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precess.py
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precess.py
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# -*- encoding: utf-8 -*-
from osgeo import gdal
import numpy as np
from osgeo import osr
import os
import cv2
import sys
# from gdalconst import *
def geo2lonlat(dataset, x, y):
'''
将投影坐标转为经纬度坐标（具体的投影坐标系由给定数据确定）
:param dataset: GDAL地理数据
:param x: 投影坐标x
:param y: 投影坐标y
:return: 投影坐标(x, y)对应的经纬度坐标(lon, lat)
'''
prosrs, geosrs = getSRSPair(dataset)
ct = osr.CoordinateTransformation(prosrs, geosrs)
coords = ct.TransformPoint(x, y)
return coords[:2]
def imagexy2geo(dataset, row, col):
'''
根据GDAL的六参数模型将影像图上坐标（行列号）转为投影坐标或地理坐标（根据具体数据的坐标系统转换）
:param dataset: GDAL地理数据
:param row: 像素的行号
:param col: 像素的列号
:return: 行列号(row, col)对应的投影坐标或地理坐标(x, y)
'''
trans = dataset.GetGeoTransform()
px = trans[0] + row * trans[1] + col * trans[2]
py = trans[3] + row * trans[4] + col * trans[5]
return px, py
def getSRSPair(dataset):
'''
获得给定数据的投影参考系和地理参考系
:param dataset: GDAL地理数据
:return: 投影参考系和地理参考系
'''
prosrs = osr.SpatialReference()
prosrs.ImportFromWkt(dataset.GetProjection())
geosrs = prosrs.CloneGeogCS()
return prosrs, geosrs
def lonlat2geo(dataset, lon, lat):
'''
将经纬度坐标转为投影坐标（具体的投影坐标系由给定数据确定）
:param dataset: GDAL地理数据
:param lon: 地理坐标lon经度
:param lat: 地理坐标lat纬度
:return: 经纬度坐标(lon, lat)对应的投影坐标
'''
prosrs, geosrs = getSRSPair(dataset)
ct = osr.CoordinateTransformation(geosrs, prosrs)
coords = ct.TransformPoint(lon, lat)
return coords[:2]
def geo2imagexy(dataset, x, y):
'''
根据GDAL的六 参数模型将给定的投影或地理坐标转为影像图上坐标（行列号）
:param dataset: GDAL地理数据
:param x: 投影或地理坐标x
:param y: 投影或地理坐标y
:return: 影坐标或地理坐标(x, y)对应的影像图上行列号(row, col)
'''
trans = dataset.GetGeoTransform()
a = np.array([[trans[1], trans[2]], [trans[4], trans[5]]])
b = np.array([x - trans[0], y - trans[3]])
return np.linalg.solve(a, b) # 使用numpy的linalg.solve进行二元一次方程的求解
def transForm():
dataset = gdal.Open("test.tif")
out = open('fcn/1/locations2.txt', 'w')
f = open('fcn/1/1.csv')
l=[69,68,1,36,61,24,77,23,43]
while True:
line = f.readline()
if not line:
break
if line[0] == ';':
continue
lis = line.strip().split(',')
xx = float(lis[4])
yy = float(lis[5])
label = int(lis[-1])
if label not in l:
continue
coords = lonlat2geo(dataset, yy, xx)
coords = geo2imagexy(dataset, coords[0], coords[1])
if coords[0] > 0 and coords[1] > 0:
out.write('{},{},{}\n'.format(int(coords[0]), int(coords[1]), label))
def infoLonLat():
dataset=gdal.Open("/home/cln/hitsz/毕业设计/CDL_2014_clip_20170828212859_603366421/CDL_2014_clip_20170828212859_603366421.tif")
tifData=gdal.Open("/home/cln/hitsz/毕业设计/9.23/256.tif")
height=dataset.RasterYSize
width=dataset.RasterXSize
data=dataset.ReadAsArray(0,0,width,height)
start=int(sys.argv[1])
end=int(sys.argv[2])
index=sys.argv[3]
write=open("9.23/info"+str(index)+".txt","a+")
for row in range(start,end):
print row
for col in range(width):
px,py=imagexy2geo(dataset, col, row)
coords=geo2lonlat(dataset, px, py)
geos=lonlat2geo(tifData, coords[0], coords[1])
y,x=geo2imagexy(tifData, geos[0], geos[1])
if x<tifData.RasterYSize and y<tifData.RasterXSize:
# print row,col,"==>",x,y
write.write(str(int(x))+","+str(int(y))+","+str(data[row][col])+'\n')
write.close()
###5(0).Soybeans 141(1).Deciduous Forest 3(2).Rice 190(3).Woody Wetlands 176(4):Grass/Pasture 121(5):Developed/Open Space 1(6):Corn 61(7):Fallow/Idle Cropland
###2(8):Cotton 26(9)Dbl Crop WinWht/Soybeans 143(10).Mixed Forest 111(11):Open Water 122(12).Developed/Low Intensity 4(13).Sorghum others(14)
def CreateGeoTiff():
d1={}
d2={}
with open("9.23/info.txt","r") as f:
for line in f:
content=line.strip().split(",")
rows=content[0]
cols=content[1]
lab=int(content[2])
k=str(rows)+","+str(cols)
if lab!=0:
d1[k]=lab
print("done")
d2[5]=0
d2[141]=1
d2[3]=2
d2[190]=3
d2[176]=4
d2[121]=5
d2[1]=6
d2[61]=7
d2[2]=8
d2[26]=9
d2[143]=10
d2[111]=11
d2[122]=12
d2[4]=13
SourceDS = gdal.Open("9.23/256.tif")
GeoT = SourceDS.GetGeoTransform()
Projection = osr.SpatialReference()
Projection.ImportFromWkt(SourceDS.GetProjectionRef())
nXSize = SourceDS.RasterXSize
nYSize = SourceDS.RasterYSize
stride=40
picWidth=224
picHeight=224
width=int(np.floor((nXSize-picWidth)/stride)+1)
height=int(np.floor((nYSize-picHeight)/stride)+1)
start=sys.argv[1]
end=sys.argv[2]
for i in range(int(start),int(end)):
print i
for j in range(width):
Array=SourceDS.ReadAsArray(j*stride,i*stride,picHeight,picWidth)
DataType = gdal.GDT_Float32
labels=np.zeros([picWidth,picHeight])
for row in range(i*stride,i*stride+picWidth):
for col in range(j*stride,j*stride+picHeight):
k=str(row)+","+str(col)
if d1.get(k) is not None:
if d2.get(d1.get(k)) is not None:
labels[row-i*stride][col-j*stride]=int(d2[d1.get(k)])
else:
labels[row-i*stride][col-j*stride]=int(14)
else:
labels[row-i*stride][col-j*stride]=int(14)
if np.min(labels)!=np.max(labels):
NewFileName = str(i)+"_"+str(j)+"_923"
driver = gdal.GetDriverByName('GTiff')
DataSet = driver.Create( "chip9.23/data/"+NewFileName+".tif", picWidth, picHeight, 3, DataType )
DataSet.SetGeoTransform(GeoT)
DataSet.SetProjection( Projection.ExportToWkt() )
DataSet.GetRasterBand(1).WriteArray( Array[0])
DataSet.GetRasterBand(2).WriteArray( Array[1])
DataSet.GetRasterBand(3).WriteArray( Array[2])
txtName="chip9.23/labels/"+NewFileName+".txt"
w=open(txtName,"a+")
for m in range(picWidth):
for n in range(picHeight):
w.write(str(int(labels[m][n]))+" ")
w.write("\n")
w.close()
def test():
d={}
f=open("fcn/1/1.csv","r")
while True:
line = f.readline()
if not line:
break
if line[0] == ';':
continue
lis = line.strip().split(',')
xx = float(lis[4])
yy = float(lis[5])
label=int(lis[6])
if d.get(label) is None:
d[label]=1
else:
d[label]=d[label]+1
d=sorted(d.iteritems(),key=lambda x:x[1],reverse=True)
for k,val in d:
print k,val
def processData():
a=np.array([0.,0.,0.])
num=1369
for picName in os.listdir("chip/data"):
dataset=gdal.Open("chip/data/"+picName).ReadAsArray(0,0,224,224)
a[0]+=np.mean(dataset[0])
a[1]+=np.mean(dataset[1])
a[2]+=np.mean(dataset[2])
print a/float(num)
def statistic():
d={}
with open("info.txt") as f:
for line in f:
label=int(line.strip().split(",")[2])
if d.get(label) is None:
d[label]=1
else:
d[label]+=1
d=sorted(d.iteritems(),key=lambda x:x[1],reverse=True)
for k,v in d:
print k,v
if __name__ == '__main__':
# infoLonLat()
# statistic()
CreateGeoTiff()
# processData()
# data=gdal.Open("test.tif").ReadAsArray(0,0,12,12)
# print data
# test()
# transForm()