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microproduct
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更新植被物候结果掩膜时背景值透明

dev
tian jiax 2024-01-05 14:19:25 +08:00
parent a6556791f2
commit 8b1a71ef36
6 changed files with 10 additions and 10 deletions
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1
.gitignore vendored
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@ -39,3 +39,4 @@
/deformation-C-SAR/tool/
/dem-C-SAR/tool/
/soilMoistureTop/tool/
/backScattering/dist/

4
Ortho/Ortho.xml
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@ -45,7 +45,7 @@
<ParaType>File</ParaType>
<DataType>tar.gz</DataType>
<ParaSource>Cal</ParaSource>
<ParaValue>E:\202306hb\sar_img\GF3_KSC_QPSI_036065_E116.2_N43.5_20230616_L1A_AHV_L10006792279.tar.gz</ParaValue>
<ParaValue>E:\202306hb\sar_img\GF3B_SYC_QPSI_008316_E116.1_N43.3_20230622_L1A_AHV_L10000202892.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_QPSI_036065_E116.2_N43.5_20230616_L1A_AHV_L10006792279-ortho.tar.gz</ParaValue>
<ParaValue>D:\micro\WorkSpace\Ortho\Output\GF3B_SYC_QPSI_008316_E116.1_N43.3_20230622_L1A_AHV_L10000202892-ortho.tar.gz</ParaValue>
<MaxValue>DEFAULT</MaxValue>
<MinValue>DEFAULT</MinValue>
<OptionValue>DEFAULT</OptionValue>

BIN
backScattering/dist/BackScatteringMain.exe vendored
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2
tool/algorithm/algtools/ROIAlg.py
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@ -224,7 +224,7 @@ class ROIAlg:
for i in range(0, im_bands):
tif_array[i, :, :][np.isnan(mask_array)] = background_value
tif_array[i, :, :][mask_array == 0] = background_value
image_handler.write_img(out_tif_path, proj, geotrans, tif_array, '-9999')
image_handler.write_img(out_tif_path, proj, geotrans, tif_array, background_value)
logger.info("cal_roi success, path: %s", out_tif_path)
return True

10
vegetationPhenology/VegetationPhenology.xml
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@ -37,7 +37,7 @@
<ParaType>File</ParaType>
<DataType>tar.gz</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>G:\VegetationPhenology-likun\rusuoces\GF3C_MYC_QPSI_006270_E100.4_N27.0_20230615_L1A_AHV_L10000158764-ortho.tar.gz</ParaValue>
<ParaValue>E:\VegetationPhenology-likun\rusuoces\GF3C_MYC_QPSI_006270_E100.4_N27.0_20230615_L1A_AHV_L10000158764-ortho.tar.gz</ParaValue>
<MaxValue>DEFAULT</MaxValue>
<MinValue>DEFAULT</MinValue>
<OptionValue>DEFAULT</OptionValue>
@ -51,7 +51,7 @@
<ParaType>File</ParaType>
<DataType>csv</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>G:\VegetationPhenology-likun\rusuoces\VegetationPhe_samples.csv</ParaValue>
<ParaValue>E:\VegetationPhenology-likun\rusuoces\VegetationPhe_samples.csv</ParaValue>
<MaxValue>DEFAULT</MaxValue>
<MinValue>DEFAULT</MinValue>
<OptionValue>DEFAULT</OptionValue>
@ -65,7 +65,7 @@
<ParaType>File</ParaType>
<DataType>tif</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>G:\VegetationPhenology-likun\rusuoces\landcover.tif</ParaValue>
<ParaValue>E:\VegetationPhenology-likun\rusuoces\N47_25_2020LC030\n47_25_2020lc030.tif</ParaValue>
<EnModification>True</EnModification>
<EnMultipleChoice>False</EnMultipleChoice>
<Control>File</Control>
@ -80,7 +80,7 @@
<ParaType>Value</ParaType>
<DataType>string</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>empty</ParaValue>
<ParaValue>10</ParaValue>
<EnModification>True</EnModification>
<EnMultipleChoice>False</EnMultipleChoice>
<Control>UploadInput</Control>
@ -113,7 +113,7 @@
<ParaType>Value</ParaType>
<DataType>string</DataType>
<ParaSource>Man</ParaSource>
<ParaValue>0,1,2,7,8,9,10</ParaValue>
<ParaValue>0,1,2,7,8,9,10,11,12,13</ParaValue>
<EnModification>True</EnModification>
<EnMultipleChoice>True</EnMultipleChoice>
<Control>UploadInput</Control>

3
vegetationPhenology/VegetationPhenologyMain.py
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@ -381,7 +381,7 @@ 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, 0.07, 0.85)
X_train_part, Y_train_part, optimal_feature = ml.gene_optimal_train_set(train_data_dic, feature_dir, 0.08, 0.85)
name_list = ml.get_name_list(feature_dir)
if len(optimal_feature) <= 0:
logger.error('特征筛选结果为空，无可用特征作为训练集')
@ -527,7 +527,6 @@ class PhenologyMain:
# product_geo_path = self.__product_dic + img_name + '_VegetationPhenologyProduct.tif'
# int_16_array = np.array(array, dtype=np.int16)
rows, cols = self.get_name_rows_cols(img_name)
array = np.zeros((rows, cols), dtype='float16')
array[row_list, col_list] = Y_test