更新后向散射系数，修改配准内存溢出问题

Ortho/OrthoMain.spec

@@ -1,6 +1,28 @@
 # -*- 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
 
 

backScattering/BackScatteringMain.py

@@ -300,6 +300,7 @@ class ScatteringMain:
         # 对映射表进行校正
         sim_ori_tiff = out_dir_path + "\\" + "RD_sim_ori.tif"
         out_sim_ori = out_dir_path + "\\" + "sim_ori-ortho.tif"
+        out_sim_ori_temp = self.__workspace_baseMap_path + "\\" + "sim_ori-ortho.tif"
         parameter_path = os.path.join(self.__workspace_processing_path, "orth_para.txt")
         in_tif_paths = list(glob.glob(os.path.join(slc_paths, '*.tiff')))
         out_rpc_db = os.path.join(self.__workspace_baseMap_path, 'rpc_line.tif')
@@ -335,7 +336,8 @@ class ScatteringMain:
         lon_new = im_geotrans[0] + x
         lat_new = im_geotrans[3] - y
         im_geosNew = [lon_new, im_geotrans[1], im_geotrans[2], lat_new, im_geotrans[4], im_geotrans[5]]
-        ImageHandler().write_img(out_sim_ori, im_proj, im_geosNew, im_arr)
+        ImageHandler().write_img(out_sim_ori_temp, im_proj, im_geosNew, im_arr)
+        pp.resample_by_gdal(out_sim_ori_temp, out_sim_ori)  # todo 重采样为方像元
         os.remove(sim_ori_tiff)
         return out_sim_ori
 

backScattering/BackScatteringMain.spec

@@ -1,6 +1,28 @@
 # -*- 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
 
 

landcover-S-SAR/LandCover-S-SAR.xml

@@ -38,7 +38,7 @@
         <ParaType>File</ParaType>
         <DataType>tar.gz</DataType>
 		<ParaSource>Man</ParaSource>
-		<ParaValue>F:\MicroWorkspace\20240814tw\HJ2E_KRN_QPS_008852_E110.6_N20.1_20240515_SLC_AHV_L10000208028-Ortho.tar.gz</ParaValue>
+		<ParaValue>F:\MicroWorkspace\S_SAR\AHV\HJ2E_MYC_QPS_001752_E118.0_N37.7_20230204_SLC_AHV_L10000010458-Ortho.tar.gz</ParaValue>
         <EnModification>True</EnModification> 
         <EnMultipleChoice>False</EnMultipleChoice> 
         <Control>File</Control> 
@@ -51,9 +51,9 @@
         <ParaChsName>标记数据</ParaChsName>
         <Description>标记的样本数据</Description>
         <ParaType>File</ParaType>
-        <DataType>csv</DataType>
+        <DataType>zip</DataType>
 		<ParaSource>Man</ParaSource>
-        <ParaValue>F:\MicroWorkspace\20240814tw\LandCover.csv</ParaValue>
+        <ParaValue>F:\al_zhongji\S-SAR-data\landCover\SSAR_landcover_landaCoverSample.zip</ParaValue>
         <EnModification>True</EnModification> 
         <EnMultipleChoice>True</EnMultipleChoice> 
         <Control>UploadInput</Control> 
@@ -103,7 +103,7 @@
         <ParaType>File</ParaType>
         <DataType>tar.gz</DataType>
 		<ParaSource>Man</ParaSource>
-        <ParaValue>D:\micro\SWork\LandCover\Output\HJ2E_KRN_QPS_008852_E110.6_N20.1_20240515_SLC_AHV_L10000208028-Ortho-LANDCLASS.tar.gz</ParaValue>
+        <ParaValue>D:\micro\SWork\LandCover\Output\HJ2E_MYC_QPS_001752_E118.0_N37.7_20230204_SLC_AHV_L10000010458-Ortho-LANDCLASS.tar.gz</ParaValue>
       </Parameter>
     </Outputs>
   </AlgCompt>

soilMoisture-S-SAR/SoilMoistureMain.py

@@ -386,7 +386,7 @@ class MoistureMain:
         # data[data > soil_moisture_value_max] = soil_moisture_value_max
         data[data < soil_moisture_value_min] = -9999
         data[data > soil_moisture_value_max] = -9999
-        self.imageHandler.write_img(product_path, proj, geos, data)
+        self.imageHandler.write_img(product_path, proj, geos, data, '-9999')
 
         # 生成快视图
         self.imageHandler.write_quick_view(product_path)

soilMoisture-S-SAR/SoilMoistureMain.spec

@@ -1,6 +1,28 @@
 # -*- 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
 
 

tool/algorithm/algtools/PreProcess.py

@@ -276,6 +276,40 @@ class PreProcess:
             logger.error('shapely.geos.TopologicalError occurred!')
             return
 
+    @staticmethod
+    def resample_by_gdal(in_path, out_path):
+        src_ds = gdal.Open(in_path, gdal.GA_ReadOnly)
+
+        # 设置目标影像的投影和范围
+        target_projection = src_ds.GetProjection()
+        target_geotransform = src_ds.GetGeoTransform()
+
+        x_scale = target_geotransform[1]
+        y_scale = target_geotransform[5]
+        scale = [x_scale, np.abs(y_scale)]
+        new_scale = np.max(scale)
+
+        dst_geotransform = [target_geotransform[0], new_scale, target_geotransform[2], target_geotransform[3],
+                            target_geotransform[4], -new_scale]
+        target_x_size = int(src_ds.RasterXSize * x_scale / new_scale)  # 假设我们要将影像大小缩小到原来的一半
+        target_y_size = int(src_ds.RasterYSize * np.abs(y_scale) / new_scale)
+
+        # 创建输出驱动
+        driver = gdal.GetDriverByName('GTiff')
+
+        # 创建输出文件
+        dst_ds = driver.Create(out_path, target_x_size, target_y_size, src_ds.RasterCount,
+                               src_ds.GetRasterBand(1).DataType)
+        dst_ds.SetGeoTransform(dst_geotransform)
+        dst_ds.SetProjection(target_projection)
+
+        # 执行重采样
+        gdal.ReprojectImage(src_ds, dst_ds, None, None, gdal.GRA_Bilinear)  # 使用双线性插值
+
+        # 关闭数据集
+        dst_ds = None
+        src_ds = None
+
 
     @staticmethod
     def write_polygon_shp(out_shp_path, point_list, EPSG =32649):

tool/algorithm/image/ImageHandle.py

@@ -693,7 +693,12 @@ class ImageHandler:
         img_col_start = x_split * 1
         img_col_end = x_split * 3
         img_row_start = y_split * 1
-        img_row_end = y_split *3
+        img_row_end = y_split * 3
+        cols = img_col_end - img_col_start
+        rows = img_row_end - img_row_start
+        if cols > 10000 or rows > 10000:
+            img_col_end = img_col_start + 10000
+            img_row_end = img_row_start + 10000
 
         point_upleft = self.trans_rowcol2geo(img_geotrans, img_col_start, img_row_start)
         point_upright = self.trans_rowcol2geo(img_geotrans, img_col_end, img_row_start)