diff --git a/.idea/misc.xml b/.idea/misc.xml index 70a0a935..abf6bf18 100644 --- a/.idea/misc.xml +++ b/.idea/misc.xml @@ -1,4 +1,7 @@ + + \ No newline at end of file diff --git a/Ortho/OrthOne.spec b/Ortho/OrthOne.spec deleted file mode 100644 index 925f5ec9..00000000 --- a/Ortho/OrthOne.spec +++ /dev/null @@ -1,49 +0,0 @@ -# -*- mode: python ; coding: utf-8 -*- - - -block_cipher = None - - -a = Analysis( - ['OrthoMain.py'], - pathex=['.'], - binaries=[], - datas=[], - hiddenimports=[], - hookspath=[], - runtime_hooks=[], - excludes=[], - win_no_prefer_redirects=False, - win_private_assemblies=False, - cipher=block_cipher, - noarchive=False, -) -pyz = PYZ(a.pure, a.zipped_data, cipher=block_cipher) - -exe = EXE( - pyz, - a.scripts, - [], - exclude_binaries=True, - name='OrthOne', - debug=False, - bootloader_ignore_signals=False, - strip=False, - upx=True, - console=True, - disable_windowed_traceback=False, - argv_emulation=False, - target_arch=None, - codesign_identity=None, - entitlements_file=None, -) -coll = COLLECT( - exe, - a.binaries, - a.zipfiles, - a.datas, - strip=False, - upx=True, - upx_exclude=[], - name='OrthOne', -) diff --git a/Ortho/Ortho.xml b/Ortho/Ortho.xml index ed1ab405..9332773f 100644 --- a/Ortho/Ortho.xml +++ b/Ortho/Ortho.xml @@ -45,7 +45,7 @@ File tar.gz Cal - F:\MicroWorkspace\def_GF3\GF3_KSC_FSII_036108_E120.1_N31.0_20230619_L1A_VHVV_L10006793347.tar.gz + F:\MicroWorkspace\原老师新增干涉数据20240413\GF3_SYC_FSII_036654_E120.0_N30.7_20230727_L1A_HHHV_L10006808388.tar.gz True False File @@ -92,7 +92,7 @@ File tar.gz Cal - D:\micro\WorkSpace\ortho\Output\GF3_KSC_FSII_036108_E120.1_N31.0_20230619_L1A_VHVV_L10006793347-ortho.tar.gz + D:\micro\WorkSpace\ortho\Output\GF3_SYC_FSII_036654_E120.0_N30.7_20230727_L1A_HHHV_L10006808388-ortho.tar.gz DEFAULT DEFAULT DEFAULT diff --git a/Ortho/OrthoMain.py b/Ortho/OrthoMain.py index 74cd0d42..6dce9eac 100644 --- a/Ortho/OrthoMain.py +++ b/Ortho/OrthoMain.py @@ -384,7 +384,7 @@ class OrthoMain: if CorrectMethod.get('CorrectMethod') == '1' or CorrectMethod.get('CorrectMethod') == 1: logger.info("CorrectMethod is RPC!") - return self.RPC_process_handle() + return self.RD_process_handle() elif CorrectMethod.get('CorrectMethod') == '2' or CorrectMethod.get('CorrectMethod') == 2: logger.info("CorrectMethod is RD!") @@ -393,8 +393,6 @@ class OrthoMain: else: raise Exception('No CorrectMethod') - - def RPC_process_handle(self): logger.info(datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')) @@ -662,6 +660,8 @@ class OrthoMain: if file_type in ["xml"]: output = os.path.join(self.__workspace_package_path, filename) shutil.copy(apath, output) + elif 'lin' in filename: + continue else: output=os.path.join(self.__workspace_package_path, filename) shutil.copy(apath, output) diff --git a/Ortho/OrthoMain.spec b/Ortho/OrthoMain.spec index af31838c..2148d46a 100644 --- a/Ortho/OrthoMain.spec +++ b/Ortho/OrthoMain.spec @@ -1,6 +1,29 @@ # -*- mode: python ; coding: utf-8 -*- +import sys +from shutil import copy +import os +cwdpath = os.getcwd() +toolDir = os.path.join(cwdpath, 'tool') +if os.path.exists(toolDir): + os.remove(toolDir) +os.mkdir(toolDir) +source_folder = '../tool' + +def copy_file(path_read, path_write): + names = os.listdir(path_read) + for name in names: + path_read_new = os.path.join(path_read, name) + path_write_new = os.path.join(path_write, name) + if os.path.isdir(path_read_new): + if not os.path.exists(path_write_new): + os.mkdir(path_write_new) + copy_file(path_read_new, path_write_new) + else: + copy(path_read_new, path_write_new) + +copy_file(source_folder, toolDir) block_cipher = None diff --git a/atmosphericDelay-C-SAR/AtmosphericDelay.xml b/atmosphericDelay-C-SAR/AtmosphericDelay.xml index c67e3e34..5fb0ed9a 100644 --- a/atmosphericDelay-C-SAR/AtmosphericDelay.xml +++ b/atmosphericDelay-C-SAR/AtmosphericDelay.xml @@ -1,7 +1,7 @@ CSAR_202107275419_0001-0 - E:\Result_GF3\ + D:\micro\WorkSpace\ File ElementAlg @@ -9,20 +9,20 @@ AtmosphericDelay-C-SAR-V2.2.exe 大气延迟校正产品 微波卫星3-5级产品生产模型 - AtmosphericDelay-C-SAR-V2.2-1 + AtmosphericDelay-C-SAR-V2.2-1 2.2 辐射类产品_大气延迟校正 5 - AtmosphericDelay_中科卫星应用德清研究院_2.2 + AtmosphericDelay_中科卫星应用德清研究院_2.2 中科卫星应用德清研究院 景-算法 - + - + 1.8 python - + 0 0 Windows10 @@ -33,68 +33,71 @@ 无需求 无需求 - + - - MasterSarData - 主影像 - 经过几何校正和地形校正的SAR影像产品 - File - tar.gz - Man - E:\GF3Data\AtmophericDealy\GF3_SAY_FSI_001614_E113.2_N34.5_20161129_L1A_HHHV_L10002015686.tar.gz - True - False - File - Satellite - 1 - S1A - - AuxiliarySarData - 辅影像 - 经过几何校正和地形校正的SAR影像产品 + MainImg + 主影像时间 + 哨兵数据主影像的时间，来源于数据名称 + Value + string + Man + 20161129 + True + False + UploadInput + Aux + 0 + Aux + + + SARS + SAR影像文件夹路径 + 哨兵1号数据存放的文件夹 File tar.gz - Man - E:\GF3Data\AtmophericDealy\GF3_KAS_FSI_002034_E113.4_N34.7_20161228_L1A_HHHV_L10002077539.tar.gz - True - False - File + Man + + G:\辅助数据\GF3Data\AtmophericDealy\GF3_SAY_FSI_001614_E113.2_N34.5_20161129_L1A_HHHV_L10002015686.tar.gz; + G:\辅助数据\GF3Data\AtmophericDealy\GF3_KAS_FSI_002034_E113.4_N34.7_20161228_L1A_HHHV_L10002077539.tar.gz + + True + False + File Satellite - 1 + 0 S1A - - + + MasterNC 主影像气象数据 当DataType:nc时，ParaValue处填写下载的ERA文件的路径，且气象数据须包含变量：longitude、latitude、 - pressure_level、time、Geopotential、Relative humidity、Temperature；当DataType:file时，ParaValue处 - 填写文件夹路径，且文件夹中需包含三个tif格式的气象参数：相对湿度、温度和位势能 + pressure_level、time、Geopotential、Relative humidity、Temperature；当DataType:file时，ParaValue处 + 填写文件夹路径，且文件夹中需包含三个tif格式的气象参数：相对湿度、温度和位势能 File zip - Man - E:\GF3Data\AtmophericDealy\CASR_atmo_ERA5_N33_N36_E112_E115_20161228_22.zip - True - False - File + Man + G:\辅助数据\GF3Data\AtmophericDealy\CASR_atmo_ERA5_N33_N36_E112_E115_20161228_22.zip + True + False + File Aux 1 Aux - - + + AuxiliaryNC 辅影像气象数据 当DataType:nc时，ParaValue处填写下载的ERA文件的路径，且气象数据须包含变量：longitude、latitude、 - pressure_level、time、Geopotential、Relative humidity、Temperature；当DataType:file时，ParaValue处 - 填写文件夹路径，且文件夹中需包含三个tif格式的气象参数：相对湿度、温度和位势能 + pressure_level、time、Geopotential、Relative humidity、Temperature；当DataType:file时，ParaValue处 + 填写文件夹路径，且文件夹中需包含三个tif格式的气象参数：相对湿度、温度和位势能 File zip - Man - E:\GF3Data\AtmophericDealy\CASR_atmo_ERA5_N33_N36_E112_E115_20161129_22.zip - True - False - File + Man + G:\辅助数据\GF3Data\AtmophericDealy\CASR_atmo_ERA5_N33_N36_E112_E115_20161129_22.zip + True + False + File Aux 1 Aux @@ -105,30 +108,34 @@ 高程数据数据。数据来源:30米 ASTGTM2, 数据格式：tif。备注：数据的经纬度范围必须是整数 File zip - Man - E:\GF3Data\AtmophericDealy\CASR_atmo_ASTGTM2_N34E113_dem.zip;E:\GF3Data\AtmophericDealy\CASR_atmo_ASTGTM2_N34E114_dem.zip;E:\GF3Data\AtmophericDealy\CASR_atmo_ASTGTM2_N35E113_dem.zip;E:\GF3Data\AtmophericDealy\CASR_atmo_ASTGTM2_N35E114_dem.zip - True - False - File + Man + + G:\辅助数据\GF3Data\Deformation\CASR_df_ASTGTM2_N34E113_dem.zip; + G:\辅助数据\GF3Data\Deformation\CASR_df_ASTGTM2_N34E114_dem.zip; + G:\辅助数据\GF3Data\Deformation\CASR_df_ASTGTM2_N35E113_dem.zip; + G:\辅助数据\GF3Data\Deformation\CASR_df_ASTGTM2_N35E114_dem.zip + True + False + File DEM 0 DEM - box + box 经纬度包围盒 经纬度包围盒SNWE。例子：30.0;30.2;117.3;117.5 Value string - Man - 34.60;34.67;113.05;113.18 - True - True - UploadInput + Man + 34.64;34.67;113.15;113.18 + True + True + UploadInput Aux 0 Aux - + @@ -137,8 +144,8 @@ 大气延迟校正产品反演 File tar.gz - Man - E:\Result_GF3\AtmosphericDelay\Output\GF3_SAY_FSI_001614_E113.2_N34.5_20161129_L1A_HHHV_L10002015686-IADC.tar.gz + Man + D:\micro\WorkSpace\AtmosphericDelay\Output\GF3_SAY_FSI_001614_E113.2_N34.5_20161129_L1A_HHHV_L10002015686 diff --git a/atmosphericDelay-C-SAR/AtmosphericDelayMain.py b/atmosphericDelay-C-SAR/AtmosphericDelayMain.py index a7ef87cd..59262c88 100644 --- a/atmosphericDelay-C-SAR/AtmosphericDelayMain.py +++ b/atmosphericDelay-C-SAR/AtmosphericDelayMain.py @@ -106,9 +106,10 @@ class AtmosphericMain: self.__create_work_space() self.__input_paras = self.__alg_xml_handler.get_input_paras() # 获取输入文件夹中的数据名、类型、地址 self.__processing_paras = self.__init_processing_paras(self.__input_paras, self.__workspace_preprocessed_path) # 输出{文件名:地址} + SrcImagePath = self.__input_paras["SARS"]['ParaValue'] + paths = SrcImagePath.split(';') SrcImageName = os.path.split(self.input_paras["MasterSarData"])[1].split('.tar.gz')[0] - result_name = SrcImageName + tar + ".tar.gz" - self.__out_para = os.path.join(self.__workspace_path, EXE_NAME, 'Output', result_name) + self.__out_para = os.path.join(self.__workspace_path, EXE_NAME, 'Output', SrcImageName) self.__alg_xml_handler.write_out_para("AtmosphericDelayProduct", self.__out_para) # 写入输出参数 # 判断气象数据是tif格式还是file格式 @@ -162,7 +163,7 @@ class AtmosphericMain: a_nc = 1 processing_paras.update({name: file_path}) else: - para_value_list = out_path.split(";") + para_value_list = para['ParaValue'].split(";") if len(para_value_list) == 1: para_path = para['ParaValue'] if para_path != 'empty' and para_path != '': @@ -171,7 +172,7 @@ class AtmosphericMain: else: for n, para_value_zip in zip(range(len(para_value_list)), para_value_list): file_path = BlockProcess.unzip_file(para_value_zip, out_path) - processing_paras.update({name+str(n): file_path}) + processing_paras.update({name + str(n): file_path}) elif para['DataType'] == 'file': if name in ["MasterNC", "AuxiliaryNC"]: processing_paras.update({name: para_path}) @@ -224,19 +225,6 @@ class AtmosphericMain: shutil.copy(file_path, os.path.join(dem_path, tif_name)) para_path = os.path.join(self.__workspace_origin_path, para['ParaName']) processing_paras.update({'dem': para_path}) - # # 解压DEM到指定文件夹 - # path = para['ParaValue'] - # import zipfile - # zip_file = zipfile.ZipFile(path) - # zip_list = zip_file.namelist() # 得到压缩包里所有文件 - # for f in zip_list: - # zip_file.extract(f, self.__workspace_dem_path) # 循环解压文件到指定目录 - # if os.path.splitext(f)[1] == '.wgs84': - # dem_name = f - # processing_paras.update({'dem': os.path.join(self.__workspace_dem_path, f)}) - # zip_file.close() - # self.verifyAndModifyWgsXml(self.__workspace_dem_path + '\\' + dem_name + '.xml', - # self.__workspace_dem_path + '\\' + dem_name) if name == 'Orbits': if para['DataType'] == 'File': processing_paras.update({'orbits': para['ParaValue']}) @@ -267,7 +255,7 @@ class AtmosphericMain: para_path = os.path.join(self.__workspace_origin_path, para['ParaName']) processing_paras.update({'slc': para_path}) for pa in para_path_list: - key_word = os.path.basename(pa).split('_')[7] + key_word = os.path.basename(pa).split('_')[6] if key_word == self.mas_key_word: self.input_paras.update({"MasterSarData": pa}) else: diff --git a/backScattering/BackScatteringMain.py b/backScattering/BackScatteringMain.py index d3c187f2..95e3455e 100644 --- a/backScattering/BackScatteringMain.py +++ b/backScattering/BackScatteringMain.py @@ -333,7 +333,7 @@ class ScatteringMain: dem_merged_path = DEMProcess.dem_merged(in_dem_path, meta_file_path, out_dem_path) # 生成TestDEM\mergedDEM_VRT.tif - dem_path = self.cut_dem(dem_merged_path, meta_file_path) + # dem_path = self.cut_dem(dem_merged_path, meta_file_path) in_slc_path = None for slc_path in in_tif_paths: @@ -343,7 +343,7 @@ class ScatteringMain: break # 获取校正模型后 - Orthorectification.preCaldem_sar_rc(dem_path, in_slc_path, self.__workspace_preprocessing_path, + Orthorectification.preCaldem_sar_rc(dem_merged_path, in_slc_path, self.__workspace_preprocessing_path, self.__workspace_processing_path.replace("\\", "\\\\")) # 初步筛选坐标范围 logger.info('progress bar: 40%') # clip_dem_reample_path=os.path.join(self.__workspace_preprocessing_path, "SAR_dem.tiff") diff --git a/deformation-C-SAR/DeformationImageHandle.py b/deformation-C-SAR/DeformationImageHandle.py index 900f31ac..60cbf8d0 100644 --- a/deformation-C-SAR/DeformationImageHandle.py +++ b/deformation-C-SAR/DeformationImageHandle.py @@ -392,8 +392,8 @@ class DemImageHandler: min = np.nanmin(t_data) max = np.nanmax(t_data) t_data[np.isnan(t_data)] = max - if (max - min) < 256: - t_data = (t_data - min) / (max - min) * 255 + # if (max - min) < 256: + t_data = (t_data - min) / (max - min) * 255 out_img = Image.fromarray(t_data) out_img = out_img.resize((q_c, q_r)) # 重采样 out_img = out_img.convert("L") # 转换成灰度图 diff --git a/dem-C-SAR/DemImageHandle.py b/dem-C-SAR/DemImageHandle.py index 900f31ac..60cbf8d0 100644 --- a/dem-C-SAR/DemImageHandle.py +++ b/dem-C-SAR/DemImageHandle.py @@ -392,8 +392,8 @@ class DemImageHandler: min = np.nanmin(t_data) max = np.nanmax(t_data) t_data[np.isnan(t_data)] = max - if (max - min) < 256: - t_data = (t_data - min) / (max - min) * 255 + # if (max - min) < 256: + t_data = (t_data - min) / (max - min) * 255 out_img = Image.fromarray(t_data) out_img = out_img.resize((q_c, q_r)) # 重采样 out_img = out_img.convert("L") # 转换成灰度图 diff --git a/dem-C-SAR/DemMain.py b/dem-C-SAR/DemMain.py index cea44ff9..4dcf1319 100644 --- a/dem-C-SAR/DemMain.py +++ b/dem-C-SAR/DemMain.py @@ -40,6 +40,8 @@ else: DEBUG = False file = fileHandle(DEBUG) tar = r'-' + cf.get('tar') +alks = cf.get('alks') +rlks = cf.get('rlks') productLevel = cf.get('productLevel') LogHandler.init_log_handler('run_log\\' + EXE_NAME) logger = logging.getLogger("mylog") @@ -184,12 +186,15 @@ class DemMain: if name == 'MainImg': processing_paras.update({'mainimg': para['ParaValue']}) if name == 'box': - datas = para['ParaValue'].split(';') - if len(datas) != 4: - msg = 'para: box is error!box:' + para['ParaValue'] - raise Exception(msg) - box = datas[0] + ' ' + datas[1] + ' ' + datas[2] + ' ' + datas[3] - processing_paras.update({'box': box}) + if para['ParaValue'] == 'empty': + processing_paras.update({'box': 'empty'}) + else: + datas = para['ParaValue'].split(';') + if len(datas) != 4: + msg = 'para: box is error!box:' + para['ParaValue'] + raise Exception(msg) + box = datas[0] + ' ' + datas[1] + ' ' + datas[2] + ' ' + datas[3] + processing_paras.update({'box': box}) if name == 'AuxDir': if para['DataType'] == 'File': processing_paras.update({'AuxDir': para['ParaValue']}) @@ -406,6 +411,10 @@ class DemMain: CreateProductXml(para_dict, model_path, meta_xml_path).create_standard_xml() return meta_xml_path + def isce_run_steps(self, run_steps, target): + for i in range(0, len(run_steps)): + uwm_file = os.path.join(self.__workspace_isce_path, "run_files", run_steps[i]) + shutil.move(uwm_file, target) def process_handle(self,start): # 执行isce2.5生成干涉图 @@ -467,17 +476,36 @@ class DemMain: logger.info('slc to isce_data finish!') logger.info('progress bar: 10%') - # os.chdir(isce_exe_dir) - cmd = "stackStripMap.exe -s {} -w {} -d {} -m {} -a {} -r {} -x {} -u 'snaphu' --nofocus".format(out_slc_dir, isce_work_space, dem_path, main_img, 3, 3, box) - # cmd = "stackStripMap.exe -s {} -w {} -d {} -m {} -a {} -r {} -u 'snaphu' --nofocus".format(out_slc_dir, isce_work_space, dem_path, main_img, 3, 3) - logger.info('stackStripMap_cmd:{}'.format(cmd)) - result = os.system(cmd) - logger.info('cmd_result:{}'.format(result)) - logger.info('stackStripMap finish!') + if self.__in_processing_paras['box'] == 'empty': + box = '' + cmd = "stackStripMap.exe -s {} -w {} -d {} -m {} -a {} -r {} -u 'snaphu' --nofocus".format(out_slc_dir, + isce_work_space, + dem_path, + main_img, alks, + rlks) + logger.info('stackStripMap_cmd:{}'.format(cmd)) + result = os.system(cmd) + logger.info('cmd_result:{}'.format(result)) + logger.info('stackStripMap finish!') + run_files = os.path.join(self.__workspace_isce_path, 'run_files') + for file in list(glob.glob(os.path.join(run_files, '*.job'))): + os.remove(file) + run_steps = ["run_07_grid_baseline"] + self.isce_run_steps(run_steps, self.__workspace_isce_path) + else: + box = "'" + self.__in_processing_paras['box'] + "'" + cmd = "stackStripMap.exe -s {} -w {} -d {} -m {} -a {} -r {} -x {} -u 'snaphu' --nofocus".format( + out_slc_dir, isce_work_space, dem_path, main_img, alks, rlks, box) + logger.info('stackStripMap_cmd:{}'.format(cmd)) + result = os.system(cmd) + logger.info('cmd_result:{}'.format(result)) + logger.info('stackStripMap finish!') - run_files = os.path.join(self.__workspace_isce_path, 'run_files') - for file in list(glob.glob(os.path.join(run_files, '*.job'))): - os.remove(file) + run_files = os.path.join(self.__workspace_isce_path, 'run_files') + for file in list(glob.glob(os.path.join(run_files, '*.job'))): + os.remove(file) + run_steps = ["run_08_grid_baseline"] + self.isce_run_steps(run_steps, self.__workspace_isce_path) cmd = ['-e', isce_exe_dir, '-o', self.__workspace_isce_path] logger.info('autorun_cmd:{}'.format(cmd)) @@ -534,7 +562,7 @@ if __name__ == '__main__': start = datetime.datetime.now() try: if len(sys.argv) < 2: - xml_path = r'Dem.xml' + xml_path = r'Dem_C_SAR_V3.xml' else: xml_path = sys.argv[1] Main = DemMain(xml_path) diff --git a/dem-C-SAR/Dem_C_SAR_V3.xml b/dem-C-SAR/Dem_C_SAR_V3.xml index d6acf1a5..f9c7c057 100644 --- a/dem-C-SAR/Dem_C_SAR_V3.xml +++ b/dem-C-SAR/Dem_C_SAR_V3.xml @@ -41,7 +41,7 @@ DEFAULT DEFAULT Man - 20161129 + 20230615 True False UploadInput @@ -60,8 +60,8 @@ DEFAULT Cal - D:\micro\microproduct_depdence\GF3-Deformation\download\cls\GF3_SAY_FSI_001614_E113.2_N34.5_20161129_L1A_HHHV_L10002015686.tar.gz; - D:\micro\microproduct_depdence\GF3-Deformation\download\cls\GF3_KAS_FSI_002034_E113.4_N34.7_20161228_L1A_HHHV_L10002077539.tar.gz + F:\MicroWorkspace\yuan-GF3-INSAR\GF3B_MYC_UFS_008208_E116.5_N44.2_20230615_L1A_DH_L10000199472.tar.gz; + F:\MicroWorkspace\yuan-GF3-INSAR\GF3B_MYC_UFS_009462_E116.3_N44.3_20230910_L1A_DH_L10000237326.tar.gz True False File @@ -72,14 +72,14 @@ box 经纬度包围盒 - 经纬度包围盒SNWE。例子：30.0;30.2;117.3;117.5 37;38.2;108.87;109.1 + 经纬度包围盒SNWE。例子：37;38.2;108.87;109.1 value string DEFAULT DEFAULT DEFAULT Man - 34.60;34.67;113.05;113.18 + 44.14;44.3;116.351;116.437 True True UploadInput @@ -92,12 +92,12 @@ DEM高程数据路径 DEM高程数据数据。数据来源:30米 ASTGTM2, 数据格式：tif。备注：数据的经纬度范围必须是整数 File - File + tif DEFAULT DEFAULT DEFAULT Cal - D:\micro\microproduct_depdence\GF3-Deformation\dem + F:\MicroWorkspace\COPDEM\COPDEM_Int16\115E39N_COP30.tif True False File @@ -137,8 +137,7 @@ DEFAULT DEFAULT -9999 - - D:\micro\WorkSpace\Dem\Output\GF3_SAY_FSI_001614_E113.2_N34.5_20161129_L1A_HHHV_L10002015686-DEM.tar.gz + D:\micro\WorkSpace\Dem\Output\GF3B_MYC_UFS_008208_E116.5_N44.2_20230615_L1A_DH_L10000199472-DEM.tar.gz diff --git a/dem-C-SAR/ISCEApp/_internal/isce/components/isceobj/Sensor/GF3_SLC.py b/dem-C-SAR/ISCEApp/_internal/isce/components/isceobj/Sensor/GF3_SLC.py index f36dd753..496c4bf8 100644 --- a/dem-C-SAR/ISCEApp/_internal/isce/components/isceobj/Sensor/GF3_SLC.py +++ b/dem-C-SAR/ISCEApp/_internal/isce/components/isceobj/Sensor/GF3_SLC.py @@ -1253,7 +1253,7 @@ class _prodInfo(GF3_SLCNamespace): elif z.tag == 'WidthInMeters': self.WidthInMeters = float(z.text) if z.tag == 'productLevel': - self.productLevel = int(z.text) + self.productLevel = str(z.text) elif z.tag == 'productType': self.productType = z.text elif z.tag == 'productFormat': @@ -1421,14 +1421,17 @@ class _imageInfo(GF3_SLCNamespace): elif z.tag == 'QualifyValue': QualifyValue = z for value in QualifyValue: - if value.tag == 'HH': - self.QualifyValue[0] = float(value.text) - elif value.tag == 'HV': - self.QualifyValue[1] = float(value.text) - elif value.tag == 'VH': - self.QualifyValue[2] = float(value.text) - elif value.tag == 'VV': - self.QualifyValue[3] = float(value.text) + try: + if value.tag == 'HH': + self.QualifyValue[0] = float(value.text) + elif value.tag == 'HV': + self.QualifyValue[1] = float(value.text) + elif value.tag == 'VH': + self.QualifyValue[2] = float(value.text) + elif value.tag == 'VV': + self.QualifyValue[3] = float(value.text) + except Exception as e: + print(e) def __str__(self): retstr = "_ImageInfo:"+sep+tab diff --git a/dem-C-SAR/config.ini b/dem-C-SAR/config.ini index a2f7bc2f..50aa9cee 100644 --- a/dem-C-SAR/config.ini +++ b/dem-C-SAR/config.ini @@ -5,7 +5,8 @@ exe_name = Dem # 开启调试模式则不删除临时工作区，True:开启调试，False:不开启调试 debug = True - +alks = 10 +rlks = 10 # 算法信息 tar = DEM productLevel = 5 diff --git a/landcover_c_sar/LandCoverMain.py b/landcover_c_sar/LandCoverMain.py index edcb37d3..dad9311f 100644 --- a/landcover_c_sar/LandCoverMain.py +++ b/landcover_c_sar/LandCoverMain.py @@ -587,7 +587,7 @@ class LandCoverMain: logging.info("feature_tif_paths:%s",feature_tif_paths) # 对所有特征进行地理编码 - feature_geo = self.features_geo(feature_tif_paths) + feature_geo = self.features_geo(self.__feature_tif_dir) # 新添加的特征做归一化 # for name in self.__feature_name_list: # proj, geo, arr = self.imageHandler.read_img(self.__preprocessed_paras[name]) @@ -709,7 +709,7 @@ if __name__ == '__main__': start = datetime.datetime.now() try: if len(sys.argv) < 2: - xml_path = 'LandCover.xml' + xml_path = 'LandCover_C_SAR_V3.xml' else: xml_path = sys.argv[1] main_handler = LandCoverMain(xml_path) diff --git a/landcover_c_sar/LandCover_C_SAR_V3.xml b/landcover_c_sar/LandCover_C_SAR_V3.xml index 691118d5..0a9bf5bd 100644 --- a/landcover_c_sar/LandCover_C_SAR_V3.xml +++ b/landcover_c_sar/LandCover_C_SAR_V3.xml @@ -42,7 +42,7 @@ DEFAULT Cal - E:\MicroWorkspace\GF3A_nanjing\input-ortho\GF3_SAY_QPSI_011444_E118.9_N31.4_20181012_L1A_AHV_L10003515422-ortho.tar.gz + F:\MicroWorkspace\GF3A_nanjing\input-ortho\GF3_SAY_QPSI_011444_E118.9_N31.4_20181012_L1A_AHV_L10003515422-ortho.tar.gz True False File @@ -55,12 +55,12 @@ 标记数据 标记的样本数据 File - csv + zip DEFAULT DEFAULT DEFAULT Cal - E:\MicroWorkspace\GF3A_nanjing\input-ortho\LandCoverLable_geo.csv + F:\al_zhongji\C-SAR-data\landcover\CSAR_land_LandCoverLable.zip True True UploadTable @@ -90,17 +90,16 @@ FeatureCombination 极化特征组合 可选极化特征组合一、共14种特征（编号依次为0-13） - Freeman：表面散射p_s(0)、偶次散射p_d(1)、体散射p_v(2); - Touzi：散射角α_s(3)、散射相位ϕ_α(4)、目标散射对称度τ(5)、相对能量λ_i(6); - Yamaguchi：表面散射f_s(7)、二次散射f_d(8)、体散射f_v(9)、螺旋体散射f_h(10); - Cloude-Pottier：分解散射熵H(11)、反熵A(12)、平均散射角α(13) + Freeman：表面散射p_s(0)、偶次散射p_d(1)、体散射p_v(2); + Yamaguchi：表面散射f_s(3)、二次散射f_d(4)、体散射f_v(5)、螺旋体散射f_h(6); + Cloude-Pottier：分解散射熵H(7)、反熵A(8)、平均散射角α(9) Value string DEFAULT DEFAULT DEFAULT Man - 0,1,2,7,8,9,10 + 0,1,2 True True UploadInput @@ -121,8 +120,7 @@ DEFAULT DEFAULT Man - - D:\micro\WorkSpace\LandCover\Output\GF3_SAY_QPSI_011444_E118.9_N31.4_20181012_L1A_AHV_L10003515422-ortho-LANDClASS.tar.gz + D:\micro\WorkSpace\LandCover\Output\GF3_SAY_QPSI_011444_E118.9_N31.4_20181012_L1A_AHV_L10003515422-ortho-LANDCLASS.tar.gz diff --git a/soilMoistureTop/SoilMoisture.xml b/soilMoistureTop/SoilMoisture.xml index 71a16f6f..f5a04c92 100644 --- a/soilMoistureTop/SoilMoisture.xml +++ b/soilMoistureTop/SoilMoisture.xml @@ -36,16 +36,16 @@ File tar.gz Man - F:\202306hb\sar_img\GF3B_SYC_QPSI_008316_E116.1_N43.3_20230622_L1A_AHV_L10000202892-cal.tar.gz + F:\Tian-GF3-Wenchang\GF3_SYC_QPSI_040488_E110.7_N19.9_20240418_L1A_AHV_L10006923783-cal.tar.gz Covering 地表覆盖类型数据 经过地理定标（WGS84）的地表覆盖类型数据 File - zip + tif Man - E:\辅助数据\GF3Data\soilMoisture\CSAR_solim_50T_20220101-20230101.zip + F:\Tian-GF3-Wenchang\landCover.tif CoveringIDs @@ -64,9 +64,9 @@ NDVI数据 经过地理定标（WGS84）的NDVI数据 File - zip + tif Man - E:\辅助数据\GF3Data\soilMoisture\CSAR_solim_S2_202306_NDVI.zip + F:\Tian-GF3-Wenchang\NDVI\NDVI_20240417_WGS841.tif NDVIScope @@ -98,9 +98,9 @@ NDWI数据 经过地理定标（WGS84）的NDWI数据 File - zip + tif Man - E:\辅助数据\GF3Data\soilMoisture\CSAR_solim_S2_202306_NDWI.zip + F:\Tian-GF3-Wenchang\NDWI\NDWI_20240417_WGS841.tif e1 @@ -109,7 +109,7 @@ Value float Man - -22.482554048434324 + 5.308639240349595 100 -100 DEFAULT @@ -121,7 +121,7 @@ Value float Man - -10.72946251632336 + -3.546779815649669 100 -100 DEFAULT @@ -133,7 +133,7 @@ Value float Man - -0.08238130673792357 + 92.54550090363222 9999 -9999 DEFAULT @@ -145,7 +145,7 @@ Value float Man - 1.0194495140476119 + -0.016379035637768415 9999 -9999 DEFAULT @@ -157,7 +157,7 @@ Value float Man - 6.107713980885245 + -67.4408236678189 9999 -9999 DEFAULT @@ -169,7 +169,7 @@ Value float Man - -4.496951628949385 + 0.054641574960551206 9999 -9999 DEFAULT @@ -183,7 +183,7 @@ File tar.gz Man - D:\micro\WorkSpace\SoilMoisture\Output\GF3B_SYC_QPSI_008316_E116.1_N43.3_20230622_L1A_AHV_L10000202892-cal-SMC.tar.gz + D:\micro\WorkSpace\SoilMoisture\Output\GF3_SYC_QPSI_040488_E110.7_N19.9_20240418_L1A_AHV_L10006923783-cal-SMC.tar.gz DEFAULT DEFAULT DEFAULT diff --git a/tool/algorithm/image/ImageHandle.py b/tool/algorithm/image/ImageHandle.py index 58ebac57..afcef790 100644 --- a/tool/algorithm/image/ImageHandle.py +++ b/tool/algorithm/image/ImageHandle.py @@ -645,9 +645,8 @@ class ImageHandler: # 灰度图 min = np.percentile(t_data, 2) # np.nanmin(t_data) max = np.percentile(t_data, 98) # np.nanmax(t_data) - t_data[np.isnan(t_data)] = max - if (max - min) < 256: - t_data = (t_data - min) / (max - min) * 255 + # if (max - min) < 256: + t_data = (t_data - min) / (max - min) * 255 out_img = Image.fromarray(t_data) out_img = out_img.resize((q_c, q_r)) # 重采样 out_img = out_img.convert("L") # 转换成灰度图 @@ -763,8 +762,8 @@ class ImageHandler: if __name__ == '__main__': cols = 7086 rows = 8064 - inc_xml = r'D:\micro\WorkSpace\SurfaceRoughness\Temporary\preprocessing\GF3C_KSC_QPSI_008440_E86.0_N44.7_20231113_L1A_AHV_L10000215825-ortho\GF3C_KSC_QPSI_008440_E86.0_N44.7_20231113_L1A_AHV_L10000215825.incidence.xml' - ImageHandler.get_inc_angle(inc_xml, rows, cols) + inc_xml = r"D:\micro\WorkSpace\Dem\Temporary\processing\product\GF3_SAY_FSI_001614_E113.2_N34.5_20161129_L1A_HHHV_L10002015686-DEM.tiff" + # ImageHandler().write_quick_view(inc_xml) # fn = r'E:\202306hb\result\GF3B_SYC_QPSI_008316_E116.1_N43.3_20230622_L1A_AHV_L10000202892-cal-SMC.tif' # out = r'E:\202306hb\result\soil.tif' # # @@ -780,3 +779,7 @@ if __name__ == '__main__': # s = ImageHandler().band_merge(path, path2, path3) # print(s) # pass + fn = r"D:\BaiduNetdiskDownload\植被物候\chen_features_warp.tif" + outP = r'D:\BaiduNetdiskDownload\植被物候\chen_features_warp_LWZ.tif' + im_proj, im_geotrans, im_arr = ImageHandler.read_img(fn) + ImageHandler.write_img(outP, im_proj, im_geotrans, im_arr) diff --git a/tool/algorithm/ml/machineLearning.py b/tool/algorithm/ml/machineLearning.py index 9ff25882..d9d04719 100644 --- a/tool/algorithm/ml/machineLearning.py +++ b/tool/algorithm/ml/machineLearning.py @@ -218,9 +218,10 @@ class MachineLeaning: # 开启多进程处理 bp = BlockProcess() block_size = bp.get_block_size(rows, cols) + name_d = out_tif_name.split('_')[6] + '_VTH' block_features_dir = X_test_list - bp_cover_dir = os.path.join(workspace_processing_path, out_tif_name, + bp_cover_dir = os.path.join(workspace_processing_path, name_d, 'pre_result\\') # workspace_processing_path + out_tif_name + '\\' file.creat_dirs([bp_cover_dir]) @@ -242,7 +243,7 @@ class MachineLeaning: suffix = '_' + name.split('_')[-4] + "_" + name.split('_')[-3] + "_" + name.split('_')[-2] + "_" + \ name.split('_')[-1] - img_path = os.path.join(bp_cover_dir, out_tif_name + suffix) # bp_cover_dir + out_tif_name + suffix + img_path = os.path.join(bp_cover_dir, name_d + suffix) # bp_cover_dir + out_tif_name + suffix row_begin = int(name.split('_')[-4]) col_begin = int(name.split('_')[-2]) pool.apply_async(ml.predict_blok, (clf, X_test, block_size, block_size, img_path, row_begin, col_begin, len(block_features_dir), n)) @@ -259,7 +260,7 @@ class MachineLeaning: # 添加地理信息 cover_path = os.path.join(workspace_processing_path, - out_tif_name + ".tif") # workspace_processing_path + out_tif_name + ".tif" + name_d + ".tif") # workspace_processing_path + out_tif_name + ".tif" # bp.assign_spatial_reference_byfile(self.__ref_img_path, cover_path) return cover_path @@ -311,6 +312,46 @@ class MachineLeaning: logger.info("gene_train_set success!") return X_train, Y_train + @staticmethod + def gene_train_set_deLandcover(train_data_dic, feature_tif_dir, land_cover_tif, coverId): + """ + 生成训练集 + :param train_data_dic : 从csv读取的训练数据 + :param feature_tif_dir : 特征影像路径路径 + :return X_train, Y_train : 训练数据 + """ + in_tif_paths = list(glob.glob(os.path.join(feature_tif_dir, '*.tif'))) + land_arr = ImageHandler.get_band_array(land_cover_tif, 1) + dim = len(in_tif_paths) + X_train = np.empty(shape=(0, dim)) + Y_train = np.empty(shape=(0, 1)) + + ids = train_data_dic['ids'] + positions = train_data_dic['positions'] + for id, points in zip(ids, positions): + # for data in train_data_list: + if points == []: + raise Exception('data is empty!') + row, col = zip(*points) + l = len(points) + X = np.empty(shape=(l, dim)) + + for n, tif_path in zip(range(dim), in_tif_paths): + feature_array = ImageHandler.get_data(tif_path) + feature_array[np.isnan(feature_array)] = 0 # 异常值填充为0 + for id in coverId: + feature_array[np.where(land_arr == id)] = 0 + x = feature_array[row, col].T + X[:, n] = x + + Y = np.full((l, 1), id) + X_train = np.vstack((X_train, X)) + Y_train = np.vstack((Y_train, Y)) + Y_train = Y_train.T[0, :] + + logger.info("gene_train_set success!") + return X_train, Y_train + @staticmethod def standardization(data, num=1): # 矩阵标准化到[0,1] diff --git a/tool/algorithm/polsarpro/createfeature.py b/tool/algorithm/polsarpro/createfeature.py index b252a083..4aaaf104 100644 --- a/tool/algorithm/polsarpro/createfeature.py +++ b/tool/algorithm/polsarpro/createfeature.py @@ -29,18 +29,18 @@ class CreateFeature: atp = AHVToPolsarpro() atp = AHVToPolsarpro(hh_hv_vh_vv_list) - lee_filter_path = os.path.join(workspace_processing_path, name, 'lee_filter\\') # workspace_processing_path + name + '\\lee_filter\\' + lee_filter_path = os.path.join(workspace_processing_path, name.split('_')[6], 'lee_filter\\') # workspace_processing_path + name + '\\lee_filter\\' if self._debug == False: - t3_path = os.path.join(workspace_processing_path, name, 'psp_t3\\') # workspace_processing_path + name + '\\psp_t3\\' + t3_path = os.path.join(workspace_processing_path, name.split('_')[6], 'psp_t3\\') # workspace_processing_path + name + '\\psp_t3\\' # atp.ahv_to_polsarpro_t3(t3_path, tif_path) polarization = ['HH', 'HV', 'VH', 'VV'] - if os.path.exists(workspace_preprocessing_path + name + '\\'): - meta_xml_paths = list(glob.glob(os.path.join(workspace_preprocessing_path + name, '*.meta.xml'))) + if os.path.exists(workspace_preprocessing_path + name.split('_')[6] + '\\'): + meta_xml_paths = list(glob.glob(os.path.join(workspace_preprocessing_path + name.split('_')[6], '*.meta.xml'))) meta_dic = InitPara.get_meta_dic_new(meta_xml_paths, name) calibration = Calibration.get_Calibration_coefficient(meta_dic['Origin_META'], polarization) - tif_path = atp.calibration(calibration, workspace_preprocessing_path, name) + tif_path = atp.calibration(calibration, workspace_preprocessing_path) atp.ahv_to_polsarpro_t3_veg(t3_path, tif_path) # Lee滤波 @@ -64,7 +64,7 @@ class CreateFeature: freemanOutDir = os.path.join(workspace_processing_path, name + '\\freeman\\') if self._debug == False: freemDecom = PspFreemanDecomposition(exeDir, t3_path, freemanOutDir) - flag = freemDecom.api_freeman_decomposition_T3(0, 0, rows, cols) + flag = freemDecom.api_freeman_decomposition_T3(0, 0, rows, cols, 7) if not flag: logger.error('FreemanDecomposition err') return False, None @@ -88,7 +88,7 @@ class CreateFeature: yamaguchiOutDir = os.path.join(workspace_processing_path, name + '\\yamaguchi\\') if self._debug == False: yamaguchiDecom = PspYamaguchiDecomposition(exeDir, t3_path, yamaguchiOutDir) - flag = yamaguchiDecom.api_yamaguchi_4components_decomposition_T3(0, 0, rows, cols) + flag = yamaguchiDecom.api_yamaguchi_4components_decomposition_T3(0, 0, rows, cols, 7) if not flag: logger.error('CloudePottierDecomposition err') return False, None @@ -102,7 +102,7 @@ class CreateFeature: cloudeDecom = PspCloudePottierDecomposition( exeDir, t3_path, cloudeOutDir) flag = cloudeDecom.api_h_a_alpha_decomposition_T3( - 0, 0, rows, cols) + 0, 0, rows, cols, 7) if not flag: logger.error('CloudePottierDecomposition err') return False, None @@ -152,14 +152,14 @@ class CreateFeature: hh_hv_vh_vv_dic.update({'VH': hh_hv_vh_vv_list[2]}) hh_hv_vh_vv_dic.update({'VV': hh_hv_vh_vv_list[3]}) t3_path = os.path.join(workspace_processing_path, name, "lee_filter") # workspace_processing_path + name + "\\lee_filter" - feature_tif_dir = os.path.join(workspace_processing_path, name, 'features') # workspace_processing_path + name + "\\features" + feature_tif_dir = os.path.join(workspace_processing_path, name.split('_')[6], 'features') # workspace_processing_path + name + "\\features" cfeature = CreateFeature(debug, exe_dir) # cfeature.creat_h_a_alpha_features(t3_path, feature_tif_dir) t3_path = cfeature.ahv_to_t3(workspace_processing_path, workspace_preprocessing_path, hh_hv_vh_vv_list, name, FILTER_SIZE) - flag, outFolderDic = cfeature.decompose(workspace_processing_path, name, t3_path, rows, cols, hh_hv_vh_vv_dic, FeatureInput) # , 'Touzi' + flag, outFolderDic = cfeature.decompose(workspace_processing_path, name.split('_')[6], t3_path, rows, cols, hh_hv_vh_vv_dic, FeatureInput) # , 'Touzi' cfeature.cereat_features_dic(outFolderDic, feature_tif_dir) return feature_tif_dir diff --git a/tool/algorithm/xml/AlgXmlHandle.py b/tool/algorithm/xml/AlgXmlHandle.py index 936d2e3b..b752cfe9 100644 --- a/tool/algorithm/xml/AlgXmlHandle.py +++ b/tool/algorithm/xml/AlgXmlHandle.py @@ -713,14 +713,15 @@ class InitPara: def get_mult_tar_gz_inf(self,tar_gz_path, workspace_preprocessing_path): para_dic = {} name = os.path.split(tar_gz_path)[1].rstrip('.tar.gz') + name_d = name.split('_')[6] para_dic.update({'name': name}) - file_dir = os.path.join(workspace_preprocessing_path, name + '\\') + file_dir = os.path.join(workspace_preprocessing_path, name_d + '\\') fileHandle().de_targz(tar_gz_path, file_dir) # 元文件字典 - para_dic.update(InitPara.get_meta_dic_VP(InitPara.get_meta_paths(file_dir, name), name)) + para_dic.update(InitPara.get_meta_dic_VP(InitPara.get_meta_paths(file_dir, name_d), name)) # tif路径字典 - pol_dic = InitPara.get_polarization_mode(InitPara.get_tif_paths(file_dir, name)) + pol_dic = InitPara.get_polarization_mode(InitPara.get_tif_paths(file_dir, name_d)) parameter_path = os.path.join(file_dir, "orth_para.txt") para_dic.update({name + "paraMeter": parameter_path}) for key, in_tif_path in pol_dic.items(): diff --git a/vegetationPhenology/VegetationPhenology.xml b/vegetationPhenology/VegetationPhenology.xml index 4560c84e..de03e454 100644 --- a/vegetationPhenology/VegetationPhenology.xml +++ b/vegetationPhenology/VegetationPhenology.xml @@ -107,14 +107,14 @@ FeatureCombination 极化特征组合 - 可选极化特征组合一、共14种特征（编号依次为0-13） + 可选极化特征组合一、共10种特征（编号依次为0-9） Freeman：表面散射p_s(0)、偶次散射p_d(1)、体散射p_v(2); - Yamaguchi：表面散射f_s(7)、二次散射f_d(8)、体散射f_v(9)、螺旋体散射f_h(10); - Cloude-Pottier：分解散射熵H(11)、反熵A(12)、平均散射角α(13) + Yamaguchi：表面散射f_s(3)、二次散射f_d(4)、体散射f_v(5)、螺旋体散射f_h(6); + Cloude-Pottier：分解散射熵H(7)、反熵A(8)、平均散射角α(9) Value string Man - 0,1,2,7,8,9,10 + 0,1,2,3,4,5,6,7,8,9 True True UploadInput diff --git a/vegetationPhenology/VegetationPhenologyAuxData.py b/vegetationPhenology/VegetationPhenologyAuxData.py index 832d2a37..f381b46a 100644 --- a/vegetationPhenology/VegetationPhenologyAuxData.py +++ b/vegetationPhenology/VegetationPhenologyAuxData.py @@ -318,22 +318,23 @@ class PhenoloyMeasCsv_geo: if train_data[1] == type_id: train_data[3] = train_data[3] + self.__render(poly) if train_data[3] == [] : - raise Exception('there are empty data!', train_data) - - if len(train_data_list) <= 1: - raise Exception('there is only one label type!', train_data_list) - - num_list = [] - for train_data in train_data_list: - if not len(train_data[3]) == 0: - num_list.append(len(train_data[3])) - max_num = np.min(num_list) - for train_data in train_data_list: - logger.info(str(train_data[0]) + "," + str(train_data[2]) +"," + "num:" + str(len(train_data[3]))) - # max_num = self.__max_tran__num_per_class - logger.info("max number =" + str(max_num) +", random select"+str(max_num)+" point as train data!") - if(len(train_data[3]) > max_num): - train_data[3] = random.sample(train_data[3], max_num) + pass + # raise Exception('there are empty data!', train_data) + # + # if len(train_data_list) <= 1: + # raise Exception('there is only one label type!', train_data_list) + # + # num_list = [] + # for train_data in train_data_list: + # if not len(train_data[3]) == 0: + # num_list.append(len(train_data[3])) + # max_num = np.min(num_list) + # for train_data in train_data_list: + # logger.info(str(train_data[0]) + "," + str(train_data[2]) +"," + "num:" + str(len(train_data[3]))) + # # max_num = self.__max_tran__num_per_class + # logger.info("max number =" + str(max_num) +", random select"+str(max_num)+" point as train data!") + # if(len(train_data[3]) > max_num): + # train_data[3] = random.sample(train_data[3], max_num) return train_data_list diff --git a/vegetationPhenology/VegetationPhenologyMain.py b/vegetationPhenology/VegetationPhenologyMain.py index cc971394..348919b3 100644 --- a/vegetationPhenology/VegetationPhenologyMain.py +++ b/vegetationPhenology/VegetationPhenologyMain.py @@ -101,8 +101,8 @@ class PhenologyMain: self.__processing_paras.update(InitPara(DEBUG).get_mult_tar_gz_infs(self.__processing_paras, self.__workspace_preprocessing_path)) SrcImagePath = self.__input_paras["AHVS"]['ParaValue'] paths = SrcImagePath.split(';') - SrcImageName = os.path.split(paths[0])[1].split('.tar.gz')[0] - result_name = SrcImageName + tar + ".tar.gz" + self.SrcImageName = os.path.split(paths[0])[1].split('.tar.gz')[0] + result_name = self.SrcImageName + tar + ".tar.gz" self.__out_para = os.path.join(self.__workspace_path, EXE_NAME, 'Output', result_name) self.__alg_xml_handler.write_out_para("VegetationPhenologyProduct", self.__out_para) #写入输出参数 logger.info('check_source success!') @@ -147,7 +147,7 @@ class PhenologyMain: l1a_height = ImageHandler.get_img_height(self.__processing_paras[hh_key]) tr = TransImgL1A(ori_sim_path, scopes_roi, l1a_height, l1a_width) for k in key_list: - out_path = os.path.join(self.__workspace_preprocessed_path, k + "_preprocessed.tif") + out_path = os.path.join(self.__workspace_preprocessed_path, k.split('_')[6] + '_' + k.split('_')[10] + "_preprocessed.tif") tr.cut_L1A(self.__processing_paras[k], out_path) self.__preprocessed_paras.update({k: out_path}) self._name_tr_dic.update({name: tr}) @@ -173,8 +173,9 @@ class PhenologyMain: scopes_roi = p.cal_intersect_shp(intersect_shp_path, para_names_geo, self.__processing_paras, scopes) cutted_img_paths = p.cut_imgs_VP(self.__workspace_preprocessing_path, para_names_geo, self.__processing_paras, intersect_shp_path, name) + name_d = name.split('_')[6] self.__preprocessed_paras.update({name + '_sim_ori': cutted_img_paths.get(name + '_sim_ori')}) - self.__preprocessed_paras.update({name + '_Covering': cutted_img_paths.get('Covering')}) + self.__preprocessed_paras.update({name_d + '_Covering': cutted_img_paths.get('Covering')}) self.preprocess_single_tar(name, scopes_roi) @@ -277,7 +278,7 @@ class PhenologyMain: sim_ori_path = self.__preprocessed_paras[sim_ori_key] hh_path = self.__preprocessed_paras[name + "_HH"] - hh_geo_path = os.path.join(self.__workspace_processing_path, name.split('-')[0] + '_geo.tif') + hh_geo_path = os.path.join(self.__workspace_processing_path, os.path.split(os.path.basename(hh_path))[0] + '_geo.tif') paramter = self.__processing_paras[name + "paraMeter"] self.calInterpolation_bil_Wgs84_rc_sar_sigma(paramter, sim_ori_path, hh_path, hh_geo_path) @@ -290,7 +291,7 @@ class PhenologyMain: logger.info("read phenology Measure.csv success!") # 添加四极化后向散射系数到特征图中 - feature_tif_dir = os.path.join(self.__workspace_processing_path, name, 'features') + feature_tif_dir = os.path.join(self.__workspace_processing_path, name.split('_')[6], 'features') if not os.path.exists(feature_tif_dir): os.makedirs(feature_tif_dir) origin_xml = self.__processing_paras[name + "_Origin_META"] @@ -319,7 +320,7 @@ class PhenologyMain: rows = self.imageHandler.get_img_height(hh_hv_vh_vv_list[0]) featureInput = self.__getInputFeatures() - feature_dir = CreateFeature.decompose_single_tar(hh_hv_vh_vv_list, self.__workspace_processing_path, self.__workspace_preprocessing_path, name, self._env_str, rows, cols, FILTER_SIZE=3, debug=DEBUG, FeatureInput=featureInput) + feature_dir = CreateFeature.decompose_single_tar(hh_hv_vh_vv_list, self.__workspace_processing_path, self.__workspace_preprocessing_path, name, self._env_str, rows, cols, FILTER_SIZE=7, debug=DEBUG, FeatureInput=featureInput) feature_geo_dir = self.features_geo(feature_dir, paramter, sim_ori_path, name) # # 获取训练集提取特征的信息 @@ -350,9 +351,9 @@ class PhenologyMain: return feature_geo_dir, train_data_dic def features_geo(self, features_path, paraMeter, sim_ori, sar_name): - dir = os.path.join(self.__workspace_processing_path, sar_name, 'features_geo') + dir = os.path.join(self.__workspace_processing_path, sar_name.split('_')[6], 'features_geo') if not os.path.exists(dir): - os.mkdir(dir) + os.makedirs(dir) in_tif_paths = list(glob.glob(os.path.join(features_path, '*.tif'))) processes_num = min([len(in_tif_paths), multiprocessing_num, multiprocessing.cpu_count() - 1]) pool = multiprocessing.Pool(processes=processes_num) @@ -384,7 +385,8 @@ class PhenologyMain: feature_dir, train_data_dic = self.create_feature_single_tar(name) # 生成训练集 # X_train_part, Y_train_part, optimal_feature = ml.gene_optimal_train_set(train_data_dic, feature_dir, 0.08, 0.7) - X_train_part, Y_train_part = ml.gene_train_set(train_data_dic, feature_dir) + + X_train_part, Y_train_part = ml.gene_train_set_deLandcover(train_data_dic, feature_dir, self.__preprocessed_paras[name.split('_')[6] + 'Covering'], self.__processing_paras['CoveringIDs']) name_list = ml.get_name_list(feature_dir) # 生成测试集合 @@ -442,8 +444,8 @@ class PhenologyMain: para_names = ['Covering'] mask_dir = os.path.join(self.__workspace_processing_path, name + '\\') bare_land_mask_path = roi().roi_process_VP(para_names, mask_dir, - self.__processing_paras, self.__preprocessed_paras, name) - product_path_pro = os.path.join(self.__product_dic, os.path.basename(product_path).split('.tif')[0] + tar + '.tif') + self.__processing_paras, self.__preprocessed_paras, name.split('_')[6]) + product_path_pro = os.path.join(self.__product_dic, name + tar + '.tif') # 获取影像roi区域 roi.cal_roi(product_path_pro, cover_geo_path, bare_land_mask_path, background_value=0) self.imageHandler.write_quick_view(product_path_pro, color_img=True) @@ -538,8 +540,9 @@ class PhenologyMain: def resampleImgs(self, name, refer_img_path): cover_rampling_path = os.path.join(self.__workspace_processing_path, name + "_cover.tif") - pp.resampling_by_scale(self.__preprocessed_paras[name + "_Covering"], cover_rampling_path, refer_img_path) - self.__preprocessed_paras[name + "_Covering"] = cover_rampling_path + name_d = name.split('_')[6] + pp.resampling_by_scale(self.__preprocessed_paras[name_d + "_Covering"], cover_rampling_path, refer_img_path) + self.__preprocessed_paras[name_d + "_Covering"] = cover_rampling_path def create_roi(self, img_path): """ @@ -588,7 +591,7 @@ class PhenologyMain: SrcImageName = os.path.basename(product_path).split('.tif')[0] model_path = "./product.xml" meta_xml_path = os.path.join(self.__product_dic, SrcImageName + ".meta.xml") - key = os.path.basename(product_path).split('-VP.tif')[0] + '_Origin_META' + key = self.SrcImageName + '_Origin_META' para_dict = CreateMetaDict(image_path, self.__processing_paras[key], self.__workspace_processing_path, out_path1, out_path2).calu_nature() para_dict.update({"imageinfo_ProductName": "植被物候"}) diff --git a/vegetationPhenology/config.ini b/vegetationPhenology/config.ini index bf007472..aa6c4494 100644 --- a/vegetationPhenology/config.ini +++ b/vegetationPhenology/config.ini @@ -11,6 +11,6 @@ exe_name = VegetationPhenology debug = False ######2-算法处理参数###### # 影像滤波尺寸。取值范围：大于1的奇数，默认值：3 -filter_size = 3 +filter_size = 7 #每个类别最大训练样本量 max_tran__num_per_class =100000 \ No newline at end of file diff --git a/vegetationPhenology/testxmlreading.py b/vegetationPhenology/testxmlreading.py index cc3a0377..6b620221 100644 --- a/vegetationPhenology/testxmlreading.py +++ b/vegetationPhenology/testxmlreading.py @@ -51,11 +51,11 @@ def createcsv_roi_polygon(coordinates): return polygon_str if __name__ == '__main__': - xmlpath = r"E:\MicroWorkspace\GF3A_nanjing\input-ortho\test_shp\test.xml" + xmlpath = r"F:\MicroWorkspace\Micro\likun-GF3-VegetationP\vegTest.xml" tree_obj = ET.parse(xmlpath) csv_header = ['sar_img_name', 'phenology_id', 'phenology_name', 'roi_polygon'] - csvpath = r"E:\MicroWorkspace\GF3A_nanjing\input-ortho\test_shp\test.csv" + csvpath = r"F:\MicroWorkspace\Micro\likun-GF3-VegetationP\vegTest.csv" # csvcreateTitile(csvpath,csv_header) csvfile(csvpath,csv_header) # 得到所有匹配Region 标签的Element对象的list集合