def compose_two_image(self, main_image, second_image, nodata):
if io_function.is_file_exist(main_image) is False:
return False
if io_function.is_file_exist(second_image) is False:
return False
main_img = RSImageclass()
if main_img.open(main_image) is False:
return False
width_main = main_img.GetWidth()
height_main = main_img.GetHeight()
bandcount_main = main_img.GetBandCount()
sec_img = RSImageclass()
if sec_img.open(second_image) is False:
return False
width_sec = sec_img.GetWidth()
height_sec = sec_img.GetHeight()
bandcount_sec = sec_img.GetBandCount()
if width_main != width_sec or height_main != height_sec or bandcount_main != bandcount_sec:
basic.outputlogMessage(
'Error: The dimension of two composed images is different')
return False
if main_img.GetGDALDataType() != sec_img.GetGDALDataType(
) or main_img.GetGDALDataType() != 6:
basic.outputlogMessage(
'Error: The Data type of two composed imagaes is different or is not float'
)
return False
outputfile = io_function.get_name_by_adding_tail(main_image, 'comp')
imagenew = RSImageclass()
width = width_main
height = height_main
if not imagenew.New(outputfile, width, height, bandcount_main,
main_img.GetGDALDataType()):
return False
for i in range(0, bandcount_main):
bandindex = i + 1
band_main_str = main_img.ReadbandData(bandindex, 0, 0, width,
height,
main_img.GetGDALDataType())
band_sec_str = sec_img.ReadbandData(bandindex, 0, 0, width, height,
sec_img.GetGDALDataType())
band_main_data = struct.unpack('f' * width * height, band_main_str)
band_main_numpy = numpy.asarray(band_main_data)
band_sec_data = struct.unpack('f' * width * height, band_sec_str)
band_sec_numpy = numpy.asarray(band_sec_data)
compose_loc = numpy.where(
(numpy.fabs(band_main_numpy - nodata) < 0.0001)
& (numpy.fabs(band_sec_numpy - nodata) > 0.0001))
band_main_numpy[compose_loc] = band_sec_numpy[compose_loc]
basic.outputlogMessage('outputfortest2: compose_loc_num = %d' %
numpy.array(compose_loc).size)
templist = band_main_numpy.tolist()
band_composed_str = struct.pack('%sf' % width * height, *templist)
if imagenew.WritebandData(bandindex, 0, 0, width, height,
band_composed_str,
imagenew.GetGDALDataType()) is False:
return False
imagenew.SetBandNoDataValue(bandindex, nodata)
imagenew.SetGeoTransform(main_img.GetGeoTransform())
imagenew.SetProjection(main_img.GetProjection())
main_img = None
sec_img = None
imagenew = None
return outputfile
def coregistration_siftGPU(basefile, warpfile, bkeepmidfile, xml_obj):
tiepointfile = '0_1_after.pts'
if os.path.isfile(tiepointfile):
basic.outputlogMessage(
'warning:tie points already exist in dir, skip get_tie_points_by_ZY3ImageMatch'
)
else:
tiepointfile = tiepoints.get_tie_points_by_ZY3ImageMatch(
basefile, warpfile, bkeepmidfile)
if tiepointfile is False:
basic.outputlogMessage('Get tie points by ZY3ImageMatch failed')
return False
xml_obj.add_coregistration_info('tie_points_file', tiepointfile)
#draw tie points rms vector on base image
result_rms_files = '0_1_fs.txt'
tiepoint_vector_ = 'tiepoints_vector.png'
output_tie_points_vector_on_base_image(basefile, result_rms_files,
tiepoint_vector_)
xml_obj.add_coregistration_info('tie_points_drawed_image',
os.path.abspath(tiepoint_vector_))
#check the tie points
try:
rms_files_obj = open(result_rms_files, 'r')
rms_lines = rms_files_obj.readlines()
if len(rms_lines) < 2:
basic.outputlogMessage("%s do not contain tie points information" %
os.path.abspath(result_rms_files))
return False
required_point_count = parameters.get_required_minimum_tiepoint_number(
)
acceptable_rms = parameters.get_acceptable_maximum_RMS()
xml_obj.add_coregistration_info('required_tie_point_count',
str(required_point_count))
xml_obj.add_coregistration_info('acceptable_rms', str(acceptable_rms))
try:
digit_str = re.findall('\d+', rms_lines[0])
tiepoints_count = int(digit_str[0])
xml_obj.add_coregistration_info('tie_points_count',
str(tiepoints_count))
if tiepoints_count < required_point_count:
basic.outputlogMessage(
"ERROR: tiepoints count(%d) is less than required one(%d)"
% (tiepoints_count, required_point_count))
return False
digit_str = re.findall('\d+\.?\d*', rms_lines[1])
totalrms_value = float(digit_str[2])
xml_obj.add_coregistration_info('total_rms_value',
str(totalrms_value))
if totalrms_value > acceptable_rms:
basic.outputlogMessage(
"ERROR:Total RMS(%f) exceeds the acceptable one(%f)" %
(totalrms_value, acceptable_rms))
return False
except ValueError:
return basic.outputlogMessage(str(ValueError))
return False
rms_files_obj.close()
except IOError:
syslog.outputlogMessage(str(IOError))
return False
baseimg = RSImageclass()
if not baseimg.open(basefile):
return False
proj = baseimg.GetProjection()
geotransform = baseimg.GetGeoTransform()
xres = baseimg.GetXresolution()
yres = baseimg.GetYresolution()
try:
Outputtiff = setGCPsfromptsFile(warpfile, proj, geotransform,
tiepointfile)
except RuntimeError as e:
basic.outputlogMessage('setGCPsfromptsFile failed: ')
basic.outputlogMessage(str(e))
return False
if Outputtiff is False:
return False
else:
basic.outputlogMessage('setGCPsfromptsFile completed, Out file: ' +
Outputtiff)
# if not bkeepmidfile:
# os.remove(warpfile)
xml_obj.add_coregistration_info('setted_gcps_file', Outputtiff)
#warp image
warpresultfile = Outputtiff.split('.')[0] + '_warp.tif'
#-order 1 -tps
#-tr xres yres: set output file resolution (in target georeferenced units)
# set resolution as the same as base image is important
order_number = parameters.get_gdalwarp_polynomial_order()
xml_obj.add_coregistration_info('warp_polynomial_order_number',
str(order_number))
if order_number is False:
return False
CommandString = 'gdalwarp ' + ' -order ' + str(
order_number) + ' -r bilinear -tr ' + str(xres) + ' ' + str(
yres) + ' ' + Outputtiff + ' ' + warpresultfile
basic.outputlogMessage(CommandString)
(status, result) = commands.getstatusoutput(CommandString)
basic.outputlogMessage(result)
if not os.path.isfile(warpresultfile):
return False
if not bkeepmidfile:
os.remove(Outputtiff)
return warpresultfile
def convert_orthometricH_to_elliopsoidalH(output, orthometricH_file,
geoidHfile):
if io_function.is_file_exist(
orthometricH_file) is False or io_function.is_file_exist(
geoidHfile) is False:
return False
orthom_obj = RSImageclass()
if orthom_obj.open(orthometricH_file) is False:
return False
geoidH_obj = RSImageclass()
if geoidH_obj.open(geoidHfile) is False:
return False
Nodata = parameters.get_nodata_value()
x_res = orthom_obj.GetXresolution()
y_res = orthom_obj.GetYresolution()
x_res_geoid = geoidH_obj.GetXresolution()
y_res_geoid = geoidH_obj.GetYresolution()
orthom_prj = orthom_obj.GetProjection()
geoid_prj = geoidH_obj.GetProjection()
#check projection and resolution, and convert it if need
#use orthometricH_file as base image
if x_res != x_res_geoid or y_res != y_res_geoid or orthom_prj != geoid_prj:
geoid_convertfile = io_function.get_name_by_adding_tail(
geoidHfile, 'tran')
if os.path.isfile(geoid_convertfile) is False:
if RSImageProcess.transforms_raster_srs(
geoidHfile, orthom_prj, geoid_convertfile, abs(x_res),
abs(y_res)) is False:
return False
else:
basic.outputlogMessage(geoid_convertfile + ' already exist')
#sub geoidHfile base on the small one
(ulx, uly, lrx,
lry) = RSImageProcess.get_image_proj_extent(orthometricH_file)
if ulx is False:
return False
geoid_convertfile_sub = io_function.get_name_by_adding_tail(
geoid_convertfile, 'sub')
if os.path.isfile(geoid_convertfile_sub) is False:
result = RSImageProcess.subset_image_projwin(geoid_convertfile_sub,
geoid_convertfile, ulx,
uly, lrx, lry)
if result is False:
return False
else:
basic.outputlogMessage(geoid_convertfile_sub + ' already exist')
##caculate elliopsoidal height
# orthometricH_data = img_pro.Read_Image_band_data_to_numpy_array_all_pixel(1,orthometricH_file)
# img_pro = None
# img_pro = RSImgProclass(syslog)
# geoidH_data = img_pro.Read_Image_band_data_to_numpy_array_all_pixel(1,geoid_convertfile_sub)
# img_pro = None
# if orthometricH_data.shape != geoidH_data.shape:
# syslog.outputlogMessage("the shape of orthometricH_data and geoidH_data is different")
# return False
#
# nodata = parameters.get_nodata_value(syslog)
# width = orthom_obj.GetWidth()
# height = orthom_obj.GetHeight()
# orthometricH_data = orthometricH_data.astype(numpy.float32)
# geoidH_data = geoidH_data.astype(numpy.float32)
# elliopsoidalH = orthometricH_data + geoidH_data
# elliopsoidalH = elliopsoidalH.reshape(height,width)
#
# RSImageProcess.save_numpy_2d_array_to_image_tif(output,elliopsoidalH,6,\
# orthom_obj.GetGeoTransform(),orthom_obj.GetProjection(),nodata,syslog)
#
# orthom_obj = None
# geoidH_obj = None
CommandString = 'gdal_calc.py -A '+orthometricH_file + ' -B ' + geoid_convertfile_sub +\
' --NoDataValue='+str(Nodata) +' --outfile='+output + ' --calc="A+B"'
if RSImageProcess.exec_commond_string_one_file(CommandString,
output) is False:
return False
else:
basic.outputlogMessage(
"converting orthometric Height to elliopsoidal Height is completed"
)
return True
def calculate_terrain_offset(output, dem_file, image_file, exec_dir,
bkeepmidfile):
if io_function.is_file_exist(
image_file) is False or io_function.is_file_exist(
dem_file, ) is False:
return False
exefile = os.path.join(exec_dir, 'geometry_pro')
nodata = parameters.get_nodata_value()
(centre_lat, centre_lon) = RSImage.get_image_latlon_centre(image_file)
if centre_lat is False or centre_lon is False:
return False
image_obj = RSImageclass()
if image_obj.open(image_file) is False:
return False
dem_obj = RSImageclass()
if dem_obj.open(dem_file) is False:
return False
x_res = image_obj.GetXresolution()
y_res = image_obj.GetYresolution()
x_res_dem = dem_obj.GetXresolution()
y_res_dem = dem_obj.GetYresolution()
image_prj = image_obj.GetProjection()
dem_prj = dem_obj.GetProjection()
#check projection and resolution, and convert it if need
#use orthometricH_file as base image
dem_convertedfile = io_function.get_name_by_adding_tail(dem_file, 'tran')
if x_res != x_res_dem or y_res != y_res_dem or image_prj != dem_prj:
if os.path.isfile(dem_convertedfile) is False:
if map_projection.transforms_raster_srs(
dem_file, image_prj, dem_convertedfile, abs(x_res),
abs(y_res)) is False:
return False
if os.path.isfile(dem_convertedfile):
dem_file = dem_convertedfile
#sub dem file
(ulx, uly, lrx, lry) = RSImage.get_image_proj_extent(image_file)
if ulx is False:
return False
tail = os.path.splitext(os.path.basename(image_file))[0]
dem_file_sub = io_function.get_name_by_adding_tail(dem_file, tail)
if os.path.isfile(dem_file_sub) is False:
if RSImageProcess.subset_image_projwin(dem_file_sub, dem_file, ulx,
uly, lrx, lry) is False:
return False
#calculateing terrain contains a lot of I/O operations, the parallel computing will slow down it
nblockwidth = 8000
nblcckheight = 8000
njobs = 1
logfile = 'cal_terrain_offset_log.txt'
CommandString = exefile \
+ ' -i ' + image_file + ' -d ' + dem_file_sub \
+ ' -o ' + output + ' -n ' + str(nodata)\
+ ' -w ' + str(nblockwidth) + ' -h ' + str(nblcckheight) + ' -j ' +str(njobs) \
+ ' --centre_lat=' + str(centre_lat) \
+ ' --logfile=' + logfile
basic.outputlogMessage(CommandString)
(status, result) = commands.getstatusoutput(CommandString)
basic.outputlogMessage(result)
if bkeepmidfile is False:
# if os.path.isfile(dem_convertedfile):
# io_function.delete_file_or_dir(dem_convertedfile)
if os.path.isfile(dem_file_sub):
io_function.delete_file_or_dir(dem_file_sub)
if os.path.isfile(output):
if os.path.getsize(output) > 0:
return output
else:
basic.outputlogMessage('error: the size of file %s is 0' %
os.path.basename(output))
return False
else:
return False
def get_geoimage_range_geoid_height(outputfile, ref_image):
#convert srs
ref_img_obj = RSImageclass()
if not ref_img_obj.open(ref_image):
return False
# x_res = ref_img_obj.GetXresolution()
# y_res = ref_img_obj.GetYresolution()
width = ref_img_obj.GetWidth()
height = ref_img_obj.GetHeight()
img_pro = RSImgProclass()
ref_image_data = img_pro.Read_Image_band_data_to_numpy_array_all_pixel(
1, ref_image)
if ref_image_data is False:
return False
nodata = parameters.get_nodata_value()
Image_array = ref_image_data.reshape(height, width)
start_x = ref_img_obj.GetStartX()
start_y = ref_img_obj.GetStartY()
resolution_x = ref_img_obj.GetXresolution()
resolution_y = ref_img_obj.GetYresolution()
ref_img_WKT = ref_img_obj.GetProjection()
# ref_img_WKT = RSImageProcess.get_raster_or_vector_srs_info_wkt(ref_image,syslog)
(i, j) = numpy.where(Image_array != nodata)
input_x = start_x + j * resolution_x
input_y = start_y + i * resolution_y
# srs_longlat_prj4 = '\'+proj=longlat +datum=WGS84 +no_defs\''
# intput_proj4 = RSImage.wkt_to_proj4(ref_img_WKT,syslog)
# intput_proj4 = RSImageProcess.get_raster_or_vector_srs_info_proj4(ref_image,syslog)
# map_projection.convert_points_coordinate_proj4(input_x,input_y,intput_proj4,srs_longlat_prj4,syslog)
srs_longlat_wkt = "GEOGCS[\"WGS 84\",DATUM[\"WGS_1984\",SPHEROID[\"WGS 84\",6378137,298.257223563]],PRIMEM[\"Greenwich\",0],UNIT[\"degree\",0.01745329251994328]]"
map_projection.convert_points_coordinate(input_x, input_y, ref_img_WKT,
srs_longlat_wkt)
tempsave_str = []
save_point_txt_file = 'TXTgeoid_' + os.path.splitext(
os.path.basename(ref_image))[0] + '.txt'
if os.path.isfile(save_point_txt_file):
file_object = open(save_point_txt_file, 'r')
savepoints = file_object.readlines()
for point in savepoints:
tempsave_str.append(point)
file_object.close()
io_function.delete_file_or_dir(save_point_txt_file)
file_object = open(save_point_txt_file, 'a')
nsize = Image_array.size
Image_array = Image_array.astype(numpy.float32)
for index in range(0, nsize):
lon_deg = input_x[index]
lat_deg = input_y[index]
if index < len(tempsave_str):
temp_point = tempsave_str[index].split()
value = float(temp_point[2])
else:
(LongitudeDeg, LongitudeMin, LongitudeSec) = degree_to_dms(lon_deg)
(LatitudeDeg, LatitudeMin, LatitudeSec) = degree_to_dms(lat_deg)
value = get_geoid_height(LatitudeDeg, LatitudeMin, LatitudeSec,
LongitudeDeg, LongitudeMin, LongitudeSec,
nodata)
if value is False:
break
saved_point = ('%f %f %f' % (lon_deg, lat_deg, value))
print saved_point
# tempsave_str.append(saved_point)
file_object.writelines(saved_point + '\n')
file_object.flush()
basic.outputlogMessage('Longitude=%f, Latitude=%f, geoid = %f' %
(lon_deg, lat_deg, value))
# Image_array[index] = value
Image_array[i[index], j[index]] = value
print(i[index], j[index], Image_array[i[index], j[index]])
file_object.close()
if index != (nsize - 1):
return False
#save geoid height
RSImageProcess.save_numpy_2d_array_to_image_tif(outputfile,Image_array,\
6,ref_img_obj.GetGeoTransform(),ref_img_WKT,nodata)
return True