help="spatial resolution in x (in m)",
dest="dx",
required=False,
type=int,
default=100)
parser.add_argument("-dy",
"--dy",
help="spatial resolution in y (in m)",
dest="dy",
required=False,
type=int,
default=100)
args = parser.parse_args()
ULX = 600000.0
ULY = 4000020.0
LRX = 709800.0
LRY = 3890220.0
projection = 'epsg:32612'
dict = {'ulx': ULX, 'uly': ULY, 'lrx': LRX, 'lry': LRY, 'a_srs': projection}
dict.update({'otype': 'GDT_UInt16'})
dict.update({'dy': args.dy, 'dx': args.dx})
jim0 = jl.createJim(**dict)
if jim0.nrOfCol() != 1098:
print("Failed: number of cols")
if jim0.nrOfRow() != 1098:
print("Failed: number of rows")
else:
print("Success: create georeferenced image")
jim0.close()
dest="sampleSize",
required=False,
type=int,
default=100)
parser.add_argument("-classifier",
"--classifier",
help="classifier (sml, svm, ann)",
dest="classifier",
required=True,
type=str,
default="sml")
args = parser.parse_args()
# try:
if True:
jim = jl.createJim(args.input)
#preparation of reference
classDict = {}
classDict['urban'] = 2
classDict['agriculture'] = 12
classDict['forest'] = 25
classDict['water'] = 41
classDict['rest'] = 50
classFrom = list(range(0, 50))
classTo = [50] * 50
for i in range(0, 50):
if i >= 1 and i < 10:
classTo[i] = classDict['urban']
elif i >= 11 and i < 22:
classTo[i] = classDict['agriculture']
elif i >= 23 and i < 25:
parser=argparse.ArgumentParser()
parser.add_argument("-input","--input",help="Path of the input raster dataset",dest="input",required=True,type=str)
parser.add_argument("-filter","--filter",help="filter function",dest="filter",required=False,type=str)
parser.add_argument("-band","--band",help="band to filter (leave empty to filter all bands)",dest="band",required=False,type=int,nargs='+')
parser.add_argument("-size","--size",help="size",dest="size",required=False,type=int,default=3)
parser.add_argument("-nodata","--nodata",help="no data value",dest="nodata",required=False,type=int,nargs='+')
parser.add_argument("-output","--output",help="Path of the classification output raster dataset",dest="output",required=False,type=str)
args = parser.parse_args()
# try:
if True:
jimlist=jl.createJimList()
if args.band:
for band in args.band:
jim0=jl.createJim(filename=args.input,band=band)
print("mean of jim0:{}".format(jim0.getStats({'function':'mean'})))
projection=jim0.getProjection()
gt=jim0.getGeoTransform()
np0=jl.jim2np(jim0)
jim=jl.np2jim(np0)
print("mean of jim:{}".format(jim.getStats({'function':'mean'})))
print("number of cols in jim:{}".format(jim.nrOfCol()))
print("number of rows in jim:{}".format(jim.nrOfRow()))
# jim.setGeoTransform(gt)
# jim.setProjection(projection)
if args.filter:
if args.nodata:
print("filter with nodata value {}".format(args.nodata))
jimlist.pushImage(jim.filter2d({'filter':args.filter,'dx':args.size,'dy':args.size,'nodata':args.nodata}))
else:
# Change log
import argparse
import os
import jiplib as jl
parser = argparse.ArgumentParser()
parser.add_argument("-input",
"--input",
help="Path of the input file",
dest="input",
required=True,
type=str)
args = parser.parse_args()
jim0 = jl.createJim(filename=args.input, noread=True)
ULX = jim0.getUlx()
ULY = jim0.getUly()
LRX = ULX + 1000
LRY = ULY - 1000
jim0.close()
jim0 = jl.createJim(filename=args.input,
ulx=ULX,
uly=ULY,
lrx=LRX,
lry=LRY,
dx=5,
dy=5)
if jim0.nrOfCol() != 200:
print("Failed: createJim with upsample")
elif jim0.nrOfRow() != 200:
import argparse
import os
import math
import jiplib as jl
parser=argparse.ArgumentParser()
parser.add_argument("-input","--input",help="Path of the input raster dataset",dest="input",required=True,type=str)
parser.add_argument("-vector","--vector",help="Path of the sample vector dataset with labels",dest="vector",required=True,type=str)
parser.add_argument("-model","--model",help="Path of the model output filename used for training",dest="model",required=True,type=str)
parser.add_argument("-output","--output",help="Path of the classification output raster dataset",dest="output",required=True,type=str)
parser.add_argument("-classifier","--classifier",help="classifier (svm, ann)",dest="classifier",required=False,type=str,default="svm")
args = parser.parse_args()
try:
print("createJim")
jim=jl.createJim(args.input)
print("createVector")
sample=jl.createVector();
print("open vector",args.vector)
sample.open(args.vector)
print("extractOgr")
training=jim.extractOgr(sample,{'output':'training','oformat':'Memory','copy':'label'})
test=jim.extractOgr(sample,{'output':'test','oformat':'Memory','copy':'None'})
if args.classifier == 'svm':
#SVM classification
print("training")
training.train({'method':args.classifier,'label':'label','model':args.model})
print("classification")
vclass=test.classify({'output':args.output,'co':'OVERWRITE=YES','model':args.model,'method':args.classifier})
print("write")
vclass.write()
type=float,
default=2000)
args = parser.parse_args()
ULX = 600000.0
ULY = 4000020.0
LRX = 709800.0
LRY = 3890220.0
projection = 'epsg:32612'
dict = {'ulx': ULX, 'uly': ULY, 'lrx': LRX, 'lry': LRY, 'a_srs': projection}
dict.update({'nrow': args.nrow, 'ncol': args.ncol})
dict.update({'uniform': [args.min, args.max + 1]})
dict.update({'otype': 'GDT_UInt16'})
dict.update({'seed': 10915})
try:
jim0 = jl.createJim(**dict)
#create a copy
jim1 = jl.createJim(jim0)
if not jim1.isEqual(jim0):
print("Failed: isEqual")
throw()
jim0.d_pointOpBlank(500)
if jim1.isEqual(jim0):
print("Failed: isEqual")
throw()
jim1.d_pointOpBlank(2000)
jim0.close()
theStats = jim1.getStats({'function': ['max']})
if theStats['max'] != 2000:
print("Failed: max")
throw()
# History # 2017/10/23 - Created by Pieter Kempeneers ([email protected]) # Change log import argparse import os import jiplib as jl parser=argparse.ArgumentParser() parser.add_argument("-input","--input",help="Path of the input file",dest="input",required=True,type=str) parser.add_argument("-extent","--extent",help="Path of the extent file",dest="extent",required=True,type=str) args = parser.parse_args() jim0=jl.createJim(filename=args.input,extent=args.extent) v0=jl.createVector() v0.open({'filename':args.extent}) print("v0.getBoundingBox():",v0.getBoundingBox()) if jim0.getUlx()<v0.getUlx()-jim0.getDeltaX() or jim0.getUlx()>v0.getUlx()+jim0.getDeltaX(): print("1Failed: get spatial extent ulx") elif jim0.getUly()>v0.getUly()+jim0.getDeltaY() or jim0.getUly()<v0.getUly()-jim0.getDeltaY(): print("2Failed: get spatial extent uly") if jim0.getLrx()<v0.getLrx()-jim0.getDeltaX() or jim0.getLrx()>v0.getLrx()+jim0.getDeltaX(): print("3Failed: get spatial extent lrx") elif jim0.getLry()>v0.getLry()+jim0.getDeltaY() or jim0.getLry()<v0.getLry()-jim0.getDeltaY(): print("4Failed: get spatial extent lry") else: print("Success: createJim with extent") jim0.close() v0.close()
oformat='Memory'
openDict={'t_srs':'epsg:'+args.t_srs}
openDict.update({'ulx':args.ulx,'uly':args.uly,'lrx':args.lrx,'lry':args.lry})
if(args.dx):
openDict.update({'dx':args.dx})
if(args.dy):
openDict.update({'dy':args.dy})
if args.input:
refpath=args.input
else:
refpath='/eos/jeodpp/data/base/Landcover/EUROPE/CorineLandCover/CLC2012/VER18-5/Data/GeoTIFF/250m/g250_clc12_V18_5.tif'
openDict.update({'s_srs':'epsg:3035'})
# openDict.update({'filename':refpath})
jim_ref=jl.createJim(refpath,**openDict)
# jim_ref=jim_ref.warp({'t_srs':'epsg:'+args.t_srs})
classDict={}
classDict['urban']=2
classDict['agriculture']=12
classDict['forest']=25
classDict['water']=41
classDict['rest']=50
sorted(classDict.values())
print(classDict)
classFrom=list(range(0,50))
classTo=[50]*50
print("classFrom: {}".format(classFrom))
help="Postpone reading raster dataset",
dest="noread",
required=False,
type=bool,
default=False)
parser.add_argument("-random",
"--random",
help="Number of random pixels to select",
dest="random",
required=False,
type=int,
default=100)
args = parser.parse_args()
try:
jim0 = jl.createJim(args.input)
rules = ['centroid', 'min', 'max', 'mean', 'stdev']
if not args.vector:
v01 = jim0.extractSample({
'random': 20,
'buffer': 3,
'rule': rules,
'output': 'mem01',
'oformat': 'Memory'
})
v01.close()
npoint = 100
gridsize = int(jim0.nrOfCol() * jim0.getDeltaX() / math.sqrt(npoint))
v02 = jim0.extractSample({
'grid': gridsize,
'buffer': 3,
parser.add_argument("-max","--max",help="max value for pixel values",dest="max",required=False,type=float,default=2000)
args = parser.parse_args()
ULX=600000.0
ULY=4000020.0
LRX=709800.0
LRY=3890220.0
projection='epsg:32612'
dict={'ulx':ULX,'uly':ULY,'lrx':LRX,'lry':LRY,'a_srs':projection}
dict.update({'nrow':args.nrow,'ncol':args.ncol})
dict.update({'uniform':[args.min,args.max+1]})
dict.update({'otype':'GDT_UInt16'})
dict.update({'seed':10915})
# try:
if True:
jim0=jl.createJim(**dict)
jim0.d_pointOpBlank(500)
#create a copy without copying pixel values
jim1=jl.createJim(jim0,copyData=False)
#images should have same geoTransform
print("jim0.getGeoTransform:{}".format(jim0.getGeoTransform()))
print("jim1.getGeoTransform:{}".format(jim1.getGeoTransform()))
if jim0.getGeoTransform() != jim1.getGeoTransform():
print("Failed: geoTransform")
throw()
print("stats jim0:{}".format(jim0.getStats({'function':['min','max','mean']})))
print("stats jim1:{}".format(jim1.getStats({'function':['min','max','mean']})))
#images should not be identical in pixel values
if jim0.isEqual(jim1):
print("Failed: isEqual")
throw()
