def test_gdal_translate_lib_8():
gcpList = [
gdal.GCP(440720.000, 3751320.000, 0, 0, 0),
gdal.GCP(441920.000, 3751320.000, 0, 20, 0),
gdal.GCP(441920.000, 3750120.000, 0, 20, 20),
gdal.GCP(440720.000, 3750120.000, 0, 0, 20)
]
ds = gdal.Open('../gcore/data/byte.tif')
ds = gdal.Translate('tmp/test8.tif',
ds,
outputSRS='EPSG:26711',
GCPs=gcpList)
if ds is None:
return 'fail'
if ds.GetRasterBand(1).Checksum() != 4672:
gdaltest.post_reason('Bad checksum')
return 'fail'
gcps = ds.GetGCPs()
if len(gcps) != 4:
gdaltest.post_reason('GCP count wrong.')
return 'fail'
if ds.GetGCPProjection().find('26711') == -1:
gdaltest.post_reason('Bad GCP projection.')
return 'fail'
ds = None
return 'success'
def warp_39():
# Create an output file with GCPs.
out_file = 'tmp/warp_39.tif'
ds = gdal.GetDriverByName('GTiff').Create(out_file, 50, 50, 3)
gcp_list = [
gdal.GCP(397000, 5642000, 0, 0, 0),
gdal.GCP(397000, 5641990, 0, 0, 50),
gdal.GCP(397010, 5642000, 0, 50, 0),
gdal.GCP(397010, 5641990, 0, 50, 50),
gdal.GCP(397005, 5641995, 0, 25, 25),
]
ds.SetGCPs(gcp_list, gdaltest.user_srs_to_wkt('EPSG:32632'))
ds = None
gdal.Warp(out_file, 'data/test3658.tif', options='-to DST_METHOD=GCP_TPS')
ds = gdal.Open(out_file)
cs = ds.GetRasterBand(1).Checksum()
ds = None
# Should exactly match the source file.
exp_cs = 30546
if cs != exp_cs:
gdaltest.post_reason('Got %d instead of expected checksum %d.' %
(cs, exp_cs))
return 'fail'
os.unlink(out_file)
return 'success'
def offset_image(inImage, coner_col_row, coner_coord, temp1, temp2):
'''
根据影像的脚点行列号及坐标，对影像进行偏移（配准）
:param inImage:输入影像路径
:param coner_col_row:元组，(upperLeft_col_row, lowerLeft_col_row, lowerRight_col_row, upperRight_col_row)
:param coner_coord:元组，(upperLeft_xy, lowerLeft_xy, lowerRight_xy, upperRight_xy)
'''
# gdal.GCP()是gdal中地面控制点的数据结构，顺序依次是：空间位置x,y,z,影像列号，行号
coordlist = [
gdal.GCP(coner_coord[0][0], coner_coord[0][1], 0, coner_col_row[0][0],
coner_col_row[0][1]),
gdal.GCP(coner_coord[1][0], coner_coord[1][1], 0, coner_col_row[1][0],
coner_col_row[1][1]),
gdal.GCP(coner_coord[2][0], coner_coord[2][1], 0, coner_col_row[2][0],
coner_col_row[2][1]),
gdal.GCP(coner_coord[3][0], coner_coord[3][1], 0, coner_col_row[3][0],
coner_col_row[3][1])
]
# 根据脚点坐标进行配准
gdal.Translate(temp1, inImage, GCPs=coordlist)
gdal.Warp(temp2,
temp1,
format="MEM",
srcNodata=0.0,
dstNodata=0.0,
dstSRS="EPSG:4326")
def test_gdalwarp_lib_5():
ds = gdal.Open('../gcore/data/byte.tif')
gcpList = [
gdal.GCP(440720.000, 3751320.000, 0, 0, 0),
gdal.GCP(441920.000, 3751320.000, 0, 20, 0),
gdal.GCP(441920.000, 3750120.000, 0, 20, 20),
gdal.GCP(440720.000, 3750120.000, 0, 0, 20)
]
ds1 = gdal.Translate('tmp/testgdalwarp_gcp.tif',
ds,
outputSRS='EPSG:26711',
GCPs=gcpList)
dstDS = gdal.Warp('', ds1, format='MEM', tps=True)
if dstDS.GetRasterBand(1).Checksum() != 4672:
gdaltest.post_reason('Bad checksum')
return 'fail'
if not gdaltest.geotransform_equals(ds.GetGeoTransform(),
dstDS.GetGeoTransform(), 1e-9):
gdaltest.post_reason('Bad geotransform')
return 'fail'
dstDS = None
return 'success'
def SetGCPsToGeoTransform(cornerPointUL, cornerPointUR, cornerPointLR,
cornerPointLL, frameCenterLon, frameCenterLat, ele):
''' Make Geotranform from pixel to lon lat coordinates '''
gcps = []
global gcornerPointUL, gcornerPointUR, gcornerPointLR, gcornerPointLL, gframeCenterLat, gframeCenterLon, geotransform_affine, geotransform
# TEMP FIX : If have elevation the geotransform is wrong
if ele:
del cornerPointUL[-1]
del cornerPointUR[-1]
del cornerPointLR[-1]
del cornerPointLL[-1]
gcornerPointUL = cornerPointUL
gcornerPointUR = cornerPointUR
gcornerPointLR = cornerPointLR
gcornerPointLL = cornerPointLL
gframeCenterLat = frameCenterLat
gframeCenterLon = frameCenterLon
Height = GetFrameCenter()[2]
gcp = gdal.GCP(cornerPointUL[1], cornerPointUL[0], Height, 0, 0,
"Corner Upper Left", "1")
gcps.append(gcp)
gcp = gdal.GCP(cornerPointUR[1], cornerPointUR[0], Height, xSize, 0,
"Corner Upper Right", "2")
gcps.append(gcp)
gcp = gdal.GCP(cornerPointLR[1], cornerPointLR[0], Height, xSize, ySize,
"Corner Lower Right", "3")
gcps.append(gcp)
gcp = gdal.GCP(cornerPointLL[1], cornerPointLL[0], Height, 0, ySize,
"Corner Lower Left", "4")
gcps.append(gcp)
gcp = gdal.GCP(frameCenterLon, frameCenterLat, Height, xSize / 2,
ySize / 2, "Center", "5")
gcps.append(gcp)
geotransform_affine = gdal.GCPsToGeoTransform(gcps)
src = np.float64(
np.array([[0.0, 0.0], [xSize, 0.0], [xSize, ySize], [0.0, ySize]]))
dst = np.float64(
np.array([cornerPointUL, cornerPointUR, cornerPointLR, cornerPointLL]))
try:
geotransform = from_points(src, dst)
except Exception:
pass
if geotransform is None:
qgsu.showUserAndLogMessage("",
"Unable to extract a geotransform.",
onlyLog=True)
return
def SetGCPsToGeoTransform(cornerPointUL, cornerPointUR, cornerPointLR,
cornerPointLL, frameCenterLon, frameCenterLat, ele):
''' Make Geotranform from pixel to lon lat coordinates '''
gcps = []
gv.setCornerUL(cornerPointUL)
gv.setCornerUR(cornerPointUR)
gv.setCornerLR(cornerPointLR)
gv.setCornerLL(cornerPointLL)
gv.setFrameCenter(frameCenterLat, frameCenterLon)
xSize = gv.getXSize()
ySize = gv.getYSize()
Height = GetFrameCenter()[2]
gcp = gdal.GCP(cornerPointUL[1], cornerPointUL[0], Height, 0, 0,
"Corner Upper Left", "1")
gcps.append(gcp)
gcp = gdal.GCP(cornerPointUR[1], cornerPointUR[0], Height, xSize, 0,
"Corner Upper Right", "2")
gcps.append(gcp)
gcp = gdal.GCP(cornerPointLR[1], cornerPointLR[0], Height, xSize, ySize,
"Corner Lower Right", "3")
gcps.append(gcp)
gcp = gdal.GCP(cornerPointLL[1], cornerPointLL[0], Height, 0, ySize,
"Corner Lower Left", "4")
gcps.append(gcp)
gcp = gdal.GCP(frameCenterLon, frameCenterLat, Height, xSize / 2,
ySize / 2, "Center", "5")
gcps.append(gcp)
at = gdal.GCPsToGeoTransform(gcps)
gv.setAffineTransform(at)
src = np.float64(
np.array([[0.0, 0.0], [xSize, 0.0], [xSize, ySize], [0.0, ySize],
[xSize / 2.0, ySize / 2.0]]))
dst = np.float64(
np.array([[cornerPointUL[0], cornerPointUL[1]],
[cornerPointUR[0], cornerPointUR[1]],
[cornerPointLR[0], cornerPointLR[1]],
[cornerPointLL[0], cornerPointLL[1]],
[frameCenterLat, frameCenterLon]]))
try:
geotransform, _ = findHomography(src, dst)
gv.setTransform(geotransform)
except Exception:
pass
if geotransform is None:
qgsu.showUserAndLogMessage("",
"Unable to extract a geotransform.",
onlyLog=True)
return
def do_rgs(data_time_value, rgs_file_path):
""" 配准
:param data_time_value: dict 原始图像的信息-GCJ02
{
"time" : "", #时间
"timestamp" : "", #时间戳
"url" : "", #下载链接
"extent" : "", #范围
"req_pnt" : "", #该瓦片请求的点坐标
"file_path" : "" #文件的path
}
:param rgs_file_path: str 配准后保存的路径
:return: rgs_data_item: dict/None
{
"extent" : "", #范围-WGS84
"file_path" : "", #该文件的路径
}
"""
# 将tiff保存到配准文件夹
origin_file_path = data_time_value["file_path"]
im = Image.open(origin_file_path)
im.save(rgs_file_path)
# 转换extent
extent_gcj02 = data_time_value[
"extent_gcj02"] #[21.532796186275732, 115.14559029127062, 25.66504821372427, 119.65495970872936]
extent_wgs84 = gcj02towgs84_extent(
extent_gcj02
) #[21.53519080438208, 115.14078044126353, 25.66805217057752, 119.65050502755392]
x1, y1, x2, y2 = extent_wgs84
# 用extent_wgs84对rgs_file_path文件进行配准
ds = gdal.Open(rgs_file_path, gdal.GA_Update) #打开影像
if not ds:
return None
# 创建坐标系
srs = osr.SpatialReference()
srs.SetWellKnownGeogCS('WGS84')
# 相关信息
rows = ds.RasterYSize # 行数
cols = ds.RasterXSize # 列数
# 创建地面控制点：经度、纬度、z，照片列数，照片行数
gcps = [
gdal.GCP(y1, x2, 0, 0, 0), # 左上
gdal.GCP(y2, x2, 0, cols - 1, 0), # 右上
gdal.GCP(y1, x1, 0, 0, rows - 1), # 左下
gdal.GCP(y2, x1, 0, cols - 1, rows - 1) # 右下
]
ds.SetGCPs(gcps, srs.ExportToWkt())
ds.SetProjection(srs.ExportToWkt())
ds.SetGeoTransform(gdal.GCPsToGeoTransform(gcps))
del ds
return {"extent": extent_wgs84, "file_path": rgs_file_path}
def vrtwarp_7():
if test_cli_utilities.get_gdalwarp_path() is None:
return 'skip'
src_ds = gdal.Open('../gcore/data/byte.tif')
tmp_ds = gdal.GetDriverByName('GTiff').CreateCopy('tmp/vrtwarp_7.tif',
src_ds)
cs_main = tmp_ds.GetRasterBand(1).Checksum()
tmp_ds.SetGeoTransform([0, 1, 0, 0, 0, 1]) # cancel geotransform
gcp1 = gdal.GCP()
gcp1.GCPPixel = 0
gcp1.GCPLine = 0
gcp1.GCPX = 440720.000
gcp1.GCPY = 3751320.000
gcp2 = gdal.GCP()
gcp2.GCPPixel = 0
gcp2.GCPLine = 20
gcp2.GCPX = 440720.000
gcp2.GCPY = 3750120.000
gcp3 = gdal.GCP()
gcp3.GCPPixel = 20
gcp3.GCPLine = 0
gcp3.GCPX = 441920.000
gcp3.GCPY = 3751320.000
src_gcps = (gcp1, gcp2, gcp3)
tmp_ds.SetGCPs(src_gcps, src_ds.GetProjectionRef())
tmp_ds.BuildOverviews('NEAR', overviewlist=[2, 4])
cs_ov0 = tmp_ds.GetRasterBand(1).GetOverview(0).Checksum()
cs_ov1 = tmp_ds.GetRasterBand(1).GetOverview(1).Checksum()
tmp_ds = None
gdaltest.runexternal(
test_cli_utilities.get_gdalwarp_path() +
' tmp/vrtwarp_7.tif tmp/vrtwarp_7.vrt -overwrite -of VRT -tps')
vrtwarp_ds = gdal.Open('tmp/vrtwarp_7.vrt')
if vrtwarp_ds.GetRasterBand(1).GetOverviewCount() != 2:
gdaltest.post_reason('fail')
return 'fail'
if vrtwarp_ds.GetRasterBand(1).Checksum() != cs_main:
print(cs_main)
return 'fail'
if vrtwarp_ds.GetRasterBand(1).GetOverview(0).Checksum() != cs_ov0:
gdaltest.post_reason('fail')
return 'fail'
if vrtwarp_ds.GetRasterBand(1).GetOverview(1).Checksum() != cs_ov1:
gdaltest.post_reason('fail')
return 'fail'
vrtwarp_ds = None
gdal.Unlink('tmp/vrtwarp_7.vrt')
gdal.Unlink('tmp/vrtwarp_7.tif')
return 'success'
def geographic_info(ds, srsout=None):
# Read geotransform matrix and source reference system
srs = osr.SpatialReference()
if ds.GetGCPCount():
gcps = ds.GetGCPs()
srs.ImportFromWkt(ds.GetGCPProjection())
geomatrix = gdal.GCPsToGeoTransform(gcps)
else:
gcps = []
if not ds.GetProjection():
raise ValueError('no geographic info in "%s"' %
ds.GetDescription())
srs.ImportFromWkt(ds.GetProjection())
geomatrix = ds.GetGeoTransform()
if geomatrix == (0.0, 1.0, 0.0, 0.0, 0.0, 1.0):
raise ValueError('no geographic info in "%s"' % ds.GetDescription())
# Set the target reference system
srsout = makesrs(srsout)
# Instantiate the coordinate transformer
transformer = osr.CoordinateTransformation(srs, srsout)
# dataset corners setup
corners = []
for id_, (pixel, line) in enumerate((
(0, 0),
(0, ds.RasterYSize - 1),
(ds.RasterXSize - 1, ds.RasterYSize - 1),
(ds.RasterXSize - 1, 0))):
X = geomatrix[0] + geomatrix[1] * pixel + geomatrix[2] * line
Y = geomatrix[3] + geomatrix[4] * pixel + geomatrix[5] * line
# Shift to the center of the pixel
X += geomatrix[1] / 2.0
Y += geomatrix[5] / 2.0
Z = 0.
(x, y, z) = transformer.TransformPoint(X, Y, Z)
gcp = gdal.GCP(x, y, z, pixel, line, '', str(id_ + 1))
corners.append(gcp)
# convert GCPs to the targer srs
outgcps = []
for gcp in gcps:
(x, y, z) = transformer.TransformPoint(gcp.GCPX, gcp.GCPY, gcp.GCPZ)
gcp = gdal.GCP(x, y, z, gcp.GCPPixel, gcp.GCPLine, gcp.Info, gcp.Id)
outgcps.append(gcp)
return corners, outgcps
def SetGCPsToGeoTransform(cornerPointUL, cornerPointUR, cornerPointLR,
cornerPointLL, frameCenterLon, frameCenterLat):
''' Make Geotranform from pixel to lon lat coordinates '''
gcps = []
global gcornerPointUL
gcornerPointUL = cornerPointUL
global gcornerPointUR
gcornerPointUR = cornerPointUR
global gcornerPointLR
gcornerPointLR = cornerPointLR
global gcornerPointLL
gcornerPointLL = cornerPointLL
global gframeCenterLat
gframeCenterLat = frameCenterLat
global gframeCenterLon
gframeCenterLon = frameCenterLon
global geotransform
global geotransform_affine
Height = GetFrameCenter()[2]
gcp = gdal.GCP(cornerPointUL[1], cornerPointUL[0], Height, 0, 0,
"Corner Upper Left", "1")
gcps.append(gcp)
gcp = gdal.GCP(cornerPointUR[1], cornerPointUR[0], Height, xSize, 0,
"Corner Upper Right", "2")
gcps.append(gcp)
gcp = gdal.GCP(cornerPointLR[1], cornerPointLR[0], Height, xSize, ySize,
"Corner Lower Right", "3")
gcps.append(gcp)
gcp = gdal.GCP(cornerPointLL[1], cornerPointLL[0], Height, 0, ySize,
"Corner Lower Left", "4")
gcps.append(gcp)
gcp = gdal.GCP(frameCenterLon, frameCenterLat, Height, xSize / 2,
ySize / 2, "Center", "5")
gcps.append(gcp)
geotransform_affine = gdal.GCPsToGeoTransform(gcps)
src = np.float64(
np.array([[0.0, 0.0], [xSize, 0.0], [xSize, ySize], [0.0, ySize]]))
dst = np.float64(
np.array([cornerPointUL, cornerPointUR, cornerPointLR, cornerPointLL]))
geotransform = from_points(src, dst)
if geotransform is None:
qgsu.showUserAndLogMessage("",
"Unable to extract a geotransform.",
onlyLog=True)
return
def vrtwarp_6():
src_ds = gdal.Open('../gcore/data/byte.tif')
tmp_ds = gdal.GetDriverByName('GTiff').CreateCopy('tmp/vrtwarp_6.tif',
src_ds)
cs_main = tmp_ds.GetRasterBand(1).Checksum()
tmp_ds.SetGeoTransform([0, 1, 0, 0, 0, 1]) # cancel geotransform
gcp1 = gdal.GCP()
gcp1.GCPPixel = 0
gcp1.GCPLine = 0
gcp1.GCPX = 440720.000
gcp1.GCPY = 3751320.000
gcp2 = gdal.GCP()
gcp2.GCPPixel = 0
gcp2.GCPLine = 20
gcp2.GCPX = 440720.000
gcp2.GCPY = 3750120.000
gcp3 = gdal.GCP()
gcp3.GCPPixel = 20
gcp3.GCPLine = 0
gcp3.GCPX = 441920.000
gcp3.GCPY = 3751320.000
src_gcps = (gcp1, gcp2, gcp3)
tmp_ds.SetGCPs(src_gcps, src_ds.GetProjectionRef())
tmp_ds.BuildOverviews('NEAR', overviewlist=[2, 4])
cs_ov0 = tmp_ds.GetRasterBand(1).GetOverview(0).Checksum()
cs_ov1 = tmp_ds.GetRasterBand(1).GetOverview(1).Checksum()
vrtwarp_ds = gdal.AutoCreateWarpedVRT(tmp_ds)
vrtwarp_ds.SetDescription('tmp/vrtwarp_6.vrt')
vrtwarp_ds = None
tmp_ds = None
vrtwarp_ds = gdal.Open('tmp/vrtwarp_6.vrt')
if vrtwarp_ds.GetRasterBand(1).GetOverviewCount() != 2:
gdaltest.post_reason('fail')
return 'fail'
if vrtwarp_ds.GetRasterBand(1).Checksum() != cs_main:
gdaltest.post_reason('fail')
return 'fail'
if vrtwarp_ds.GetRasterBand(1).GetOverview(0).Checksum() != cs_ov0:
gdaltest.post_reason('fail')
return 'fail'
if vrtwarp_ds.GetRasterBand(1).GetOverview(1).Checksum() != cs_ov1:
gdaltest.post_reason('fail')
return 'fail'
gdal.Unlink('tmp/vrtwarp_6.vrt')
gdal.Unlink('tmp/vrtwarp_6.tif')
return 'success'
def test_kea_7():
if gdaltest.kea_driver is None:
pytest.skip()
sr = osr.SpatialReference()
sr.ImportFromEPSG(4326)
# Geotransform
ds = gdaltest.kea_driver.Create("tmp/out.kea", 1, 1)
assert ds.GetGCPCount() == 0
assert ds.SetGeoTransform([1, 2, 3, 4, 5, 6]) == 0
assert ds.SetProjection(sr.ExportToWkt()) == 0
ds = None
ds = gdal.Open('tmp/out.kea')
out2_ds = gdaltest.kea_driver.CreateCopy('tmp/out2.kea', ds)
ds = None
assert out2_ds.GetGCPCount() == 0
assert out2_ds.GetGeoTransform() == (1, 2, 3, 4, 5, 6)
assert out2_ds.GetProjectionRef() != ''
out2_ds = None
gdaltest.kea_driver.Delete('tmp/out.kea')
gdaltest.kea_driver.Delete('tmp/out2.kea')
# GCP
ds = gdaltest.kea_driver.Create("tmp/out.kea", 1, 1)
gcp1 = gdal.GCP(0, 1, 2, 3, 4)
gcp1.Id = "id"
gcp1.Info = "info"
gcp2 = gdal.GCP(0, 1, 2, 3, 4)
gcps = [gcp1, gcp2]
ds.SetGCPs(gcps, sr.ExportToWkt())
ds = None
ds = gdal.Open('tmp/out.kea')
out2_ds = gdaltest.kea_driver.CreateCopy('tmp/out2.kea', ds)
ds = None
assert out2_ds.GetGCPCount() == 2
assert out2_ds.GetGCPProjection() != ''
got_gcps = out2_ds.GetGCPs()
for i in range(2):
assert (got_gcps[i].GCPX == gcps[i].GCPX and got_gcps[i].GCPY == gcps[i].GCPY and \
got_gcps[i].GCPZ == gcps[i].GCPZ and got_gcps[i].GCPPixel == gcps[i].GCPPixel and \
got_gcps[i].GCPLine == gcps[i].GCPLine and got_gcps[i].Id == gcps[i].Id and \
got_gcps[i].Info == gcps[i].Info)
out2_ds = None
gdaltest.kea_driver.Delete('tmp/out.kea')
gdaltest.kea_driver.Delete('tmp/out2.kea')
def overviewds_3():
src_ds = gdal.Open('data/byte.tif')
ds = gdal.GetDriverByName('GTiff').CreateCopy('tmp/byte.tif', src_ds)
ds.SetGeoTransform([0, 1, 0, 0, 0, 1]) # cancel geotransform
gcp1 = gdal.GCP()
gcp1.GCPPixel = 0
gcp1.GCPLine = 0
gcp1.GCPX = 440720.000
gcp1.GCPY = 3751320.000
gcp2 = gdal.GCP()
gcp2.GCPPixel = 0
gcp2.GCPLine = 20
gcp2.GCPX = 440720.000
gcp2.GCPY = 3750120.000
gcp3 = gdal.GCP()
gcp3.GCPPixel = 20
gcp3.GCPLine = 0
gcp3.GCPX = 441920.000
gcp3.GCPY = 3751320.000
src_gcps = (gcp1, gcp2, gcp3)
ds.SetGCPs(src_gcps, src_ds.GetProjectionRef())
tr = gdal.Transformer(ds, None, ['METHOD=GCP_POLYNOMIAL'])
(_, ref_pnt) = tr.TransformPoint(0, 20, 10)
ds.BuildOverviews('NEAR', overviewlist=[2, 4])
ds = None
ds = gdal.OpenEx('tmp/byte.tif', open_options=['OVERVIEW_LEVEL=0'])
gcps = ds.GetGCPs()
for i in range(3):
if gcps[i].GCPPixel != src_gcps[i].GCPPixel / 2 or gcps[i].GCPLine != src_gcps[i].GCPLine / 2 or \
gcps[i].GCPX != src_gcps[i].GCPX or gcps[i].GCPY != src_gcps[i].GCPY:
gdaltest.post_reason('fail')
return 'fail'
# Really check that the transformer works
tr = gdal.Transformer(ds, None, ['METHOD=GCP_POLYNOMIAL'])
(_, pnt) = tr.TransformPoint(0, 20 / 2.0, 10 / 2.0)
for i in range(3):
if abs(ref_pnt[i] - pnt[i]) > 1e-5:
gdaltest.post_reason('fail')
print(ref_pnt)
print(pnt)
return 'fail'
ds = None
return 'success'
def processImages(self, layerWMS, webScaleParamList, outputFolder):
scaleFeaturesDict = self.featuresByScale[self.scaleSelected]
width, height, ncol, nrow = webScaleParamList
for feat in scaleFeaturesDict.keys():
bboxStr = scaleFeaturesDict[feat].asWktCoordinates().replace(
',', '').split(' ')
bbox = []
for i in bboxStr:
bbox.append(float(i))
temp_path = tempfile.TemporaryDirectory()
complete_image = Image.new('RGB', (width * ncol, height * nrow))
dx = (bbox[2] - bbox[0]) / ncol
dy = (bbox[3] - bbox[1]) / nrow
for column in range(ncol):
xmin = bbox[0] + dx * column
xmax = bbox[0] + dx * (column + 1)
for line in range(nrow):
ymin = bbox[3] - dy * (line + 1)
ymax = bbox[3] - dy * line
imageURL = "https://bdgex.eb.mil.br/mapcache?SERVICE=WMS&VERSION=1.1.1&REQUEST=GetMap&BBOX={},{},{},{}&SRS=EPSG:4326&WIDTH={}&HEIGHT={}&LAYERS={}&STYLES=,,,&FORMAT=image/png&DPI=96&MAP_RESOLUTION=96&FORMAT_OPTIONS=dpi:96&TRANSPARENT=TRUE".format(
xmin, ymin, xmax, ymax, width, height, layerWMS)
partialImage = requests.get(imageURL, allow_redirects=True)
temp_file = os.path.join(temp_path.name, 'temp_image.png')
open(temp_file, "wb").write(partialImage.content)
complete_image.paste(Image.open(temp_file),
(width * column, height * line))
complete_image.save(
os.path.join(temp_path.name, 'complete_image.png'))
outputFile = os.path.join(outputFolder, feat + ".tif")
p1 = gdal.GCP(bbox[0], bbox[1], 0, 0, height * nrow)
p2 = gdal.GCP(bbox[2], bbox[1], 0, width * ncol, height * nrow)
p3 = gdal.GCP(bbox[0], bbox[3], 0, 0, 0)
p4 = gdal.GCP(bbox[2], bbox[3], 0, width * ncol, 0)
opt = gdal.TranslateOptions(format='GTiff', GCPs=[p1, p2, p3, p4])
gdal.Translate(outputFile,
os.path.join(temp_path.name, 'complete_image.png'),
options=opt)
temp_path.cleanup()
processing.run("gdal:assignprojection", {
'INPUT': outputFile,
'CRS': "EPSG:4326"
})
return
def test_gdal_translate_lib_8():
gcpList = [gdal.GCP(440720.000, 3751320.000, 0, 0, 0), gdal.GCP(441920.000, 3751320.000, 0, 20, 0), gdal.GCP(441920.000, 3750120.000, 0, 20, 20), gdal.GCP(440720.000, 3750120.000, 0, 0, 20)]
ds = gdal.Open('../gcore/data/byte.tif')
ds = gdal.Translate('tmp/test8.tif', ds, outputSRS='EPSG:26711', GCPs=gcpList)
assert ds is not None
assert ds.GetRasterBand(1).Checksum() == 4672, 'Bad checksum'
gcps = ds.GetGCPs()
assert len(gcps) == 4, 'GCP count wrong.'
assert ds.GetGCPProjection().find('26711') != -1, 'Bad GCP projection.'
ds = None
def executeTask(task, gcps, projection, records):
"""
threading function for computing reprojection of point subset
"""
# get geographic and tm projection objects
srs_s = Proj(init=projection['source'])
srs_t = Proj(init=projection['target'])
gcps_warp = []
# process subset of gcp list
idx = task['offset']
num_gcps = len(gcps['pixel'])
count = 0
while idx <= (task['offset'] + task['items']) and idx < num_gcps:
# reproject coordinates from source to target srs
x, y, z = transform(srs_s, srs_t, gcps['X'][idx],
gcps['Y'][idx], gcps['Z'][idx])
gcps_warp.append(
gdal.GCP(x, y, z, gcps['pixel'][idx], gcps['line'][idx]))
idx = idx + 1
count = count + 1
# copy to shared array
records[task['index']] = gcps_warp
return
def to_GCPList(self):
# get copy of tie points grid without no data
try:
GDF = self.CoRegPoints_table.loc[self.CoRegPoints_table.ABS_SHIFT != self.outFillVal, :].copy()
except AttributeError:
# self.CoRegPoints_table has no attribute 'ABS_SHIFT' because all points have been excluded
return []
if getattr(GDF, 'empty'): # GDF.empty returns AttributeError
return []
else:
# exclude all points flagged as outliers
if 'OUTLIER' in GDF.columns:
GDF = GDF[GDF.OUTLIER.__eq__(False)].copy()
avail_TP = len(GDF)
if not avail_TP:
# no point passed all validity checks
return []
if avail_TP > 7000:
GDF = GDF.sample(7000)
warnings.warn('By far not more than 7000 tie points can be used for warping within a limited '
'computation time (due to a GDAL bottleneck). Thus these 7000 points are randomly chosen '
'out of the %s available tie points.' % avail_TP)
# calculate GCPs
GDF['X_UTM_new'] = GDF.X_UTM + GDF.X_SHIFT_M
GDF['Y_UTM_new'] = GDF.Y_UTM + GDF.Y_SHIFT_M
GDF['GCP'] = GDF.apply(lambda GDF_row: gdal.GCP(GDF_row.X_UTM_new, GDF_row.Y_UTM_new, 0,
GDF_row.X_IM, GDF_row.Y_IM), axis=1)
self.GCPList = GDF.GCP.tolist()
return self.GCPList
def offset_image(self, inImage, outImage, list_col_row, list_xy):
'''
根据影像的行列号及对应坐标，对影像进行偏移
:param inImage: 输入影像路径
:param outImage: 输入影像路径
:param list_col_row: 行列号的列表（元组）
:param list_xy: xy坐标的列表（元组
:return: 无返回值
'''
#gdal.GCP()是gdal中地面控制点的数据结构，顺序依次是：空间位置x,y,z,影像列号，行号
coordlist = []
if len(list_col_row) == len(list_xy):
print("构建GCPs列表......")
for i in range(len(list_col_row)):
coordlist.append(
gdal.GCP(list_xy[i][0], list_xy[i][1], 0,
list_col_row[i][0], list_col_row[i][1]))
# 根据脚点坐标进行配准
print("为影像写入GCPs......")
gdal.Translate("TempOut1.tif", inImage, GCPs=coordlist)
print("终极变换！")
gdal.Warp(outImage,
"TempOut1.tif",
format="GTiff",
srcNodata=0.0,
dstNodata=0.0,
dstSRS="EPSG:4326")
else:
print("行列号与xy坐标对数量不匹配，请检查！")
def test_envi_gcp():
filename = '/vsimem/test_envi_gcp.dat'
ds = gdal.GetDriverByName('ENVI').Create(filename, 1, 1)
gcp = gdal.GCP()
gcp.GCPPixel = 1
gcp.GCPLine = 2
gcp.GCPX = 3
gcp.GCPY = 4
ds.SetGCPs([gcp], None)
ds = None
gdal.Unlink(filename + ".aux.xml")
ds = gdal.Open(filename)
assert ds.GetGCPCount() == 1
gcps = ds.GetGCPs()
assert len(gcps) == 1
gcp = gcps[0]
ds = None
assert gcp.GCPPixel == 1
assert gcp.GCPLine == 2
assert gcp.GCPX == 3
assert gcp.GCPY == 4
gdal.GetDriverByName('ENVI').Delete(filename)
def convert(self):
options=self.map.options
if options.after_name:
name_patt=self.name
elif options.after_map:
name_patt=self.map.file
else:
name_patt=self.img_file
base = dst_path(name_patt, options.dst_dir)
if options.long_name:
base += ' - ' + "".join([c for c in self.name
if c .isalpha() or c.isdigit() or c in '-_.() '])
dst_dir=os.path.split(base)[0]
out_format='VRT'
ext='.'+out_format.lower()
try:
start_dir=os.getcwd()
if dst_dir:
os.chdir(dst_dir)
dst_file = os.path.abspath(os.path.basename(base+ext)) # output file
dst_drv = gdal.GetDriverByName(out_format)
dst_ds = dst_drv.CreateCopy(
dst_file.encode(locale.getpreferredencoding()),
self.raster_ds,
0
)
dst_ds.SetProjection(self.srs)
#double x = 0.0, double y = 0.0, double z = 0.0, double pixel = 0.0,
#double line = 0.0, char info = "", char id = ""
gcps=[gdal.GCP(c[0],c[1],0,p[0],p[1],'',i) for i,p,c in self.refs]
dst_ds.SetGCPs(gcps,self.refs.srs())
dst_geotr=gdal.GCPsToGeoTransform(gcps) # if len(gcps) < 5 else (0.0, 1.0, 0.0, 0.0, 0.0, 1.0)
dst_ds.SetGeoTransform(dst_geotr)
poly,gmt_data=self.cut_poly(dst_ds)
if poly:
dst_ds.SetMetadataItem('CUTLINE',poly)
if self.name:
dst_ds.SetMetadataItem('DESCRIPTION',self.name.encode('utf-8'))
dst_ds = None # close dataset
# re_sub_file(dst_file, [
# ('^.*<GeoTransform>.*\n',''),
# ('^.*<SRS>.*\n','')
# ])
finally:
self.raster_ds = None
os.chdir(start_dir)
if options.get_cutline: # print cutline then return
print poly
return
if gmt_data and options.cut_file: # create shapefile with a cut polygon
with open(base+'.gmt','w+') as f:
f.write(gmt_data)
return dst_file
def create_gcp_list(latitude, longitude, rescaling_coef=1.0):
n_gcp = 150 # Maximum allow GCPs
percentage_gcp_per_line = 0.2
latitude_ds = gdal.OpenShared(str(latitude))
longitude_ds = gdal.OpenShared(str(longitude))
lat = (latitude_ds.GetRasterBand(1)).ReadAsArray().astype(np.float32)
lon = (longitude_ds.GetRasterBand(1)).ReadAsArray().astype(np.float32)
gcp_list_o = []
pas_pixel = np.int(latitude_ds.RasterXSize * percentage_gcp_per_line) + 1
pas_line = np.int((latitude_ds.RasterYSize * latitude_ds.RasterXSize) /
(n_gcp * pas_pixel)) + 1
print latitude_ds.RasterXSize / pas_pixel, ' ', latitude_ds.RasterYSize / pas_line
k = 0
for line in range(0, latitude_ds.RasterYSize - 1, pas_line):
for px in range(0, latitude_ds.RasterXSize - 1, pas_pixel):
gcp = gdal.GCP(
np.multiply(np.double(lon[line][px]), rescaling_coef),
np.multiply(np.double(lat[line][px]), rescaling_coef), 0, (px),
(line))
gcp_list_o.append(gcp)
k = k + 1
latitude_ds = None
longitude_ds = None
return gcp_list_o #Gdal osgeo gcp object
def test_tps_1():
drv = gdal.GetDriverByName('MEM')
ds = drv.Create('foo', 2, 2)
gcp_list = [
gdal.GCP(0, 0, 0, 0, 0),
gdal.GCP(0, 50, 0, 0, 50),
gdal.GCP(50, 0, 0, 50, 0),
gdal.GCP(50, 50, 0, 50, 50),
gdal.GCP(0 * 25, 0 * 25, 0, 25, 25),
]
ds.SetGCPs(gcp_list, osr.GetUserInputAsWKT('WGS84'))
utm_wkt = osr.GetUserInputAsWKT('+proj=utm +zone=11 +datum=WGS84')
with gdaltest.error_handler():
transformer = gdal.Transformer(
ds, None, ['DST_SRS=' + utm_wkt, 'METHOD=GCP_TPS'])
assert transformer is None
def SetGCPsToGeoTransform(cornerPointUL, cornerPointUR, cornerPointLR,
cornerPointLL, frameCenterLon, frameCenterLat):
''' Make Geotranform from pixel to lon lat coordinates '''
gcps = []
global gcornerPointUL
gcornerPointUL = cornerPointUL
global gcornerPointUR
gcornerPointUR = cornerPointUR
global gcornerPointLR
gcornerPointLR = cornerPointLR
global gcornerPointLL
gcornerPointLL = cornerPointLL
global gframeCenterLat
gframeCenterLat = frameCenterLat
global gframeCenterLon
gframeCenterLon = frameCenterLon
Height = 0
gcp = gdal.GCP(cornerPointUL[1], cornerPointUL[0], Height, 0, 0,
"Corner Upper Left", "1")
gcps.append(gcp)
gcp = gdal.GCP(cornerPointUR[1], cornerPointUR[0], Height, xSize, 0,
"Corner Upper Right", "2")
gcps.append(gcp)
gcp = gdal.GCP(cornerPointLR[1], cornerPointLR[0], Height, xSize, ySize,
"Corner Lower Right", "3")
gcps.append(gcp)
gcp = gdal.GCP(cornerPointLL[1], cornerPointLL[0], Height, 0, ySize,
"Corner Lower Left", "4")
gcps.append(gcp)
gcp = gdal.GCP(frameCenterLon, frameCenterLat, Height, xSize / 2,
ySize / 2, "Center", "5")
gcps.append(gcp)
global geotransform
geotransform = gdal.GCPsToGeoTransform(gcps)
if geotransform is None:
qgsu.showUserAndLogMessage(QCoreApplication.translate(
"QgsFmvUtils", 'Unable to extract a geotransform.'),
onlyLog=True)
return
def CopyDatasetInfo( src, dst, xoff=0, yoff=0 ):
"""
Copy georeferencing information and metadata from one dataset to another.
src: input dataset
dst: output dataset - It can be a ROI -
xoff, yoff: dst's offset with respect to src in pixel/line.
Notes: Destination dataset must have update access. Certain formats
do not support creation of geotransforms and/or gcps.
"""
dst.SetMetadata( src.GetMetadata() )
#Check for geo transform
gt = src.GetGeoTransform()
if gt != (0,1,0,0,0,1):
dst.SetProjection( src.GetProjectionRef() )
if (xoff == 0) and (yoff == 0):
dst.SetGeoTransform( gt )
else:
ngt = [gt[0],gt[1],gt[2],gt[3],gt[4],gt[5]]
ngt[0] = gt[0] + xoff*gt[1] + yoff*gt[2];
ngt[3] = gt[3] + xoff*gt[4] + yoff*gt[5];
dst.SetGeoTransform( ( ngt[0], ngt[1], ngt[2], ngt[3], ngt[4], ngt[5] ) )
#Check for GCPs
elif src.GetGCPCount() > 0:
if (xoff == 0) and (yoff == 0):
dst.SetGCPs( src.GetGCPs(), src.GetGCPProjection() )
else:
gcps = src.GetGCPs()
#Shift gcps
new_gcps = []
for gcp in gcps:
ngcp = gdal.GCP()
ngcp.GCPX = gcp.GCPX
ngcp.GCPY = gcp.GCPY
ngcp.GCPZ = gcp.GCPZ
ngcp.GCPPixel = gcp.GCPPixel - xoff
ngcp.GCPLine = gcp.GCPLine - yoff
ngcp.Info = gcp.Info
ngcp.Id = gcp.Id
new_gcps.append(ngcp)
try:
dst.SetGCPs( new_gcps , src.GetGCPProjection() )
except:
print ("Failed to set GCPs")
return
return
def test_mem_1():
#######################################################
# Setup dataset
drv = gdal.GetDriverByName('MEM')
gdaltest.mem_ds = drv.Create('mem_1.mem', 50, 3)
ds = gdaltest.mem_ds
assert ds.GetProjection() == '', 'projection wrong'
assert ds.GetGeoTransform(can_return_null=True) is None, 'geotransform wrong'
raw_data = b''.join(struct.pack('f', v) for v in range(150))
ds.WriteRaster(0, 0, 50, 3, raw_data,
buf_type=gdal.GDT_Float32,
band_list=[1])
wkt = gdaltest.user_srs_to_wkt('EPSG:26711')
ds.SetProjection(wkt)
gt = (440720, 5, 0, 3751320, 0, -5)
ds.SetGeoTransform(gt)
band = ds.GetRasterBand(1)
band.SetNoDataValue(-1.0)
# Set GCPs()
wkt_gcp = gdaltest.user_srs_to_wkt('EPSG:4326')
gcps = [gdal.GCP(0, 1, 2, 3, 4)]
ds.SetGCPs([], "")
ds.SetGCPs(gcps, wkt_gcp)
ds.SetGCPs([], "")
ds.SetGCPs(gcps, wkt_gcp)
ds.SetGCPs(gcps, wkt_gcp)
#######################################################
# Verify dataset.
assert band.GetNoDataValue() == -1.0, 'no data is wrong'
assert ds.GetProjection() == wkt, 'projection wrong'
assert ds.GetGeoTransform() == gt, 'geotransform wrong'
assert band.Checksum() == 1531, 'checksum wrong'
assert ds.GetGCPCount() == 1, 'GetGCPCount wrong'
assert len(ds.GetGCPs()) == 1, 'GetGCPs wrong'
assert ds.GetGCPProjection() == wkt_gcp, 'GetGCPProjection wrong'
assert band.DeleteNoDataValue() == 0, 'wrong return code'
assert band.GetNoDataValue() is None, 'got nodata value whereas none was expected'
gdaltest.mem_ds = None
def _list2gcps(src_list):
gcp_list = []
for src_tuple in src_list:
gcp = gdal.GCP()
gcp.GCPPixel = src_tuple[0]
gcp.GCPLine = src_tuple[1]
gcp.GCPX = src_tuple[2]
gcp.GCPY = src_tuple[3]
gcp_list.append(gcp)
return gcp_list
def georeference_image(image_input_filepath, image_output_filepath, image_width, image_height, map_bottom, map_top, map_left, map_right):
dataset = gdal.Open(str(image_input_filepath), gdal.GA_Update)
sr = osr.SpatialReference()
sr.ImportFromEPSG(4326)
# Enter the GCPs
# Format: [map x-coordinate(longitude)], [map y-coordinate (latitude)], [elevation],
# [image column index(x)], [image row index (y)]
gcps = [
gdal.GCP(map_left, map_bottom, 0, 0, image_height),
gdal.GCP(map_right, map_bottom, 0, image_width, image_height),
gdal.GCP(map_right, map_top, 0, image_width, 0),
gdal.GCP(map_left, map_top, 0, 0, 0)]
# Apply the GCPs to the open output file:
dataset.SetGCPs(gcps, sr.ExportToWkt())
gdal.Warp(str(image_output_filepath), dataset, dstSRS='EPSG:4326', format='gtiff')
# Close the output file in order to be able to work with it in other programs:
dataset = None
def test_overviewds_3():
src_ds = gdal.Open('data/byte.tif')
ds = gdal.GetDriverByName('GTiff').CreateCopy('tmp/byte.tif', src_ds)
ds.SetGeoTransform([0, 1, 0, 0, 0, 1]) # cancel geotransform
gcp1 = gdal.GCP()
gcp1.GCPPixel = 0
gcp1.GCPLine = 0
gcp1.GCPX = 440720.000
gcp1.GCPY = 3751320.000
gcp2 = gdal.GCP()
gcp2.GCPPixel = 0
gcp2.GCPLine = 20
gcp2.GCPX = 440720.000
gcp2.GCPY = 3750120.000
gcp3 = gdal.GCP()
gcp3.GCPPixel = 20
gcp3.GCPLine = 0
gcp3.GCPX = 441920.000
gcp3.GCPY = 3751320.000
src_gcps = (gcp1, gcp2, gcp3)
ds.SetGCPs(src_gcps, src_ds.GetProjectionRef())
tr = gdal.Transformer(ds, None, ['METHOD=GCP_POLYNOMIAL'])
(_, ref_pnt) = tr.TransformPoint(0, 20, 10)
ds.BuildOverviews('NEAR', overviewlist=[2, 4])
ds = None
ds = gdal.OpenEx('tmp/byte.tif', open_options=['OVERVIEW_LEVEL=0'])
gcps = ds.GetGCPs()
for i in range(3):
assert (gcps[i].GCPPixel == src_gcps[i].GCPPixel / 2 and gcps[i].GCPLine == src_gcps[i].GCPLine / 2 and \
gcps[i].GCPX == src_gcps[i].GCPX and gcps[i].GCPY == src_gcps[i].GCPY)
# Really check that the transformer works
tr = gdal.Transformer(ds, None, ['METHOD=GCP_POLYNOMIAL'])
(_, pnt) = tr.TransformPoint(0, 20 / 2.0, 10 / 2.0)
for i in range(3):
assert abs(ref_pnt[i] - pnt[i]) <= 1e-5
ds = None
def tps_1():
drv = gdal.GetDriverByName('MEM')
ds = drv.Create('foo', 2, 2)
gcp_list = [
gdal.GCP(0, 0, 0, 0, 0),
gdal.GCP(0, 50, 0, 0, 50),
gdal.GCP(50, 0, 0, 50, 0),
gdal.GCP(50, 50, 0, 50, 50),
gdal.GCP(0 * 25, 0 * 25, 0, 25, 25),
]
ds.SetGCPs(gcp_list, osr.GetUserInputAsWKT('WGS84'))
utm_wkt = osr.GetUserInputAsWKT('+proj=utm +zone=11 +datum=WGS84')
transformer = gdal.Transformer(ds, None,
['DST_SRS=' + utm_wkt, 'METHOD=GCP_TPS'])
if transformer is None or gdal.GetLastErrorType() == 0:
return 'fail'
return 'success'
def transform_gcps(gcps, imageHeight, dst):
src = osr.SpatialReference()
src.ImportFromEPSG(4326)
tr = osr.CoordinateTransformation(src, dst)
ret = []
for gcp in gcps:
x, y, z = tr.TransformPoint(gcp.ground.get_x(), gcp.ground.get_y(),
0.0)
ret.append(
gdal.GCP(x, y, z, gcp.image.get_x(),
imageHeight - gcp.image.get_y()))
return ret