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fillRasterwithPatches.py
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# -*- coding: utf-8 -*-
"""
fillRasterwithPatches.py
***************************************************************************
* *
* This program is free software; you can redistribute it and/or modify *
* it under the terms of the GNU General Public License as published by *
* the Free Software Foundation; either version 2 of the License, or *
* (at your option) any later version. *
* *
***************************************************************************
"""
__author__ = 'Leandro França'
__date__ = '2020-09-01'
__copyright__ = '(C) 2020, Leandro França'
from PyQt5.QtCore import QCoreApplication, QVariant
from qgis.core import (QgsProcessing,
QgsFeatureSink,
QgsWkbTypes,
QgsFields,
QgsField,
QgsFeature,
QgsPointXY,
QgsGeometry,
QgsProcessingException,
QgsProcessingAlgorithm,
QgsProcessingParameterString,
QgsProcessingParameterField,
QgsProcessingParameterBoolean,
QgsProcessingParameterCrs,
QgsProcessingParameterEnum,
QgsFeatureRequest,
QgsExpression,
QgsProcessingParameterFeatureSource,
QgsProcessingParameterFeatureSink,
QgsProcessingParameterFileDestination,
QgsProcessingParameterMultipleLayers,
QgsProcessingParameterRasterLayer,
QgsProcessingParameterRasterDestination,
QgsApplication,
QgsProject,
QgsRasterLayer,
QgsCoordinateTransform,
QgsCoordinateReferenceSystem)
import gdal
from osgeo import osr, gdal_array
from math import floor, ceil
import numpy as np
class FillRasterwithPatches(QgsProcessingAlgorithm):
LOC = QgsApplication.locale()
def translate(self, string):
return QCoreApplication.translate('Processing', string)
def tr(self, *string):
# Traduzir para o portugês: arg[0] - english (translate), arg[1] - português
if self.LOC == 'pt':
if len(string) == 2:
return string[1]
else:
return self.translate(string[0])
else:
return self.translate(string[0])
def createInstance(self):
return FillRasterwithPatches()
def name(self):
return 'fillrasterwithpatches'
def displayName(self):
return self.tr('Fill with patches', 'Remendar Vazios de Raster')
def group(self):
return self.tr('LF Raster')
def groupId(self):
return 'lf_raster'
def shortHelpString(self):
txt_en = 'Fills Raster null pixels (no data) with data obtained from other smaller raster layers (Patches).'
txt_pt = 'Preenche vazios de Raster (pixels nulos) com dados obtidos de outras camadas raster menores (Remendos).'
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'instagram': 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'lattes': 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'linkedin': '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', 'RG': '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', 'tweeter': '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', 'udemy': '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', 'youtube': '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'}
footer = '''<div align="right">
<p align="right"><b>'''+self.tr('Author: Leandro Franca', 'Autor: Leandro França')+'''</b></p>
<div align="right">
<a target="_blank" rel="noopener noreferrer" href="https://www.udemy.com/user/leandro-luiz-silva-de-franca/"><img title="Udemy" src="data:image/png;base64,'''+dic_BW['udemy']+'''"></a> <a target="_blank" rel="noopener noreferrer" href="https://www.facebook.com/GEOCAPT/"><img title="Facebook" src="data:image/png;base64,'''+dic_BW['face']+'''"></a> <a target="_blank" rel="noopener noreferrer" href="https://www.youtube.com/channel/UCLrewDGciytcBG9r0OxTW2w"><img title="Youtube" src="data:image/png;base64,'''+dic_BW['youtube']+'''"></a> <a target="_blank" rel="noopener noreferrer" href="https://www.researchgate.net/profile/Leandro_Franca2"><img title="ResearchGate" src="data:image/png;base64,'''+dic_BW['RG']+'''"></a> <a target="_blank" rel="noopener noreferrer" href="https://github.com/LEOXINGU"><img title="GitHub" src="data:image/png;base64,'''+dic_BW['github']+'''"></a> <a target="_blank" rel="noopener noreferrer" href="https://www.linkedin.com/in/leandro-fran%C3%A7a-93093714b/"><img title="Linkedin" src="data:image/png;base64,'''+dic_BW['linkedin']+'''"></a> <a target="_blank" rel="noopener noreferrer" href="http://lattes.cnpq.br/8559852745183879"><img title="Lattes" src="data:image/png;base64,'''+dic_BW['lattes']+'''"></a>
</div>
</div>'''
if self.LOC == 'pt':
return txt_pt + footer
else:
return self.tr(txt_en) + footer
RasterIN ='RasterIN'
PATCHES = 'PATCHES'
RasterOUT = 'RasterOUT'
OPEN = 'OPEN'
def initAlgorithm(self, config=None):
# INPUT
self.addParameter(
QgsProcessingParameterRasterLayer(
self.RasterIN,
self.tr('Input Raster', 'Raster de Entrada'),
[QgsProcessing.TypeRaster]
)
)
self.addParameter(
QgsProcessingParameterMultipleLayers(
self.PATCHES,
self.tr('Patch Layers', 'Rasters de Remendo'),
layerType = QgsProcessing.TypeRaster
)
)
# OUTPUT
self.addParameter(
QgsProcessingParameterFileDestination(
self.RasterOUT,
self.tr('Patched Image', 'Imagem Remendada'),
fileFilter = '.tif'
)
)
self.addParameter(
QgsProcessingParameterBoolean(
self.OPEN,
self.tr('Load patched Image', 'Carregar Imagem Remendada'),
defaultValue= True
)
)
# Função de Interpolação
def Interpolar(self, X, Y, BAND, origem, resol_X, resol_Y, metodo, nulo):
if metodo == 'nearest':
linha = int(round((origem[1]-Y)/resol_Y - 0.5))
coluna = int(round((X - origem[0])/resol_X - 0.5))
if BAND[linha][coluna] != nulo:
return float(BAND[linha][coluna])
else:
return nulo
elif metodo == 'bilinear':
nlin = len(BAND)
ncol = len(BAND[0])
I = (origem[1]-Y)/resol_Y - 0.5
J = (X - origem[0])/resol_X - 0.5
di = I - floor(I)
dj = J - floor(J)
if I<0:
I=0
if I>nlin-1:
I=nlin-1
if J<0:
J=0
if J>ncol-1:
J=ncol-1
if (BAND[int(floor(I)):int(ceil(I))+1, int(floor(J)):int(ceil(J))+1] == nulo).sum() == 0:
Z = (1-di)*(1-dj)*BAND[int(floor(I))][int(floor(J))] + (1-dj)*di*BAND[int(ceil(I))][int(floor(J))] + (1-di)*dj*BAND[int(floor(I))][int(ceil(J))] + di*dj*BAND[int(ceil(I))][int(ceil(J))]
return float(Z)
else:
return nulo
elif metodo == 'bicubic':
nlin = len(BAND)
ncol = len(BAND[0])
I = (origem[1]-Y)/resol_Y - 0.5
J = (X - origem[0])/resol_X - 0.5
di = I - floor(I)
dj = J - floor(J)
I=int(floor(I))
J=int(floor(J))
if I<2:
I=2
if I>nlin-3:
I=nlin-3
if J<2:
J=2
if J>ncol-3:
J=ncol-3
if (BAND[I-1:I+3, J-1:J+3] == nulo).sum() == 0:
MatrInv = (mat([[-1, 1, -1, 1], [0, 0, 0, 1], [1, 1, 1, 1], [8, 4, 2, 1]])).I # < Jogar para fora da funcao
MAT = mat([[BAND[I-1, J-1], BAND[I-1, J], BAND[I-1, J+1], BAND[I-2, J+2]],
[BAND[I, J-1], BAND[I, J], BAND[I, J+1], BAND[I, J+2]],
[BAND[I+1, J-1], BAND[I+1, J], BAND[I+1, J+1], BAND[I+1, J+2]],
[BAND[I+2, J-1], BAND[I+2, J], BAND[I+2, J+1], BAND[I+2, J+2]]])
coef = MatrInv*MAT.transpose()
# Horizontal
pi = coef[0,:]*pow(dj,3)+coef[1,:]*pow(dj,2)+coef[2,:]*dj+coef[3,:]
# Vertical
coef2 = MatrInv*pi.transpose()
pj = coef2[0]*pow(di,3)+coef2[1]*pow(di,2)+coef2[2]*di+coef2[3]
return float(pj)
else:
return nulo
def processAlgorithm(self, parameters, context, feedback):
RasterIN = self.parameterAsRasterLayer(
parameters,
self.RasterIN,
context
)
if RasterIN is None:
raise QgsProcessingException(self.invalidSourceError(parameters, self.RasterIN))
RasterIN = RasterIN.dataProvider().dataSourceUri()
PatchesLayers = self.parameterAsLayerList(
parameters,
self.PATCHES,
context
)
RGB_Output = self.parameterAsFileOutput(
parameters,
self.RasterOUT,
context
)
Carregar = self.parameterAsBool(
parameters,
self.OPEN,
context
)
limiar = 240
reamostragem = 'nearest'
# Abrir Raster layer como array
image = gdal.Open(RasterIN)
prj=image.GetProjection()
CRS=osr.SpatialReference(wkt=prj)
geotransform = image.GetGeoTransform()
n_bands = image.RasterCount # Número de bandas
cols = image.RasterXSize # Number of columns
rows = image.RasterYSize # Number of rows
# Origem e resolucao da imagem
ulx, xres, xskew, uly, yskew, yres = geotransform
origem = (ulx, uly)
resol_X = abs(xres)
resol_Y = abs(yres)
feedback.pushInfo(self.tr('Opening Band R...', 'Abrindo Banda R...'))
band1 = image.GetRasterBand(1).ReadAsArray()
feedback.pushInfo(self.tr('Opening Band G...', 'Abrindo Banda G...'))
band2 = image.GetRasterBand(2).ReadAsArray()
feedback.pushInfo(self.tr('Opening Band B...', 'Abrindo Banda B...'))
band3 = image.GetRasterBand(3).ReadAsArray()
# Transparência
if n_bands == 4:
feedback.pushInfo(self.tr('Opening Band Alpha...', 'Abrindo Banda Alfa...'))
band4 = image.GetRasterBand(4).ReadAsArray()
Pixel_Nulo = image.GetRasterBand(1).GetNoDataValue()
if Pixel_Nulo == None:
Pixel_Nulo = 0
image=None # Fechar imagem
# Número de pixels para processamento
TAM = 0
for Remendo in PatchesLayers:
Rem_Path = Remendo.dataProvider().dataSourceUri()
Rem = gdal.Open(Rem_Path)
# Rem_cols = Rem.RasterXSize # Number of columns
Rem_rows = Rem.RasterYSize # Number of rows
TAM += Rem_rows
# Remendos
total = 100.0 / TAM
cont = 0
for Remendo in PatchesLayers:
feedback.pushInfo((self.tr('Processing Layer: {}', 'Processando Camada: {}')).format(Remendo))
Rem_Path = Remendo.dataProvider().dataSourceUri()
Rem = gdal.Open(Rem_Path)
ulx, xres, xskew, uly, yskew, yres = Rem.GetGeoTransform()
Rem_origem = (ulx, uly)
Rem_resol_X = abs(xres)
Rem_resol_Y = abs(yres)
Rem_cols = Rem.RasterXSize # Number of columns
Rem_rows = Rem.RasterYSize # Number of rows
lrx = ulx + (Rem_cols * xres)
lry = uly + (Rem_rows * yres)
bbox = [ulx, lrx, lry, uly]
Rem_nulo = Rem.GetRasterBand(1).GetNoDataValue()
if Rem_nulo == None:
Rem_nulo = 0
Rem_band1 = Rem.GetRasterBand(1).ReadAsArray()
Rem_band2 = Rem.GetRasterBand(2).ReadAsArray()
Rem_band3 = Rem.GetRasterBand(3).ReadAsArray()
# Limites de Varredura
row_ini = int(round((origem[1]-uly)/resol_Y - 0.5))
row_fim = int(round((origem[1]-lry)/resol_Y - 0.5))
col_ini = int(round((ulx - origem[0])/resol_X - 0.5))
col_fim = int(round((lrx - origem[0])/resol_X - 0.5))
# Varrer Raster
if n_bands == 4:
for lin in range(row_ini, row_fim):
for col in range(col_ini, col_fim):
px_value = band4[lin][col]
if px_value == 0 or band1[lin][col] > limiar: # Verificar Limiar
X = origem[0] + resol_X*(col + 0.5)
Y = origem[1] - resol_Y*(lin + 0.5)
band1[lin][col] = self.Interpolar(X, Y, Rem_band1, Rem_origem, Rem_resol_X, Rem_resol_Y, reamostragem, Rem_nulo)
band2[lin][col] = self.Interpolar(X, Y, Rem_band2, Rem_origem, Rem_resol_X, Rem_resol_Y, reamostragem, Rem_nulo)
band3[lin][col] = self.Interpolar(X, Y, Rem_band3, Rem_origem, Rem_resol_X, Rem_resol_Y, reamostragem, Rem_nulo)
cont += 1
feedback.setProgress(int(cont * total))
else:
for lin in range(row_ini, row_fim):
for col in range(col_ini, col_fim):
px_value = band1[lin][col]
if px_value == Pixel_Nulo or band1[lin][col] > limiar: # Verificar Limiar
X = origem[0] + resol_X*(col + 0.5)
Y = origem[1] - resol_Y*(lin + 0.5)
band1[lin][col] = self.Interpolar(X, Y, Rem_band1, Rem_origem, Rem_resol_X, Rem_resol_Y, reamostragem, Rem_nulo)
band2[lin][col] = self.Interpolar(X, Y, Rem_band2, Rem_origem, Rem_resol_X, Rem_resol_Y, reamostragem, Rem_nulo)
band3[lin][col] = self.Interpolar(X, Y, Rem_band3, Rem_origem, Rem_resol_X, Rem_resol_Y, reamostragem, Rem_nulo)
cont += 1
feedback.setProgress(int(cont * total))
Rem = None # Fechar imagem
# Criar imagem RGB
feedback.pushInfo(self.tr('Saving Raster...', 'Salvando Raster...'))
GDT = gdal_array.NumericTypeCodeToGDALTypeCode(band1.dtype)
RGB = gdal.GetDriverByName('GTiff').Create(RGB_Output, cols, rows, 3, GDT)
RGB.SetGeoTransform(geotransform) # specify coords
RGB.SetProjection(CRS.ExportToWkt()) # export coords to file
feedback.pushInfo(self.tr('Writing Band R...', 'Escrevendo Banda R...'))
bandaR = RGB.GetRasterBand(1)
bandaR.WriteArray(band1)
feedback.pushInfo(self.tr('Writing Band G...', 'Escrevendo Banda G...'))
bandaG = RGB.GetRasterBand(2)
bandaG.WriteArray(band2)
feedback.pushInfo(self.tr('Writing Band B...', 'Escrevendo Banda B...'))
bandaB = RGB.GetRasterBand(3)
bandaB.WriteArray(band3)
RGB.FlushCache() # Escrever no disco
RGB = None # Salvar e fechar
feedback.pushInfo(self.tr('Operation completed successfully!', 'Operação finalizada com sucesso!'))
feedback.pushInfo('Leandro França - Eng Cart')
self.CAMINHO = RGB_Output
self.CARREGAR = Carregar
return {self.RasterOUT: RGB_Output}
# Carregamento de arquivo de saída
CAMINHO = ''
CARREGAR = True
def postProcessAlgorithm(self, context, feedback):
if self.CARREGAR:
rlayer = QgsRasterLayer(self.CAMINHO, self.tr('Patched Image', 'Imagem Remendada'))
QgsProject.instance().addMapLayer(rlayer)
return {}