def subset_image_baseimage(output_file,input_file,baseimage,same_res=False): """ subset a image base on the extent of another image Args: output_file:the result file input_file:the image need to subset baseimage:the base image which provide the extend for subset same_res: if true, then will resample the output to the resolution of baseimage, otherwise, keep the resolution Returns:True is successful, False otherwise """ (ulx,uly,lrx,lry) = RSImage.get_image_proj_extent(baseimage) if ulx is False: return False # check the save folder is valid or not save_dir = os.path.dirname(output_file) if len(save_dir) < 1: basic.outputlogMessage('output save to current folder') else: basic.outputlogMessage('result save to %s'%save_dir) img_obj = RSImageclass() if same_res: img_obj.open(baseimage) else: img_obj.open(input_file) # the resolution should keep the same xres = img_obj.GetXresolution() yres = img_obj.GetYresolution() img_obj=None if subset_image_projwin(output_file,input_file,ulx,uly,lrx,lry,xres=xres,yres=yres) is False: return False return True
def subset_image_by_shapefile(imagefile, shapefile, bkeepmidfile): """ subset an image by polygons contained in the shapefile Args: imagefile:input image file path shapefile:input shapefile contains polygon bkeepmidfile:indicate whether keep middle file Returns:output file name if succussful, False Otherwise """ if io_function.is_file_exist(imagefile) is False: return False if io_function.is_file_exist(shapefile) is False: return False Outfilename = io_function.get_name_by_adding_tail(imagefile, 'vsub') # ds = ogr.Open(shapefile) # lyr = ds.GetLayer(0) # lyr.ResetReading() # ft = lyr.GetNextFeature() # subprocess.call(['gdalwarp', imagefile, Outfilename, '-cutline', shapefile,\ # '-crop_to_cutline']) orgimg_obj = RSImageclass() if orgimg_obj.open(imagefile) is False: return False x_res = abs(orgimg_obj.GetXresolution()) y_res = abs(orgimg_obj.GetYresolution()) CommandString = 'gdalwarp ' + ' -tr ' + str(x_res) + ' ' + str( y_res ) + ' ' + imagefile + ' ' + Outfilename + ' -cutline ' + shapefile + ' -crop_to_cutline ' + ' -overwrite ' if basic.exec_command_string_one_file(CommandString, Outfilename) is False: return False # while ft: # country_name = ft.GetFieldAsString('admin') # outraster = imagefile.replace('.tif', '_%s.tif' % country_name.replace(' ', '_')) # subprocess.call(['gdalwarp', imagefile, Outfilename, '-cutline', shapefile, # '-crop_to_cutline', '-cwhere', "'admin'='%s'" % country_name]) # # ft = lyr.GetNextFeature() if not bkeepmidfile: io_function.delete_file_or_dir(imagefile) os.remove(imagefile) if io_function.is_file_exist(Outfilename): return Outfilename else: # basic.outputlogMessage(result) basic.outputlogMessage( 'The version of GDAL must be great than 2.0 in order to use the r option ' ) return False
def subset_image_by_shapefile(imagefile, shapefile, bkeepmidfile=True, overwrite=False, format='GTiff', save_path=None, resample_m='bilinear', src_nodata=None, dst_nondata=None, xres=None, yres=None, compress=None, tiled=None, bigtiff=None, thread_num=None): """ subset an image by polygons contained in the shapefile the shapefile and imagefile may have different projections, the gdalwarp can handle Args: imagefile:input image file path shapefile:input shapefile contains polygon bkeepmidfile:indicate whether keep middle file format: output format, default is GTiff, GeoTIFF File Format. Use "VRT": GDAL Virtual Format to save disk storage Returns:output file name if succussful, False Otherwise """ if io_function.is_file_exist(imagefile) is False: return False if io_function.is_file_exist(shapefile) is False: return False if save_path is None: Outfilename = io_function.get_name_by_adding_tail(imagefile, 'vsub') else: Outfilename = save_path # ds = ogr.Open(shapefile) # lyr = ds.GetLayer(0) # lyr.ResetReading() # ft = lyr.GetNextFeature() # subprocess.call(['gdalwarp', imagefile, Outfilename, '-cutline', shapefile,\ # '-crop_to_cutline']) if overwrite is False and os.path.isfile(Outfilename): basic.outputlogMessage('warning, crop file: %s already exist, skip' % Outfilename) return Outfilename orgimg_obj = RSImageclass() if orgimg_obj.open(imagefile) is False: return False if xres is None or yres is None: x_res = abs(orgimg_obj.GetXresolution()) y_res = abs(orgimg_obj.GetYresolution()) else: x_res = xres y_res = yres CommandString = 'gdalwarp -r %s '% resample_m+' -tr ' + str(x_res) + ' '+ str(y_res)+ ' -of ' + format + ' ' + \ imagefile +' ' + Outfilename +' -cutline ' +shapefile +' -crop_to_cutline ' + ' -overwrite ' if src_nodata != None: CommandString += ' -srcnodata %d ' % src_nodata if dst_nondata != None: CommandString += ' -dstnodata %d ' % dst_nondata if compress != None: CommandString += ' -co ' + 'compress=%s' % compress # lzw if tiled != None: CommandString += ' -co ' + 'TILED=%s' % tiled # yes if bigtiff != None: CommandString += ' -co ' + 'bigtiff=%s' % bigtiff # IF_SAFER if thread_num != None: CommandString += ' -multi -wo NUM_THREADS=%d ' % thread_num if basic.exec_command_string_one_file(CommandString, Outfilename) is False: return False # while ft: # country_name = ft.GetFieldAsString('admin') # outraster = imagefile.replace('.tif', '_%s.tif' % country_name.replace(' ', '_')) # subprocess.call(['gdalwarp', imagefile, Outfilename, '-cutline', shapefile, # '-crop_to_cutline', '-cwhere', "'admin'='%s'" % country_name]) # # ft = lyr.GetNextFeature() if not bkeepmidfile: io_function.delete_file_or_dir(imagefile) os.remove(imagefile) if io_function.is_file_exist(Outfilename): return Outfilename else: # basic.outputlogMessage(result) basic.outputlogMessage( 'The version of GDAL must be great than 2.0 in order to use the r option ' ) return False
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 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 prepare_gimpdem_for_Jakobshavn(workdir): nodata = parameters.get_nodata_value() #mosaics gimdem files os.chdir(workdir) gimpdem_file = ['gimpdem1_2.tif', 'gimpdem2_2.tif'] gimpdem_output = 'dem_gimp_jako.tif' if os.path.isfile(gimpdem_output) is False: if RSImageProcess.mosaics_images(gimpdem_file, gimpdem_output) is False: return False geoid_file = 'geoid_hegith_jako.tif' #convert srs img_temp = RSImageclass() if not img_temp.open(gimpdem_output): return False x_res = img_temp.GetXresolution() y_res = img_temp.GetYresolution() srs_UTM_prj4 = '\'+proj=utm +zone=22 +datum=WGS84 +units=m +no_defs\' ' gimpdem_utm = io_function.get_name_by_adding_tail(gimpdem_output, 'utm22') if os.path.isfile(gimpdem_utm) is False: if RSImageProcess.transforms_raster_srs(gimpdem_output, srs_UTM_prj4, gimpdem_utm, abs(x_res), abs(y_res)) is False: return False # print img_temp.GetGDALDataType(),type(img_temp.GetGDALDataType()) # print img_temp.GetProjection(),type(img_temp.GetProjection()) # print img_temp.GetGeoTransform(),type(img_temp.GetGeoTransform()) #get geoid_height # srs_longlat_wkt = "GEOGCS[\"WGS 84\",DATUM[\"WGS_1984\",SPHEROID[\"WGS 84\",6378137,298.257223563]],PRIMEM[\"Greenwich\",0],UNIT[\"degree\",0.01745329251994328]]" # srs_longlat_prj4 = '\'+proj=longlat +datum=WGS84 +no_defs\' ' # image = RSImageclass(syslog) # if not image.open(gimpdem_utm): # return False # # img_pro = RSImgProclass(syslog) # dem_data = img_pro.Read_Image_band_data_to_numpy_array_all_pixel(1,gimpdem_utm) # if dem_data is False: # return False # # # geoid_height = geoid_height + -9999 # geoid_utm_file = basic.get_name_by_adding_tail(geoid_file,'tran',syslog) # if RSImageProcess.transforms_raster_srs_to_base_image(geoid_file,gimpdem_utm,geoid_utm_file,\ # x_res,y_res,syslog) is False: # return False # geoid_height = img_pro.Read_Image_band_data_to_numpy_array_all_pixel(1,geoid_utm_file) # if geoid_height is False: # return False # # #get ellipsoidal height # Image_array = dem_data + geoid_height # gimpdem_utm_elli = basic.get_name_by_adding_tail(gimpdem_utm,'elli',syslog) # RSImageProcess.save_numpy_2d_array_to_image_tif(gimpdem_utm_elli,Image_array,\ # image.GetGDALDataType(),image.GetGeoTransform(),image.GetProjection(),nodata) # image = None # img_pro = None return True
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 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