BASE_DIR = os.path.dirname(__file__)
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from rscder import MulStart
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@ -1 +1 @@
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vd4FiYncytyziGH9GNCAA8hGGr1/79Xmphtc5+PHPJDpxvqj1hP7+985QMojYO4M5Qn/aqEAvFgeDN3CA8x1YAK8SdCgSXSBJpRBK8wqPQjBY1ak96QfdPCrTLunr+xuPxK3Gxe772adTTsee2+ot7WePYUsC4y4NcS5+rlP1if87xtYqVeSwx3c64cOmAGP
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wd1l4X/jr1cgW76fh50mc7p7gK2TwB6Mmn5Pcgdo3xJFxcfLcDFFQP5t0OpPv9oLnDe2zLQtNmjLkdTI3dwx4iQnBkfBeYX6/2V2A3Y1fzOVR35NoDNIhsu7qH7XD76gpyI20cRA6K4EKvIUMFwaVRBJjT7j6uJn74X4MtcixBhTvHJKrLzTF2AXDcSDyEVz
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@ -3,4 +3,6 @@ from misc import Register
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FILTER = Register('滤波处理算法')
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from .mean_filter import MeanFilter
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from filter_collection.main import *
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from filter_collection.main import *
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from .morphology_filter import MorphologyFilter
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from .bilater_filter import BilaterFilter
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135
plugins/filter_collection/bilater.py
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135
plugins/filter_collection/bilater.py
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@ -0,0 +1,135 @@
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# from misc import AlgFrontend
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# from osgeo import gdal, gdal_array
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# from skimage.filters import rank
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# from skimage.morphology import rectangle
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# from filter_collection import FILTER
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# from PyQt5.QtWidgets import QDialog, QAction
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# from PyQt5 import QtCore, QtGui, QtWidgets
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# from rscder.utils.project import PairLayer, Project, RasterLayer, ResultPointLayer
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# import os
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# from datetime import datetime
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# import cv2 as cv
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# import numpy as np
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# cv.namedWindow("image")
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# #d表示滤波窗口的直径
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# #sigmaSpace表示空间域方差,以及边缘处理方式
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# #sigmaColor表示像素域方差
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# cv.createTrackbar("d","image",0,255,print)
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# cv.createTrackbar("sigmaColor","image",0,255,print)
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# cv.createTrackbar("sigmaSpace","image",0,255,print)
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# img = cv.imread("test-data/BBB.tif",0)
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# while(1):
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# d = cv.getTrackbarPos("d","image")
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# sigmaColor = cv.getTrackbarPos("sigmaColor","image")
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# sigmaSpace = cv.getTrackbarPos("sigmaSpace","image")
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# result_img = cv.bilateralFilter(img,d,sigmaColor,sigmaSpace)
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# cv.imshow("result",result_img)
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# k = cv.waitKey(1) & 0xFF
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# if k ==27:
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# break
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# cv.destroyAllWindows()
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import os
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import cv2
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import numpy as np
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def BilateralFilter_11(img_path='test-data/BBB.tif'):
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img_src=cv2.imread(img_path)
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img=cv2.resize(src=img_src,dsize=(1020,1020))
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img=cv2.bilateralFilter(img,5,110,110)
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cv2.imshow('img',img)
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cv2.imshow('img_src',img_src)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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# def detectBilateralFilter():
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# cap=cv2.VideoCapture(0)
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# while cap.isOpened():
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# OK,frame=cap.read()
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# img_src = cv2.imread(frame)
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# img = cv2.resize(src=img_src, dsize=(450, 450))
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# img = cv2.bilateralFilter(img, 10, 150, 150)
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# cv2.imshow('img', img)
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# if cv2.waitKey(1)&0XFF==27:
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# break
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# cap.release()
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# cv2.destroyAllWindows()
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if __name__ == '__main__':
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print('Pycharm')
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# BilateralFilter_11()
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# detectBilateralFilter()
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BilateralFilter_11()
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#
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# import numpy as np
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# from scipy import signal
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# import cv2
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# import random
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# import math
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# #双边滤波
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# def getClosenessWeight(sigma_g,H,W):
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# r,c=np.mgrid[0:H:1,0:W:1]
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# r -= (H - 1) // 2
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# c -= int(W - 1) // 2
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# closeWeight=np.exp(-0.5*(np.power(r,2)+np.power(c,2))/math.pow(sigma_g,2))
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# return closeWeight
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# def bfltGray(I,H,W,sigma_g,sigma_d):
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# #构建空间距离权重模板
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# closenessWeight=getClosenessWeight(sigma_g,H,W)
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# #模板的中心点位置
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# cH = (H - 1) // 2 #//表示整数除法
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# cW = (W - 1) // 2
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# #图像矩阵的行数和列数
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# rows,cols=I.shape
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# #双边滤波后的结果
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# bfltGrayImage=np.zeros(I.shape,np.float32)
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# for r in range(rows):
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# for c in range(cols):
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# pixel=I[r][c]
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# #判断边界
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# rTop=0 if r-cH<0 else r-cH
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# rBottom=rows-1 if r+cH>rows-1 else r+cH
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# cLeft=0 if c-cW<0 else c-cW
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# cRight=cols-1 if c+cW>cols-1 else c+cW
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# # 权重模板作用的区域
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# region=I[rTop:rBottom+1,cLeft:cRight+1]
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# #构建灰度值相似性的权重因子
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# similarityWeightTemp=np.exp(-0.5*np.power(region-pixel,2.0)/math.pow(sigma_d,2))
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# #similarityWeightTemp = np.exp(-0.5 * np.power(region - pixel, 2.0) / math.pow(sigma_d, 2))
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# closenessWeightTemp=closenessWeight[rTop-r+cH:rBottom-r+cH+1,cLeft-c+cW:cRight-c+cW+1]
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# #两个权重模板相乘
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# weightTemp=similarityWeightTemp*closenessWeightTemp
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# #归一化权重模板
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# weightTemp=weightTemp/np.sum(weightTemp)
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# #权重模板和对应的领域值相乘求和
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# bfltGrayImage[r][c]=np.sum(region*weightTemp)
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# return bfltGrayImage
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# if __name__=='__main__': ##启动语句
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# a= cv2.imread('test-data/BBB.tif', cv2.IMREAD_UNCHANGED) # 路径名中不能有中文,会出错,cv2.
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# image1 = cv2.split(a)[0]#蓝通道
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# cv2.imshow("image1",image1)
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# image1=image1/255.0
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# #双边滤波
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# bfltImage=bfltGray(image1,3,3,19,0.2)
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# cv2.imshow("增强后图",bfltImage)
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# cv2.waitKey(0)
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# cv2.destroyAllWindows()
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@ -9,3 +9,89 @@ from rscder.utils.project import PairLayer, Project, RasterLayer, ResultPointLay
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import os
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from datetime import datetime
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@FILTER.register
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class BilaterFilter(AlgFrontend):
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@staticmethod
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def get_name():
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return '双边滤波'
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@staticmethod
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def get_icon():
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return None
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@staticmethod
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def get_widget(parent=None):
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widget = QtWidgets.QWidget(parent)
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x_size_input = QtWidgets.QLineEdit(widget)
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x_size_input.setText('3')
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x_size_input.setValidator(QtGui.QIntValidator())
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x_size_input.setObjectName('xinput')
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y_size_input = QtWidgets.QLineEdit(widget)
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y_size_input.setValidator(QtGui.QIntValidator())
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y_size_input.setObjectName('yinput')
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y_size_input.setText('3')
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size_label = QtWidgets.QLabel(widget)
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size_label.setText('窗口大小:')
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time_label = QtWidgets.QLabel(widget)
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time_label.setText('X')
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hlayout1 = QtWidgets.QHBoxLayout()
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hlayout1.addWidget(size_label)
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hlayout1.addWidget(x_size_input)
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hlayout1.addWidget(time_label)
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hlayout1.addWidget(y_size_input)
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widget.setLayout(hlayout1)
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return widget
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@staticmethod
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def get_params(widget:QtWidgets.QWidget=None):
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if widget is None:
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return dict(x_size=3, y_size=3)
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x_input = widget.findChild(QtWidgets.QLineEdit, 'xinput')
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y_input = widget.findChild(QtWidgets.QLineEdit, 'yinput')
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if x_input is None or y_input is None:
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return dict(x_size=3, y_size=3)
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x_size = int(x_input.text())
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y_size = int(y_input.text())
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return dict(x_size=x_size, y_size=y_size)
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@staticmethod
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def run_alg(pth, x_size, y_size, *args, **kargs):
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x_size = int(x_size)
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y_size = int(y_size)
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# pth = layer.path
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if pth is None:
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return
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ds = gdal.Open(pth)
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band_count = ds.RasterCount
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out_path = os.path.join(Project().other_path, 'bilater_filter_{}.tif'.format(int(datetime.now().timestamp() * 1000)))
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out_ds = gdal.GetDriverByName('GTiff').Create(out_path, ds.RasterXSize, ds.RasterYSize, band_count, ds.GetRasterBand(1).DataType)
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out_ds.SetProjection(ds.GetProjection())
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out_ds.SetGeoTransform(ds.GetGeoTransform())
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import cv2
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for i in range(band_count):
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band = ds.GetRasterBand(i+1)
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data = band.ReadAsArray()
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#进行双边滤波处理cv2.bilateralFilter(影像,滤波窗口直径(0-255),像素域方差(0-255),空间域方差(0-255))
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data=cv2.bilateralFilter(data,6,50,50)
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out_band = out_ds.GetRasterBand(i+1)
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out_band.WriteArray(data)
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out_ds.FlushCache()
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del out_ds
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del ds
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return out_path
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@ -82,12 +82,18 @@ class MainPlugin(BasicPlugin):
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for key in FILTER.keys():
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alg:AlgFrontend = FILTER[key]
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name = alg.get_name() or key
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action = QAction(alg.get_icon(), name, self.mainwindow)
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action = QAction(name, self.mainwindow)
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func = functools.partial(self.run, key)
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action.triggered.connect(func)
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toolbar.addAction(action)
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ActionManager().filter_menu.addAction(action)
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# def set_action(self):
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# self.action = QAction(IconInstance().VECTOR, '均值滤波', self.mainwindow)
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# self.action.triggered.connect(self.run)
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# ActionManager().filter_menu.addAction(self.action)
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# self.alg_ok.connect(self.alg_oked)
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# self.action = QAction('均值滤波', self.mainwindow)
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# # self.action.setCheckable)
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@ -96,6 +102,8 @@ class MainPlugin(BasicPlugin):
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# ActionManager().filter_menu.addAction(self.action)
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# self.alg_ok.connect(self.alg_oked)
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# basic
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def alg_oked(self, parent, layer:RasterLayer):
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parent.add_result_layer(layer)
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99
plugins/filter_collection/morphology_filter.py
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99
plugins/filter_collection/morphology_filter.py
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from misc import AlgFrontend
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from osgeo import gdal, gdal_array
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from skimage.filters import rank
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from skimage.morphology import rectangle
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from filter_collection import FILTER
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from PyQt5.QtWidgets import QDialog, QAction
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from PyQt5 import QtCore, QtGui, QtWidgets
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from rscder.utils.project import PairLayer, Project, RasterLayer, ResultPointLayer
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import os
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from datetime import datetime
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@FILTER.register
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class MorphologyFilter(AlgFrontend):
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@staticmethod
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def get_name():
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return '形态学滤波'
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@staticmethod
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def get_icon():
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return None
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@staticmethod
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def get_widget(parent=None):
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widget = QtWidgets.QWidget(parent)
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x_size_input = QtWidgets.QLineEdit(widget)
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x_size_input.setText('3')
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x_size_input.setValidator(QtGui.QIntValidator())
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x_size_input.setObjectName('xinput')
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y_size_input = QtWidgets.QLineEdit(widget)
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y_size_input.setValidator(QtGui.QIntValidator())
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y_size_input.setObjectName('yinput')
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y_size_input.setText('3')
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size_label = QtWidgets.QLabel(widget)
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size_label.setText('窗口大小:')
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time_label = QtWidgets.QLabel(widget)
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time_label.setText('X')
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hlayout1 = QtWidgets.QHBoxLayout()
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hlayout1.addWidget(size_label)
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hlayout1.addWidget(x_size_input)
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hlayout1.addWidget(time_label)
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hlayout1.addWidget(y_size_input)
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widget.setLayout(hlayout1)
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return widget
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@staticmethod
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def get_params(widget:QtWidgets.QWidget=None):
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if widget is None:
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return dict(x_size=3, y_size=3)
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x_input = widget.findChild(QtWidgets.QLineEdit, 'xinput')
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y_input = widget.findChild(QtWidgets.QLineEdit, 'yinput')
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if x_input is None or y_input is None:
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return dict(x_size=3, y_size=3)
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x_size = int(x_input.text())
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y_size = int(y_input.text())
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return dict(x_size=x_size, y_size=y_size)
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@staticmethod
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def run_alg(pth, x_size, y_size, *args, **kargs):
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x_size = int(x_size)
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y_size = int(y_size)
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# pth = layer.path
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if pth is None:
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return
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ds = gdal.Open(pth)
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band_count = ds.RasterCount
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out_path = os.path.join(Project().other_path, 'morphology_filter_{}.tif'.format(int(datetime.now().timestamp() * 1000)))
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out_ds = gdal.GetDriverByName('GTiff').Create(out_path, ds.RasterXSize, ds.RasterYSize, band_count, ds.GetRasterBand(1).DataType)
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out_ds.SetProjection(ds.GetProjection())
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out_ds.SetGeoTransform(ds.GetGeoTransform())
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for i in range(band_count):
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band = ds.GetRasterBand(i+1)
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data = band.ReadAsArray()
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#gradient形态学梯度计算
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data=rank.gradient(data,rectangle(y_size,x_size))
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out_band = out_ds.GetRasterBand(i+1)
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out_band.WriteArray(data)
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out_ds.FlushCache()
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del out_ds
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del ds
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return out_path
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@ -54,6 +54,7 @@ class ActionManager(QtCore.QObject):
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self.file_menu = menubar.addMenu( '&文件')
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self.basic_menu = menubar.addMenu( '&基础工具')
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self.filter_menu = self.basic_menu.addMenu(IconInstance().FILTER, '&滤波处理')
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self.change_detection_menu = menubar.addMenu('&通用变化检测')
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# self.unsupervised_menu = self.change_detection_menu.addMenu(IconInstance().UNSUPERVISED, '&无监督变化检测')
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self.supervised_menu = self.change_detection_menu.addMenu(IconInstance().SUPERVISED,'&监督变化检测')
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test-data/AAA.tif.ovr
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test-data/BBB.tif.ovr
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test-data/BBB.tif.ovr
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