KJ135
/
microproduct
mirror of http://172.16.0.12:5000/WBJY/microproduct.git
4
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

更新植被物候流程，提前淹没掉非地区区域，修改干涉形变快视图拉伸，修改大气延迟校正影像输入方式

dev
tian jiax 2024-07-16 11:38:55 +08:00
parent ca2d68cc03
commit 48f9d5bb7e
26 changed files with 312 additions and 262 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

3
.idea/misc.xml
View File

@ -1,4 +1,7 @@
<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="Black">
<option name="sdkName" value="Python 3.8 (micro)" />
</component>
<component name="ProjectRootManager" version="2" project-jdk-name="Python 3.8 (micro)" project-jdk-type="Python SDK" />
</project>

49
Ortho/OrthOne.spec
View File

@ -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',
)

4
Ortho/Ortho.xml
View File

@ -45,7 +45,7 @@
<ParaType>File</ParaType>
<DataType>tar.gz</DataType>
<ParaSource>Cal</ParaSource>
<ParaValue>F:\MicroWorkspace\def_GF3\GF3_KSC_FSII_036108_E120.1_N31.0_20230619_L1A_VHVV_L10006793347.tar.gz</ParaValue>
<ParaValue>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</ParaValue>
<EnModification>True</EnModification>
<EnMultipleChoice>False</EnMultipleChoice>
<Control>File</Control>
@ -92,7 +92,7 @@
<ParaType>File</ParaType>
<DataType>tar.gz</DataType>
<ParaSource>Cal</ParaSource>
<ParaValue>D:\micro\WorkSpace\ortho\Output\GF3_KSC_FSII_036108_E120.1_N31.0_20230619_L1A_VHVV_L10006793347-ortho.tar.gz</ParaValue>
<ParaValue>D:\micro\WorkSpace\ortho\Output\GF3_SYC_FSII_036654_E120.0_N30.7_20230727_L1A_HHHV_L10006808388-ortho.tar.gz</ParaValue>
<MaxValue>DEFAULT</MaxValue>
<MinValue>DEFAULT</MinValue>
<OptionValue>DEFAULT</OptionValue>

6
Ortho/OrthoMain.py
View File

@ -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!")
@ -394,8 +394,6 @@ class OrthoMain:
raise Exception('No CorrectMethod')
def RPC_process_handle(self):
logger.info(datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f'))
# print(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)

23
Ortho/OrthoMain.spec
View File

@ -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

99
atmosphericDelay-C-SAR/AtmosphericDelay.xml
View File

@ -1,7 +1,7 @@
<?xml version='1.0' encoding='utf-8'?>
<Root>
<TaskID>CSAR_202107275419_0001-0</TaskID>
<WorkSpace>E:\Result_GF3\</WorkSpace>
<WorkSpace>D:\micro\WorkSpace\</WorkSpace>
<AlgCompt>
<DataTransModel>File</DataTransModel>
<Artificial>ElementAlg</Artificial>
@ -9,20 +9,20 @@
<DllName>AtmosphericDelay-C-SAR-V2.2.exe</DllName>
<ChsName>大气延迟校正产品</ChsName>
<AlgorithmDesc>微波卫星3-5级产品生产模型</AlgorithmDesc>
<AlgorithmAlias>AtmosphericDelay-C-SAR-V2.2-1</AlgorithmAlias>
<AlgorithmAlias>AtmosphericDelay-C-SAR-V2.2-1</AlgorithmAlias>
<Version>2.2</Version>
<AlgorithmClass>辐射类产品_大气延迟校正</AlgorithmClass>
<AlgorithmLevel>5</AlgorithmLevel>
<AlgoirthmID>AtmosphericDelay_中科卫星应用德清研究院_2.2</AlgoirthmID>
<AlgoirthmID>AtmosphericDelay_中科卫星应用德清研究院_2.2</AlgoirthmID>
<Author>中科卫星应用德清研究院</Author>
<Type>景-算法</Type>
<InputTestFilePath />
<InputTestFilePath />
<InputTestFileName />
<OutputTestFilePath />
<OutputTestFilePath />
<OutputTestFileName />
<jdkVersion>1.8</jdkVersion>
<algDevlanguage>python</algDevlanguage>
<Environment>
<Environment>
<IsCluster>0</IsCluster>
<ClusterNum>0</ClusterNum>
<OperatingSystem>Windows10</OperatingSystem>
@ -33,48 +33,51 @@
<Bandwidth>无需求</Bandwidth>
<GPU>无需求</GPU>
</Environment>
<Utility Satellite="GF3C" Sensor="MSS" Resolution="1" />
<Utility Satellite="GF3C" Sensor="MSS" Resolution="1" />
<Inputs ParameterNum="6">
<Parameter>
<ParaName>MasterSarData</ParaName>
<ParaChsName>主影像</ParaChsName>
<Description>经过几何校正和地形校正的SAR影像产品</Description>
<Parameter>
<ParaName>MainImg</ParaName>
<ParaChsName>主影像时间</ParaChsName>
<Description>哨兵数据主影像的时间，来源于数据名称</Description>
<ParaType>Value</ParaType>
<DataType>string</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>20161129</ParaValue>
<EnModification>True</EnModification>
<EnMultipleChoice>False</EnMultipleChoice>
<Control>UploadInput</Control>
<InputType>Aux</InputType>
<InputNum>0</InputNum>
<DateFrom>Aux</DateFrom>
</Parameter>
<Parameter>
<ParaName>SARS</ParaName>
<ParaChsName>SAR影像文件夹路径</ParaChsName>
<Description>哨兵1号数据存放的文件夹</Description>
<ParaType>File</ParaType>
<DataType>tar.gz</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>E:\GF3Data\AtmophericDealy\GF3_SAY_FSI_001614_E113.2_N34.5_20161129_L1A_HHHV_L10002015686.tar.gz</ParaValue>
<ParaSource>Man</ParaSource>
<ParaValue>
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
</ParaValue>
<EnModification>True</EnModification>
<EnMultipleChoice>False</EnMultipleChoice>
<Control>File</Control>
<InputType>Satellite</InputType>
<InputNum>1</InputNum>
<InputNum>0</InputNum>
<DateFrom>S1A</DateFrom>
</Parameter>
<Parameter>
<ParaName>AuxiliarySarData</ParaName>
<ParaChsName>辅影像</ParaChsName>
<Description>经过几何校正和地形校正的SAR影像产品</Description>
<ParaType>File</ParaType>
<DataType>tar.gz</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>E:\GF3Data\AtmophericDealy\GF3_KAS_FSI_002034_E113.4_N34.7_20161228_L1A_HHHV_L10002077539.tar.gz</ParaValue>
<EnModification>True</EnModification>
<EnMultipleChoice>False</EnMultipleChoice>
<Control>File</Control>
<InputType>Satellite</InputType>
<InputNum>1</InputNum>
<DateFrom>S1A</DateFrom>
</Parameter>
<Parameter>
<ParaName>MasterNC</ParaName>
<ParaChsName>主影像气象数据</ParaChsName>
<Description>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</Description>
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</Description>
<ParaType>File</ParaType>
<DataType>zip</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>E:\GF3Data\AtmophericDealy\CASR_atmo_ERA5_N33_N36_E112_E115_20161228_22.zip</ParaValue>
<ParaSource>Man</ParaSource>
<ParaValue>G:\辅助数据\GF3Data\AtmophericDealy\CASR_atmo_ERA5_N33_N36_E112_E115_20161228_22.zip</ParaValue>
<EnModification>True</EnModification>
<EnMultipleChoice>False</EnMultipleChoice>
<Control>File</Control>
@ -82,16 +85,16 @@
<InputNum>1</InputNum>
<DateFrom>Aux</DateFrom>
</Parameter>
<Parameter>
<Parameter>
<ParaName>AuxiliaryNC</ParaName>
<ParaChsName>辅影像气象数据</ParaChsName>
<Description>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</Description>
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</Description>
<ParaType>File</ParaType>
<DataType>zip</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>E:\GF3Data\AtmophericDealy\CASR_atmo_ERA5_N33_N36_E112_E115_20161129_22.zip</ParaValue>
<ParaSource>Man</ParaSource>
<ParaValue>G:\辅助数据\GF3Data\AtmophericDealy\CASR_atmo_ERA5_N33_N36_E112_E115_20161129_22.zip</ParaValue>
<EnModification>True</EnModification>
<EnMultipleChoice>False</EnMultipleChoice>
<Control>File</Control>
@ -105,8 +108,12 @@
<Description>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</Description>
<ParaType>File</ParaType>
<DataType>zip</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>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</ParaValue>
<ParaSource>Man</ParaSource>
<ParaValue>
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</ParaValue>
<EnModification>True</EnModification>
<EnMultipleChoice>False</EnMultipleChoice>
<Control>File</Control>
@ -115,20 +122,20 @@
<DateFrom>DEM</DateFrom>
</Parameter>
<Parameter>
<ParaName>box</ParaName>
<ParaName>box</ParaName>
<ParaChsName>经纬度包围盒</ParaChsName>
<Description>经纬度包围盒SNWE。例子：30.0;30.2;117.3;117.5</Description>
<ParaType>Value</ParaType>
<DataType>string</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>34.60;34.67;113.05;113.18</ParaValue>
<ParaSource>Man</ParaSource>
<ParaValue>34.64;34.67;113.15;113.18</ParaValue>
<EnModification>True</EnModification>
<EnMultipleChoice>True</EnMultipleChoice>
<Control>UploadInput</Control>
<InputType>Aux</InputType>
<InputNum>0</InputNum>
<DateFrom>Aux</DateFrom>
</Parameter>
</Parameter>
</Inputs>
<Outputs ParameterNum="1">
<Parameter>
@ -137,8 +144,8 @@
<Description>大气延迟校正产品反演</Description>
<ParaType>File</ParaType>
<DataType>tar.gz</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>E:\Result_GF3\AtmosphericDelay\Output\GF3_SAY_FSI_001614_E113.2_N34.5_20161129_L1A_HHHV_L10002015686-IADC.tar.gz</ParaValue>
<ParaSource>Man</ParaSource>
<ParaValue>D:\micro\WorkSpace\AtmosphericDelay\Output\GF3_SAY_FSI_001614_E113.2_N34.5_20161129_L1A_HHHV_L10002015686</ParaValue>
</Parameter>
</Outputs>
</AlgCompt>

24
atmosphericDelay-C-SAR/AtmosphericDelayMain.py
View File

@ -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:

4
backScattering/BackScatteringMain.py
View File

@ -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")

4
deformation-C-SAR/DeformationImageHandle.py
View File

@ -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

4
dem-C-SAR/DemImageHandle.py
View File

@ -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

62
dem-C-SAR/DemMain.py
View File

@ -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)

17
dem-C-SAR/Dem_C_SAR_V3.xml
View File

@ -41,7 +41,7 @@
<MinValue>DEFAULT</MinValue>
<MaxValue>DEFAULT</MaxValue>
<ParaSource>Man</ParaSource>
<ParaValue>20161129</ParaValue>
<ParaValue>20230615</ParaValue>
<EnModification>True</EnModification>
<EnMultipleChoice>False</EnMultipleChoice>
<Control>UploadInput</Control>
@ -60,8 +60,8 @@
<MaxValue>DEFAULT</MaxValue>
<ParaSource>Cal</ParaSource>
<ParaValue>
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</ParaValue>
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</ParaValue>
<EnModification>True</EnModification>
<EnMultipleChoice>False</EnMultipleChoice>
<Control>File</Control>
@ -72,14 +72,14 @@
<Parameter>
<ParaName>box</ParaName>
<ParaChsName>经纬度包围盒</ParaChsName>
<Description>经纬度包围盒SNWE。例子：30.0;30.2;117.3;117.5 37;38.2;108.87;109.1</Description>
<Description>经纬度包围盒SNWE。例子：37;38.2;108.87;109.1</Description>
<ParaType>value</ParaType>
<DataType>string</DataType>
<OptionValue>DEFAULT</OptionValue>
<MinValue>DEFAULT</MinValue>
<MaxValue>DEFAULT</MaxValue>
<ParaSource>Man</ParaSource>
<ParaValue>34.60;34.67;113.05;113.18</ParaValue>
<ParaValue>44.14;44.3;116.351;116.437</ParaValue>
<EnModification>True</EnModification>
<EnMultipleChoice>True</EnMultipleChoice>
<Control>UploadInput</Control>
@ -92,12 +92,12 @@
<ParaChsName>DEM高程数据路径</ParaChsName>
<Description>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</Description>
<ParaType>File</ParaType>
<DataType>File</DataType>
<DataType>tif</DataType>
<OptionValue>DEFAULT</OptionValue>
<MinValue>DEFAULT</MinValue>
<MaxValue>DEFAULT</MaxValue>
<ParaSource>Cal</ParaSource>
<ParaValue>D:\micro\microproduct_depdence\GF3-Deformation\dem</ParaValue>
<ParaValue>F:\MicroWorkspace\COPDEM\COPDEM_Int16\115E39N_COP30.tif</ParaValue>
<EnModification>True</EnModification>
<EnMultipleChoice>False</EnMultipleChoice>
<Control>File</Control>
@ -137,8 +137,7 @@
<MinValue>DEFAULT</MinValue>
<MaxValue>DEFAULT</MaxValue>
<NoDataValue>-9999</NoDataValue>
<ParaValue>
D:\micro\WorkSpace\Dem\Output\GF3_SAY_FSI_001614_E113.2_N34.5_20161129_L1A_HHHV_L10002015686-DEM.tar.gz</ParaValue>
<ParaValue>D:\micro\WorkSpace\Dem\Output\GF3B_MYC_UFS_008208_E116.5_N44.2_20230615_L1A_DH_L10000199472-DEM.tar.gz</ParaValue>
</Parameter>
</Outputs>
</AlgCompt>

21
dem-C-SAR/ISCEApp/_internal/isce/components/isceobj/Sensor/GF3_SLC.py
View File

@ -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

3
dem-C-SAR/config.ini
View File

@ -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

4
landcover_c_sar/LandCoverMain.py
View File

@ -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)

18
landcover_c_sar/LandCover_C_SAR_V3.xml
View File

@ -42,7 +42,7 @@
<MaxValue>DEFAULT</MaxValue>
<ParaSource>Cal</ParaSource>
<ParaValue>
E:\MicroWorkspace\GF3A_nanjing\input-ortho\GF3_SAY_QPSI_011444_E118.9_N31.4_20181012_L1A_AHV_L10003515422-ortho.tar.gz</ParaValue>
F:\MicroWorkspace\GF3A_nanjing\input-ortho\GF3_SAY_QPSI_011444_E118.9_N31.4_20181012_L1A_AHV_L10003515422-ortho.tar.gz</ParaValue>
<EnModification>True</EnModification>
<EnMultipleChoice>False</EnMultipleChoice>
<Control>File</Control>
@ -55,12 +55,12 @@
<ParaChsName>标记数据</ParaChsName>
<Description>标记的样本数据</Description>
<ParaType>File</ParaType>
<DataType>csv</DataType>
<DataType>zip</DataType>
<OptionValue>DEFAULT</OptionValue>
<MinValue>DEFAULT</MinValue>
<MaxValue>DEFAULT</MaxValue>
<ParaSource>Cal</ParaSource>
<ParaValue>E:\MicroWorkspace\GF3A_nanjing\input-ortho\LandCoverLable_geo.csv</ParaValue>
<ParaValue>F:\al_zhongji\C-SAR-data\landcover\CSAR_land_LandCoverLable.zip</ParaValue>
<EnModification>True</EnModification>
<EnMultipleChoice>True</EnMultipleChoice>
<Control>UploadTable</Control>
@ -90,17 +90,16 @@
<ParaName>FeatureCombination</ParaName>
<ParaChsName>极化特征组合</ParaChsName>
<Description>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)</Description>
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)</Description>
<ParaType>Value</ParaType>
<DataType>string</DataType>
<OptionValue>DEFAULT</OptionValue>
<MinValue>DEFAULT</MinValue>
<MaxValue>DEFAULT</MaxValue>
<ParaSource>Man</ParaSource>
<ParaValue>0,1,2,7,8,9,10</ParaValue>
<ParaValue>0,1,2</ParaValue>
<EnModification>True</EnModification>
<EnMultipleChoice>True</EnMultipleChoice>
<Control>UploadInput</Control>
@ -121,8 +120,7 @@
<MaxValue>DEFAULT</MaxValue>
<NoDataValue>DEFAULT</NoDataValue>
<ParaSource>Man</ParaSource>
<ParaValue>
D:\micro\WorkSpace\LandCover\Output\GF3_SAY_QPSI_011444_E118.9_N31.4_20181012_L1A_AHV_L10003515422-ortho-LANDClASS.tar.gz</ParaValue>
<ParaValue>D:\micro\WorkSpace\LandCover\Output\GF3_SAY_QPSI_011444_E118.9_N31.4_20181012_L1A_AHV_L10003515422-ortho-LANDCLASS.tar.gz</ParaValue>
</Parameter>
</Outputs>
</AlgCompt>

28
soilMoistureTop/SoilMoisture.xml
View File

@ -36,16 +36,16 @@
<ParaType>File</ParaType>
<DataType>tar.gz</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>F:\202306hb\sar_img\GF3B_SYC_QPSI_008316_E116.1_N43.3_20230622_L1A_AHV_L10000202892-cal.tar.gz</ParaValue>
<ParaValue>F:\Tian-GF3-Wenchang\GF3_SYC_QPSI_040488_E110.7_N19.9_20240418_L1A_AHV_L10006923783-cal.tar.gz</ParaValue>
</Parameter>
<Parameter>
<ParaName>Covering</ParaName>
<ParaChsName>地表覆盖类型数据</ParaChsName>
<Description>经过地理定标（WGS84）的地表覆盖类型数据</Description>
<ParaType>File</ParaType>
<DataType>zip</DataType>
<DataType>tif</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>E:\辅助数据\GF3Data\soilMoisture\CSAR_solim_50T_20220101-20230101.zip</ParaValue>
<ParaValue>F:\Tian-GF3-Wenchang\landCover.tif</ParaValue>
</Parameter>
<Parameter>
<ParaName>CoveringIDs</ParaName>
@ -64,9 +64,9 @@
<ParaChsName>NDVI数据</ParaChsName>
<Description>经过地理定标（WGS84）的NDVI数据</Description>
<ParaType>File</ParaType>
<DataType>zip</DataType>
<DataType>tif</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>E:\辅助数据\GF3Data\soilMoisture\CSAR_solim_S2_202306_NDVI.zip</ParaValue>
<ParaValue>F:\Tian-GF3-Wenchang\NDVI\NDVI_20240417_WGS841.tif</ParaValue>
</Parameter>
<Parameter>
<ParaName>NDVIScope</ParaName>
@ -98,9 +98,9 @@
<ParaChsName>NDWI数据</ParaChsName>
<Description>经过地理定标（WGS84）的NDWI数据</Description>
<ParaType>File</ParaType>
<DataType>zip</DataType>
<DataType>tif</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>E:\辅助数据\GF3Data\soilMoisture\CSAR_solim_S2_202306_NDWI.zip</ParaValue>
<ParaValue>F:\Tian-GF3-Wenchang\NDWI\NDWI_20240417_WGS841.tif</ParaValue>
</Parameter>
<Parameter>
<ParaName>e1</ParaName>
@ -109,7 +109,7 @@
<ParaType>Value</ParaType>
<DataType>float</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>-22.482554048434324</ParaValue>
<ParaValue>5.308639240349595</ParaValue>
<MaxValue>100</MaxValue>
<MinValue>-100</MinValue>
<OptionValue>DEFAULT</OptionValue>
@ -121,7 +121,7 @@
<ParaType>Value</ParaType>
<DataType>float</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>-10.72946251632336</ParaValue>
<ParaValue>-3.546779815649669</ParaValue>
<MaxValue>100</MaxValue>
<MinValue>-100</MinValue>
<OptionValue>DEFAULT</OptionValue>
@ -133,7 +133,7 @@
<ParaType>Value</ParaType>
<DataType>float</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>-0.08238130673792357</ParaValue>
<ParaValue>92.54550090363222</ParaValue>
<MaxValue>9999</MaxValue>
<MinValue>-9999</MinValue>
<OptionValue>DEFAULT</OptionValue>
@ -145,7 +145,7 @@
<ParaType>Value</ParaType>
<DataType>float</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>1.0194495140476119</ParaValue>
<ParaValue>-0.016379035637768415</ParaValue>
<MaxValue>9999</MaxValue>
<MinValue>-9999</MinValue>
<OptionValue>DEFAULT</OptionValue>
@ -157,7 +157,7 @@
<ParaType>Value</ParaType>
<DataType>float</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>6.107713980885245</ParaValue>
<ParaValue>-67.4408236678189</ParaValue>
<MaxValue>9999</MaxValue>
<MinValue>-9999</MinValue>
<OptionValue>DEFAULT</OptionValue>
@ -169,7 +169,7 @@
<ParaType>Value</ParaType>
<DataType>float</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>-4.496951628949385</ParaValue>
<ParaValue>0.054641574960551206</ParaValue>
<MaxValue>9999</MaxValue>
<MinValue>-9999</MinValue>
<OptionValue>DEFAULT</OptionValue>
@ -183,7 +183,7 @@
<ParaType>File</ParaType>
<DataType>tar.gz</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>D:\micro\WorkSpace\SoilMoisture\Output\GF3B_SYC_QPSI_008316_E116.1_N43.3_20230622_L1A_AHV_L10000202892-cal-SMC.tar.gz</ParaValue>
<ParaValue>D:\micro\WorkSpace\SoilMoisture\Output\GF3_SYC_QPSI_040488_E110.7_N19.9_20240418_L1A_AHV_L10006923783-cal-SMC.tar.gz</ParaValue>
<MaxValue>DEFAULT</MaxValue>
<MinValue>DEFAULT</MinValue>
<OptionValue>DEFAULT</OptionValue>

13
tool/algorithm/image/ImageHandle.py
View File

@ -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)

47
tool/algorithm/ml/machineLearning.py
View File

@ -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]

20
tool/algorithm/polsarpro/createfeature.py
View File

@ -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

7
tool/algorithm/xml/AlgXmlHandle.py
View File

@ -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():

8
vegetationPhenology/VegetationPhenology.xml
View File

@ -107,14 +107,14 @@
<Parameter>
<ParaName>FeatureCombination</ParaName>
<ParaChsName>极化特征组合</ParaChsName>
<Description>可选极化特征组合一、共14种特征（编号依次为0-13）
<Description>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)</Description>
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)</Description>
<ParaType>Value</ParaType>
<DataType>string</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>0,1,2,7,8,9,10</ParaValue>
<ParaValue>0,1,2,3,4,5,6,7,8,9</ParaValue>
<EnModification>True</EnModification>
<EnMultipleChoice>True</EnMultipleChoice>
<Control>UploadInput</Control>

33
vegetationPhenology/VegetationPhenologyAuxData.py
View File

@ -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

33
vegetationPhenology/VegetationPhenologyMain.py
View File

@ -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"})

2
vegetationPhenology/config.ini
View File

@ -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

4
vegetationPhenology/testxmlreading.py
View File

@ -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