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