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Browse files- Task500_Glacier_zonefronts/ensemble/eval_results.json +1 -0
- Task500_Glacier_zonefronts/fold_0/debug.json +87 -0
- Task500_Glacier_zonefronts/fold_0/distance_errors.txt +120 -0
- Task500_Glacier_zonefronts/fold_0/eval_results.json +1 -0
- Task500_Glacier_zonefronts/fold_0/model_final_checkpoint.model +3 -0
- Task500_Glacier_zonefronts/fold_0/model_final_checkpoint.model.pkl +3 -0
- Task500_Glacier_zonefronts/fold_0/plans.pkl +3 -0
- Task500_Glacier_zonefronts/fold_0/progress.png +0 -0
- Task500_Glacier_zonefronts/fold_0/training_log_2022_4_6_13_42_45.txt +353 -0
- Task500_Glacier_zonefronts/fold_0/training_log_2022_4_6_14_16_01.txt +0 -0
- Task500_Glacier_zonefronts/fold_1/debug.json +87 -0
- Task500_Glacier_zonefronts/fold_1/eval_results.json +1 -0
- Task500_Glacier_zonefronts/fold_1/model_final_checkpoint.model +3 -0
- Task500_Glacier_zonefronts/fold_1/model_final_checkpoint.model.pkl +3 -0
- Task500_Glacier_zonefronts/fold_1/progress.png +0 -0
- Task500_Glacier_zonefronts/fold_1/training_log_2022_4_11_16_28_44.txt +0 -0
- Task500_Glacier_zonefronts/fold_2/debug.json +87 -0
- Task500_Glacier_zonefronts/fold_2/eval_results.json +1 -0
- Task500_Glacier_zonefronts/fold_2/model_final_checkpoint.model +3 -0
- Task500_Glacier_zonefronts/fold_2/model_final_checkpoint.model.pkl +3 -0
- Task500_Glacier_zonefronts/fold_2/progress.png +0 -0
- Task500_Glacier_zonefronts/fold_2/training_log_2022_4_11_16_28_44.txt +0 -0
- Task500_Glacier_zonefronts/fold_3/debug.json +87 -0
- Task500_Glacier_zonefronts/fold_3/eval_results.json +1 -0
- Task500_Glacier_zonefronts/fold_3/model_final_checkpoint.model +3 -0
- Task500_Glacier_zonefronts/fold_3/model_final_checkpoint.model.pkl +3 -0
- Task500_Glacier_zonefronts/fold_3/progress.png +0 -0
- Task500_Glacier_zonefronts/fold_3/training_log_2022_4_11_16_28_44.txt +0 -0
- Task500_Glacier_zonefronts/fold_4/debug.json +87 -0
- Task500_Glacier_zonefronts/fold_4/eval_results.json +1 -0
- Task500_Glacier_zonefronts/fold_4/model_final_checkpoint.model +3 -0
- Task500_Glacier_zonefronts/fold_4/model_final_checkpoint.model.pkl +3 -0
- Task500_Glacier_zonefronts/fold_4/progress.png +0 -0
- Task500_Glacier_zonefronts/fold_4/training_log_2022_4_11_16_28_44.txt +0 -0
- Task500_Glacier_zonefronts/plans.pkl +3 -0
Task500_Glacier_zonefronts/ensemble/eval_results.json
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{"Zone_Segmentation": {"Zone_Precision": {"Average_Precision": 0.8762225169564792, "Average_Precision_NA_Area": 0.9951455756080556, "Average_Precision_Stone": 0.8410944753396893, "Average_Precision_Glacier": 0.730848376193718, "Average_Precision_Ocean_and_Ice_Melange": 0.9378016406844543}, "Zone_Recall": {"Average_Recall": 0.793567272791971, "Average_Recall_NA_Area": 0.8522035009398647, "Average_Recall_Stone": 0.5462115174049614, "Average_Recall_Glacier": 0.9344260412705369, "Average_Recall_Ocean_and_Ice_Melange": 0.8414280315525208}, "Zone_F1": {"Average_F1 Score": 0.803288490267958, "Average_F1 Score_NA_Area": 0.9126747209206166, "Average_F1 Score_Stone": 0.6355228186513061, "Average_F1 Score_Glacier": 0.8151667002754798, "Average_F1 Score_Ocean_and_Ice_Melange": 0.8497897212244295}, "Zone_IoU": {"Average_IoU": 0.7129772572682996, "Average_IoU_NA_Area": 0.8486857971854096, "Average_IoU_Stone": 0.4968808213932209, "Average_IoU_Glacier": 0.6969559354443163, 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Task500_Glacier_zonefronts/fold_0/debug.json
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{
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Task500_Glacier_zonefronts/fold_0/distance_errors.txt
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Task500_Glacier_zonefronts/fold_0/eval_results.json
ADDED
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"Confidence_interval": [87.69459676759655, 99.07957865804764], "mean": 93.3870877128221, "standard_deviation": 299.2926611967921}, "summer": {"Number_no_front": 0, "Mean_mean_distance": 121.20281620555605, "Mean_median_distance": 49.904898618633254, "Median_mean_distance": 113.44905382110068, "Median_median_distance": 40.0, "Confidence_interval": [100.56486660624493, 107.10286247768742], "mean": 103.83386454196618, "standard_deviation": 265.22545895087865}}, "COL": {"all": {"Number_no_front": 1, "Mean_mean_distance": 1184.2509032928726, "Mean_median_distance": 513.1889977690979, "Median_mean_distance": 275.0101138286102, "Median_median_distance": 50.22912195401098, "Confidence_interval": [614.8798784922799, 632.5091940447364], "mean": 623.6945362685082, "standard_deviation": 1896.0187256091438}, "winter": {"Number_no_front": 1, "Mean_mean_distance": 1374.9844123310118, "Mean_median_distance": 588.818327372369, "Median_mean_distance": 275.0101138286102, "Median_median_distance": 54.8731079895686, "Confidence_interval": [683.8956828347389, 711.16836870779], "mean": 697.5320257712644, "standard_deviation": 2139.0496705800388}, "summer": {"Number_no_front": 0, "Mean_mean_distance": 939.0221059581228, "Mean_median_distance": 415.9512882791779, "Median_mean_distance": 251.67875463820252, "Median_median_distance": 45.614657384926446, "Confidence_interval": [529.1430587059797, 550.4900062538695], "mean": 539.8165324799246, "standard_deviation": 1570.8794112449243}}, "S1": {"Number_no_front": 1, "Mean_mean_distance": 2060.1756299809686, "Mean_median_distance": 973.8228057079207, "Median_mean_distance": 1075.3531208934064, "Median_median_distance": 514.4378786891652, "Confidence_interval": [3039.5049791718475, 3153.948738569721], "mean": 3096.7268588707843, "standard_deviation": 4368.1976277585345}, "ENVISAT": {"Number_no_front": 1, "Mean_mean_distance": 235.43927206339583, "Mean_median_distance": 96.74806901610124, "Median_mean_distance": 185.0585306243028, "Median_median_distance": 44.721359549995796, "Confidence_interval": [204.08429753880256, 229.73919933092236], "mean": 216.91174843486246, "standard_deviation": 373.50906720797616}, "ERS": {"Number_no_front": 0, "Mean_mean_distance": 55.99042070259927, "Mean_median_distance": 40.0, "Median_mean_distance": 55.99042070259927, "Median_median_distance": 40.0, "Confidence_interval": [49.6298648136022, 60.94429324042302], "mean": 55.28707902701261, "standard_deviation": 80.30175060809931}, "PALSAR": {"Number_no_front": 0, "Mean_mean_distance": 134.5248222533744, "Mean_median_distance": 61.157414734608835, "Median_mean_distance": 121.84524690548584, "Median_median_distance": 71.10884365826404, "Confidence_interval": [125.60195383037737, 139.91698153482915], "mean": 132.75946768260326, "standard_deviation": 218.01328249057406}, "TSX": {"Number_no_front": 0, "Mean_mean_distance": 68.95394510865577, "Mean_median_distance": 14.881356168407082, "Median_mean_distance": 63.78332603319359, "Median_median_distance": 14.0, "Confidence_interval": [67.63481868952978, 74.82077925962345], "mean": 71.22779897457661, "standard_deviation": 281.63741297126546}, "TDX": {"Number_no_front": 0, "Mean_mean_distance": 259.78074554143234, "Mean_median_distance": 64.1839011296584, "Median_mean_distance": 156.58999217198533, "Median_median_distance": 39.59797974644666, "Confidence_interval": [261.02642834724566, 266.78732726347766], "mean": 263.90687780536166, "standard_deviation": 587.9549860672332}, "20": {"Number_no_front": 2, "Mean_mean_distance": 1585.0361499852734, "Mean_median_distance": 746.815404739497, "Median_mean_distance": 223.3566262050209, "Median_median_distance": 140.0, "Confidence_interval": [2602.254064082809, 2702.512790738309], "mean": 2652.383427410559, "standard_deviation": 4157.213082067502}, "17": {"Number_no_front": 0, "Mean_mean_distance": 134.5248222533744, "Mean_median_distance": 61.157414734608835, "Median_mean_distance": 121.84524690548584, "Median_median_distance": 71.10884365826404, "Confidence_interval": [125.60195383037737, 139.91698153482915], "mean": 132.75946768260326, "standard_deviation": 218.01328249057406}, "7": {"Number_no_front": 0, "Mean_mean_distance": 198.93741786721372, "Mean_median_distance": 48.46424911302755, "Median_mean_distance": 127.66116708376876, "Median_median_distance": 29.698484809834994, "Confidence_interval": [236.574126825043, 241.7128237815767], "mean": 239.14347530330986, "standard_deviation": 561.7960264634964}}}
|
Task500_Glacier_zonefronts/fold_0/model_final_checkpoint.model
ADDED
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version https://git-lfs.github.com/spec/v1
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size 420725142
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Task500_Glacier_zonefronts/fold_0/model_final_checkpoint.model.pkl
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:fb28c31d128912ea6771548e1699913c5090ce00046dfef6769aa3499f792b23
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size 174903
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Task500_Glacier_zonefronts/fold_0/plans.pkl
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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Task500_Glacier_zonefronts/fold_0/progress.png
ADDED
![]() |
Task500_Glacier_zonefronts/fold_0/training_log_2022_4_6_13_42_45.txt
ADDED
@@ -0,0 +1,353 @@
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1 |
+
Starting...
|
2 |
+
2022-04-06 13:42:45.151882: Creating new 5-fold cross-validation split...
|
3 |
+
2022-04-06 13:42:45.161848: Desired fold for training: 0
|
4 |
+
2022-04-06 13:42:45.162639: This split has 447 training and 112 validation cases.
|
5 |
+
2022-04-06 13:46:30.086602: TRAINING KEYS:
|
6 |
+
odict_keys(['Crane_2002-11-09_ERS_20_2_061', 'Crane_2002-11-18_ERS_20_3_195', 'Crane_2003-01-18_ERS_20_1_061', 'Crane_2006-11-27_ERS_20_1_195', 'Crane_2007-02-05_ERS_20_1_195', 'Crane_2007-03-31_ENVISAT_20_3_467', 'Crane_2007-05-05_ENVISAT_20_1_467', 'Crane_2007-06-09_ENVISAT_20_1_467', 'Crane_2007-07-14_ENVISAT_20_1_467', 'Crane_2007-11-21_PALSAR_17_2_135', 'Crane_2008-01-05_ENVISAT_20_2_467', 'Crane_2008-10-13_TSX_7_3_034', 'Crane_2008-10-24_TSX_7_2_034', 'Crane_2008-11-04_TSX_7_1_034', 'Crane_2008-11-23_PALSAR_17_2_135', 'Crane_2009-09-29_PALSAR_17_1_137', 'Crane_2009-11-02_TSX_7_3_034', 'Crane_2009-11-13_TSX_7_1_034', 'Crane_2010-05-29_ENVISAT_20_3_467', 'Crane_2010-07-03_ENVISAT_20_2_467', 'Crane_2010-09-15_PALSAR_17_4_138', 'Crane_2010-10-14_PALSAR_17_2_135', 'Crane_2010-11-05_TSX_7_2_110', 'Crane_2010-11-16_TSX_7_2_110', 'Crane_2010-12-08_TSX_7_1_110', 'Crane_2010-12-14_TSX_7_1_034', 'Crane_2010-12-19_TSX_7_1_110', 'Crane_2010-12-25_TSX_7_1_034', 'Crane_2011-06-02_TSX_7_2_110', 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'Jorum_2020-01-08_S1_20_3_009', 'Jorum_2020-03-08_S1_20_3_009', 'SI_1995-11-13_ERS_20_3_109', 'SI_1995-11-14_ERS_20_4_118', 'SI_1995-11-15_ERS_20_3_118', 'SI_1995-11-16_ERS_20_4_152', 'SI_1996-01-23_ERS_20_5_109', 'SI_1996-01-24_ERS_20_4_118', 'SI_1996-02-12_ERS_20_2_390', 'SI_1996-02-29_ERS_20_2_152', 'SI_1996-03-18_ERS_20_2_390', 'SI_1997-01-27_ERS_20_4_390', 'SI_2000-09-10_RSAT_20_5_282', 'SI_2000-09-19_RSAT_20_5_063', 'SI_2000-10-04_RSAT_20_5_282', 'SI_2000-10-13_RSAT_20_5_063', 'SI_2002-01-21_ERS_20_2_390', 'SI_2002-02-25_ERS_20_3_390', 'SI_2002-11-12_ERS_20_4_109', 'SI_2002-12-21_ERS_20_3_161', 'SI_2003-12-05_ENVISAT_20_4_152', 'SI_2004-07-02_ENVISAT_20_4_152', 'SI_2004-08-06_ENVISAT_20_4_152', 'SI_2004-09-13_RSAT_12_5_282', 'SI_2004-10-15_ERS_20_5_152', 'SI_2004-11-09_RSAT_12_5_063', 'SI_2004-11-19_ERS_20_4_152', 'SI_2004-11-24_RSAT_12_4_282', 'SI_2004-12-18_RSAT_12_4_282', 'SI_2004-12-24_ENVISAT_20_5_152', 'SI_2004-12-24_ERS_20_5_152', 'SI_2005-01-28_ERS_20_5_152', 'SI_2005-02-28_RSAT_12_5_282', 'SI_2005-03-04_ENVISAT_20_3_152', 'SI_2005-04-08_ENVISAT_20_2_152', 'SI_2005-04-17_RSAT_12_3_282', 'SI_2005-05-11_RSAT_12_2_282', 'SI_2005-07-22_ENVISAT_20_2_152', 'SI_2005-08-26_ENVISAT_20_2_152', 'SI_2006-01-06_RSAT_12_2_282', 'SI_2006-02-23_RSAT_12_1_282', 'SI_2006-03-05_ENVISAT_20_2_381', 'SI_2006-03-19_RSAT_12_2_282', 'SI_2006-04-12_RSAT_12_1_282', 'SI_2006-05-06_RSAT_12_3_282', 'SI_2006-07-03_PALSAR_17_3_135', 'SI_2006-07-23_ENVISAT_20_4_381', 'SI_2006-08-10_RSAT_20_3_282', 'SI_2006-09-03_RSAT_12_2_282', 'SI_2006-09-03_RSAT_20_2_282', 'SI_2006-10-18_ERS_20_4_118', 'SI_2006-11-21_ERS_20_3_109', 'SI_2007-01-01_RSAT_12_3_282', 'SI_2007-01-14_ENVISAT_20_3_381', 'SI_2007-03-14_RSAT_12_2_282', 'SI_2007-03-25_ENVISAT_20_3_381', 'SI_2007-05-01_RSAT_12_2_282', 'SI_2007-06-03_ENVISAT_20_3_381', 'SI_2007-07-08_ENVISAT_20_3_381', 'SI_2007-09-16_ENVISAT_20_3_381', 'SI_2007-10-21_ENVISAT_20_3_381', 'SI_2007-12-03_RSAT_12_4_282', 'SI_2007-12-27_RSAT_12_2_282', 'SI_2008-01-20_RSAT_12_2_282', 'SI_2008-04-13_ENVISAT_20_2_381', 'SI_2008-05-18_ENVISAT_20_3_381', 'SI_2008-07-27_ENVISAT_20_4_381', 'SI_2008-08-31_ENVISAT_20_4_381', 'SI_2009-02-22_ENVISAT_20_2_381', 'SI_2009-03-29_ENVISAT_20_4_381', 'SI_2009-07-12_ENVISAT_20_3_381', 'SI_2009-08-16_ENVISAT_20_3_381', 'SI_2010-01-13_PALSAR_17_2_127', 'SI_2010-01-22_ERS_20_3_152', 'SI_2010-02-26_ERS_20_2_152', 'SI_2010-04-02_ERS_20_2_152', 'SI_2010-10-16_PALSAR_17_3_127', 'SI_2010-12-01_PALSAR_17_3_127', 'SI_2011-01-16_PALSAR_17_2_127', 'SI_2011-03-03_PALSAR_17_2_127', 'SI_2011-06-14_TSX_7_1_125', 'SI_2011-07-06_TSX_7_1_125', 'SI_2011-08-19_TSX_7_1_125', 'SI_2011-09-10_TSX_7_1_125', 'SI_2011-09-21_TSX_7_1_125', 'SI_2011-12-29_TSX_7_1_125', 'SI_2012-01-09_TSX_7_1_125', 'SI_2012-03-04_TSX_7_1_125', 'SI_2012-03-15_TSX_7_1_125', 'SI_2012-03-26_TSX_7_1_125', 'SI_2012-05-20_TSX_7_1_125', 'SI_2012-06-22_TSX_7_1_125', 'SI_2012-08-05_TSX_7_1_125', 'SI_2012-08-16_TSX_7_1_125', 'SI_2013-07-12_TSX_7_1_125', 'SI_2013-08-14_TSX_7_1_125', 'SI_2013-09-16_TSX_7_1_125', 'SI_2013-10-19_TSX_7_1_125', 'SI_2013-10-28_TSX_7_1_104', 'SI_2013-11-21_TSX_7_1_125', 'SI_2014-01-04_TSX_7_2_125', 'SI_2014-04-02_TSX_7_1_125', 'SI_2014-12-11_TSX_7_4_125'])
|
7 |
+
2022-04-06 13:46:30.089200: VALIDATION KEYS:
|
8 |
+
odict_keys(['Crane_2007-09-22_ENVISAT_20_1_467', 'Crane_2007-09-24_PALSAR_17_1_137', 'Crane_2007-10-27_ENVISAT_20_2_467', 'Crane_2010-11-27_TSX_7_1_110', 'Crane_2010-11-29_PALSAR_17_1_135', 'Crane_2010-12-30_TSX_7_1_110', 'Crane_2011-06-24_TSX_7_1_110', 'Crane_2012-07-25_TSX_7_2_125', 'Crane_2012-08-10_TSX_7_3_034', 'Crane_2012-11-06_TSX_7_2_034', 'Crane_2013-03-07_TSX_7_2_034', 'Crane_2013-03-29_TSX_7_2_034', 'Crane_2013-06-30_TSX_7_2_110', 'Crane_2014-02-11_TSX_7_3_034', 'DBE_1996-01-25_ERS_20_1_152', 'DBE_2000-09-10_RSAT_20_3_282', 'DBE_2004-04-07_ENVISAT_20_3_424', 'DBE_2004-06-16_ENVISAT_20_3_424', 'DBE_2004-07-21_ENVISAT_20_3_424', 'DBE_2004-11-09_RSAT_12_3_063', 'DBE_2004-12-08_ENVISAT_20_5_424', 'DBE_2004-12-08_ERS_20_5_424', 'DBE_2005-04-27_ENVISAT_20_2_424', 'DBE_2005-08-10_ENVISAT_20_2_424', 'DBE_2006-04-12_ENVISAT_20_1_424', 'DBE_2006-06-21_ENVISAT_20_2_424', 'DBE_2006-06-21_PALSAR_17_2_137', 'DBE_2007-08-15_ENVISAT_20_5_424', 'DBE_2007-09-19_ENVISAT_20_6_424', 'DBE_2008-10-14_TSX_7_3_049', 'DBE_2008-12-29_PALSAR_17_5_129', 'DBE_2009-10-23_TSX_7_2_049', 'DBE_2010-01-22_ERS_20_6_152', 'DBE_2010-04-21_ENVISAT_20_6_424', 'DBE_2010-10-16_PALSAR_17_4_127', 'DBE_2010-11-12_TSX_7_4_049', 'DBE_2010-12-06_PALSAR_17_3_132', 'DBE_2012-03-14_TSX_7_1_110', 'DBE_2012-06-10_TSX_7_1_110', 'DBE_2012-08-15_TSX_7_1_110', 'DBE_2013-01-16_TSX_7_5_110', 'DBE_2013-05-28_TSX_7_1_110', 'DBE_2013-06-19_TSX_7_1_110', 'DBE_2013-11-09_TSX_7_1_110', 'DBE_2013-12-12_TSX_7_3_110', 'JAC_2009-04-27_TSX_6_1_005', 'JAC_2009-06-10_TSX_6_1_005', 'JAC_2009-10-31_TSX_6_1_005', 'JAC_2009-12-03_TSX_6_1_005', 'JAC_2010-09-15_TSX_6_1_005', 'JAC_2010-12-01_TSX_6_1_005', 'JAC_2010-12-23_TSX_6_1_005', 'JAC_2011-05-15_TSX_6_1_005', 'JAC_2011-06-17_TSX_6_1_005', 'JAC_2012-03-07_TSX_6_1_005', 'JAC_2012-04-20_TSX_6_1_005', 'JAC_2012-05-24_TSX_6_1_027', 'JAC_2012-08-20_TSX_6_1_027', 'JAC_2012-09-11_TSX_6_1_027', 'JAC_2013-04-07_TSX_6_1_005', 'JAC_2013-05-22_TSX_6_1_027', 'JAC_2013-06-13_TSX_6_1_027', 'JAC_2013-09-08_TSX_6_1_005', 'JAC_2013-12-17_TSX_6_1_027', 'JAC_2014-01-29_TSX_6_1_005', 'JAC_2014-04-16_TSX_6_1_005', 'JAC_2014-07-03_TSX_6_1_027', 'JAC_2014-07-25_TSX_6_1_027', 'JAC_2014-12-25_TSX_6_1_005', 'JAC_2015-01-05_TSX_6_1_005', 'JAC_2015-05-06_TSX_6_1_005', 'JAC_2015-06-08_TSX_6_1_005', 'JAC_2015-07-11_TSX_6_1_005', 'JAC_2015-11-20_TSX_6_1_005', 'JAC_2015-12-12_TSX_6_1_005', 'Jorum_2003-01-27_ERS_20_1_195', 'Jorum_2007-05-05_ENVISAT_20_2_467', 'Jorum_2007-06-09_ENVISAT_20_2_467', 'Jorum_2008-11-23_PALSAR_17_2_135', 'Jorum_2010-12-08_TSX_7_2_110', 'Jorum_2010-12-19_TSX_7_1_110', 'Jorum_2010-12-25_TSX_7_1_034', 'Jorum_2012-05-14_TSX_7_2_034', 'Jorum_2012-06-16_TSX_7_2_034', 'Jorum_2012-07-30_TSX_7_2_034', 'Jorum_2013-02-24_TSX_7_3_034', 'Jorum_2013-07-22_TSX_7_1_110', 'Jorum_2013-08-02_TSX_7_2_110', 'Jorum_2013-11-26_TSX_7_5_034', 'Jorum_2014-02-11_TSX_7_2_034', 'Jorum_2017-06-16_S1_20_2_009', 'Jorum_2020-06-12_S1_20_3_009', 'SI_1996-01-22_ERS_20_3_109', 'SI_1997-03-03_ERS_20_4_390', 'SI_1999-11-07_ERS_20_2_381', 'SI_2000-02-20_ERS_20_3_381', 'SI_2003-01-25_ERS_20_3_161', 'SI_2004-02-13_ENVISAT_20_4_152', 'SI_2004-12-03_RSAT_12_5_063', 'SI_2006-01-29_ENVISAT_20_3_381', 'SI_2006-05-18_PALSAR_17_2_135', 'SI_2006-08-27_ENVISAT_20_3_381', 'SI_2007-01-25_RSAT_12_1_282', 'SI_2011-07-28_TSX_7_1_125', 'SI_2011-11-26_TSX_7_2_125', 'SI_2012-04-28_TSX_7_1_125', 'SI_2012-07-03_TSX_7_1_125', 'SI_2013-11-08_TSX_7_2_104', 'SI_2013-12-02_TSX_7_1_125', 'SI_2013-12-13_TSX_7_2_125', 'SI_2014-03-22_TSX_7_1_125', 'SI_2014-12-22_TSX_7_2_125'])
|
9 |
+
2022-04-06 13:48:05.212889: lr: 0.01
|
10 |
+
2022-04-06 13:48:13.483644: Unable to plot network architecture:
|
11 |
+
2022-04-06 13:48:13.507257: No module named 'hiddenlayer'
|
12 |
+
2022-04-06 13:48:13.519965:
|
13 |
+
printing the network instead:
|
14 |
+
|
15 |
+
2022-04-06 13:48:13.530723: Generic_UNet(
|
16 |
+
(conv_blocks_localization): ModuleList(
|
17 |
+
(0): Sequential(
|
18 |
+
(0): StackedConvLayers(
|
19 |
+
(blocks): Sequential(
|
20 |
+
(0): ConvDropoutNormNonlin(
|
21 |
+
(conv): Conv2d(960, 480, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
22 |
+
(instnorm): InstanceNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
23 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
24 |
+
)
|
25 |
+
)
|
26 |
+
)
|
27 |
+
(1): StackedConvLayers(
|
28 |
+
(blocks): Sequential(
|
29 |
+
(0): ConvDropoutNormNonlin(
|
30 |
+
(conv): Conv2d(480, 480, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
31 |
+
(instnorm): InstanceNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
32 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
33 |
+
)
|
34 |
+
)
|
35 |
+
)
|
36 |
+
)
|
37 |
+
(1): Sequential(
|
38 |
+
(0): StackedConvLayers(
|
39 |
+
(blocks): Sequential(
|
40 |
+
(0): ConvDropoutNormNonlin(
|
41 |
+
(conv): Conv2d(960, 480, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
42 |
+
(instnorm): InstanceNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
43 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
44 |
+
)
|
45 |
+
)
|
46 |
+
)
|
47 |
+
(1): StackedConvLayers(
|
48 |
+
(blocks): Sequential(
|
49 |
+
(0): ConvDropoutNormNonlin(
|
50 |
+
(conv): Conv2d(480, 480, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
51 |
+
(instnorm): InstanceNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
52 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
53 |
+
)
|
54 |
+
)
|
55 |
+
)
|
56 |
+
)
|
57 |
+
(2): Sequential(
|
58 |
+
(0): StackedConvLayers(
|
59 |
+
(blocks): Sequential(
|
60 |
+
(0): ConvDropoutNormNonlin(
|
61 |
+
(conv): Conv2d(960, 480, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
62 |
+
(instnorm): InstanceNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
63 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
64 |
+
)
|
65 |
+
)
|
66 |
+
)
|
67 |
+
(1): StackedConvLayers(
|
68 |
+
(blocks): Sequential(
|
69 |
+
(0): ConvDropoutNormNonlin(
|
70 |
+
(conv): Conv2d(480, 480, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
71 |
+
(instnorm): InstanceNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
72 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
73 |
+
)
|
74 |
+
)
|
75 |
+
)
|
76 |
+
)
|
77 |
+
(3): Sequential(
|
78 |
+
(0): StackedConvLayers(
|
79 |
+
(blocks): Sequential(
|
80 |
+
(0): ConvDropoutNormNonlin(
|
81 |
+
(conv): Conv2d(960, 480, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
82 |
+
(instnorm): InstanceNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
83 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
84 |
+
)
|
85 |
+
)
|
86 |
+
)
|
87 |
+
(1): StackedConvLayers(
|
88 |
+
(blocks): Sequential(
|
89 |
+
(0): ConvDropoutNormNonlin(
|
90 |
+
(conv): Conv2d(480, 480, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
91 |
+
(instnorm): InstanceNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
92 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
93 |
+
)
|
94 |
+
)
|
95 |
+
)
|
96 |
+
)
|
97 |
+
(4): Sequential(
|
98 |
+
(0): StackedConvLayers(
|
99 |
+
(blocks): Sequential(
|
100 |
+
(0): ConvDropoutNormNonlin(
|
101 |
+
(conv): Conv2d(512, 256, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
102 |
+
(instnorm): InstanceNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
103 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
104 |
+
)
|
105 |
+
)
|
106 |
+
)
|
107 |
+
(1): StackedConvLayers(
|
108 |
+
(blocks): Sequential(
|
109 |
+
(0): ConvDropoutNormNonlin(
|
110 |
+
(conv): Conv2d(256, 256, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
111 |
+
(instnorm): InstanceNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
112 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
113 |
+
)
|
114 |
+
)
|
115 |
+
)
|
116 |
+
)
|
117 |
+
(5): Sequential(
|
118 |
+
(0): StackedConvLayers(
|
119 |
+
(blocks): Sequential(
|
120 |
+
(0): ConvDropoutNormNonlin(
|
121 |
+
(conv): Conv2d(256, 128, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
122 |
+
(instnorm): InstanceNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
123 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
124 |
+
)
|
125 |
+
)
|
126 |
+
)
|
127 |
+
(1): StackedConvLayers(
|
128 |
+
(blocks): Sequential(
|
129 |
+
(0): ConvDropoutNormNonlin(
|
130 |
+
(conv): Conv2d(128, 128, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
131 |
+
(instnorm): InstanceNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
132 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
133 |
+
)
|
134 |
+
)
|
135 |
+
)
|
136 |
+
)
|
137 |
+
(6): Sequential(
|
138 |
+
(0): StackedConvLayers(
|
139 |
+
(blocks): Sequential(
|
140 |
+
(0): ConvDropoutNormNonlin(
|
141 |
+
(conv): Conv2d(128, 64, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
142 |
+
(instnorm): InstanceNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
143 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
144 |
+
)
|
145 |
+
)
|
146 |
+
)
|
147 |
+
(1): StackedConvLayers(
|
148 |
+
(blocks): Sequential(
|
149 |
+
(0): ConvDropoutNormNonlin(
|
150 |
+
(conv): Conv2d(64, 64, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
151 |
+
(instnorm): InstanceNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
152 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
153 |
+
)
|
154 |
+
)
|
155 |
+
)
|
156 |
+
)
|
157 |
+
(7): Sequential(
|
158 |
+
(0): StackedConvLayers(
|
159 |
+
(blocks): Sequential(
|
160 |
+
(0): ConvDropoutNormNonlin(
|
161 |
+
(conv): Conv2d(64, 32, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
162 |
+
(instnorm): InstanceNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
163 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
164 |
+
)
|
165 |
+
)
|
166 |
+
)
|
167 |
+
(1): StackedConvLayers(
|
168 |
+
(blocks): Sequential(
|
169 |
+
(0): ConvDropoutNormNonlin(
|
170 |
+
(conv): Conv2d(32, 32, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
171 |
+
(instnorm): InstanceNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
172 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
173 |
+
)
|
174 |
+
)
|
175 |
+
)
|
176 |
+
)
|
177 |
+
)
|
178 |
+
(conv_blocks_context): ModuleList(
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(0): StackedConvLayers(
|
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+
(blocks): Sequential(
|
181 |
+
(0): ConvDropoutNormNonlin(
|
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+
(conv): Conv2d(1, 32, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
183 |
+
(instnorm): InstanceNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
184 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
185 |
+
)
|
186 |
+
(1): ConvDropoutNormNonlin(
|
187 |
+
(conv): Conv2d(32, 32, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
188 |
+
(instnorm): InstanceNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
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+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
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+
)
|
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+
)
|
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+
)
|
193 |
+
(1): StackedConvLayers(
|
194 |
+
(blocks): Sequential(
|
195 |
+
(0): ConvDropoutNormNonlin(
|
196 |
+
(conv): Conv2d(32, 64, kernel_size=[3, 3], stride=[2, 2], padding=[1, 1])
|
197 |
+
(instnorm): InstanceNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
198 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
199 |
+
)
|
200 |
+
(1): ConvDropoutNormNonlin(
|
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+
(conv): Conv2d(64, 64, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
202 |
+
(instnorm): InstanceNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
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+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
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+
)
|
205 |
+
)
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206 |
+
)
|
207 |
+
(2): StackedConvLayers(
|
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+
(blocks): Sequential(
|
209 |
+
(0): ConvDropoutNormNonlin(
|
210 |
+
(conv): Conv2d(64, 128, kernel_size=[3, 3], stride=[2, 2], padding=[1, 1])
|
211 |
+
(instnorm): InstanceNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
212 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
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+
)
|
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+
(1): ConvDropoutNormNonlin(
|
215 |
+
(conv): Conv2d(128, 128, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
216 |
+
(instnorm): InstanceNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
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(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
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)
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)
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)
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(3): StackedConvLayers(
|
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(blocks): Sequential(
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(0): ConvDropoutNormNonlin(
|
224 |
+
(conv): Conv2d(128, 256, kernel_size=[3, 3], stride=[2, 2], padding=[1, 1])
|
225 |
+
(instnorm): InstanceNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
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+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
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227 |
+
)
|
228 |
+
(1): ConvDropoutNormNonlin(
|
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(conv): Conv2d(256, 256, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
230 |
+
(instnorm): InstanceNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
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+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
232 |
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)
|
233 |
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)
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)
|
235 |
+
(4): StackedConvLayers(
|
236 |
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(blocks): Sequential(
|
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+
(0): ConvDropoutNormNonlin(
|
238 |
+
(conv): Conv2d(256, 480, kernel_size=[3, 3], stride=[2, 2], padding=[1, 1])
|
239 |
+
(instnorm): InstanceNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
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+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
241 |
+
)
|
242 |
+
(1): ConvDropoutNormNonlin(
|
243 |
+
(conv): Conv2d(480, 480, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
244 |
+
(instnorm): InstanceNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
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+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
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+
)
|
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)
|
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)
|
249 |
+
(5): StackedConvLayers(
|
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+
(blocks): Sequential(
|
251 |
+
(0): ConvDropoutNormNonlin(
|
252 |
+
(conv): Conv2d(480, 480, kernel_size=[3, 3], stride=[2, 2], padding=[1, 1])
|
253 |
+
(instnorm): InstanceNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
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+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
255 |
+
)
|
256 |
+
(1): ConvDropoutNormNonlin(
|
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+
(conv): Conv2d(480, 480, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
258 |
+
(instnorm): InstanceNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
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+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
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)
|
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)
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)
|
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(6): StackedConvLayers(
|
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(blocks): Sequential(
|
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(0): ConvDropoutNormNonlin(
|
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+
(conv): Conv2d(480, 480, kernel_size=[3, 3], stride=[2, 2], padding=[1, 1])
|
267 |
+
(instnorm): InstanceNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
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(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
269 |
+
)
|
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+
(1): ConvDropoutNormNonlin(
|
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(conv): Conv2d(480, 480, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
272 |
+
(instnorm): InstanceNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
273 |
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(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
274 |
+
)
|
275 |
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)
|
276 |
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)
|
277 |
+
(7): StackedConvLayers(
|
278 |
+
(blocks): Sequential(
|
279 |
+
(0): ConvDropoutNormNonlin(
|
280 |
+
(conv): Conv2d(480, 480, kernel_size=[3, 3], stride=[2, 2], padding=[1, 1])
|
281 |
+
(instnorm): InstanceNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
282 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
283 |
+
)
|
284 |
+
(1): ConvDropoutNormNonlin(
|
285 |
+
(conv): Conv2d(480, 480, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
286 |
+
(instnorm): InstanceNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
287 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
288 |
+
)
|
289 |
+
)
|
290 |
+
)
|
291 |
+
(8): Sequential(
|
292 |
+
(0): StackedConvLayers(
|
293 |
+
(blocks): Sequential(
|
294 |
+
(0): ConvDropoutNormNonlin(
|
295 |
+
(conv): Conv2d(480, 480, kernel_size=[3, 3], stride=[2, 2], padding=[1, 1])
|
296 |
+
(instnorm): InstanceNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
297 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
298 |
+
)
|
299 |
+
)
|
300 |
+
)
|
301 |
+
(1): StackedConvLayers(
|
302 |
+
(blocks): Sequential(
|
303 |
+
(0): ConvDropoutNormNonlin(
|
304 |
+
(conv): Conv2d(480, 480, kernel_size=[3, 3], stride=(1, 1), padding=[1, 1])
|
305 |
+
(instnorm): InstanceNorm2d(480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)
|
306 |
+
(lrelu): LeakyReLU(negative_slope=0.01, inplace=True)
|
307 |
+
)
|
308 |
+
)
|
309 |
+
)
|
310 |
+
)
|
311 |
+
)
|
312 |
+
(td): ModuleList()
|
313 |
+
(tu): ModuleList(
|
314 |
+
(0): ConvTranspose2d(480, 480, kernel_size=[2, 2], stride=[2, 2], bias=False)
|
315 |
+
(1): ConvTranspose2d(480, 480, kernel_size=[2, 2], stride=[2, 2], bias=False)
|
316 |
+
(2): ConvTranspose2d(480, 480, kernel_size=[2, 2], stride=[2, 2], bias=False)
|
317 |
+
(3): ConvTranspose2d(480, 480, kernel_size=[2, 2], stride=[2, 2], bias=False)
|
318 |
+
(4): ConvTranspose2d(480, 256, kernel_size=[2, 2], stride=[2, 2], bias=False)
|
319 |
+
(5): ConvTranspose2d(256, 128, kernel_size=[2, 2], stride=[2, 2], bias=False)
|
320 |
+
(6): ConvTranspose2d(128, 64, kernel_size=[2, 2], stride=[2, 2], bias=False)
|
321 |
+
(7): ConvTranspose2d(64, 32, kernel_size=[2, 2], stride=[2, 2], bias=False)
|
322 |
+
)
|
323 |
+
(seg_outputs): ModuleList(
|
324 |
+
(0): Conv2d(480, 5, kernel_size=(1, 1), stride=(1, 1), bias=False)
|
325 |
+
(1): Conv2d(480, 5, kernel_size=(1, 1), stride=(1, 1), bias=False)
|
326 |
+
(2): Conv2d(480, 5, kernel_size=(1, 1), stride=(1, 1), bias=False)
|
327 |
+
(3): Conv2d(480, 5, kernel_size=(1, 1), stride=(1, 1), bias=False)
|
328 |
+
(4): Conv2d(256, 5, kernel_size=(1, 1), stride=(1, 1), bias=False)
|
329 |
+
(5): Conv2d(128, 5, kernel_size=(1, 1), stride=(1, 1), bias=False)
|
330 |
+
(6): Conv2d(64, 5, kernel_size=(1, 1), stride=(1, 1), bias=False)
|
331 |
+
(7): Conv2d(32, 5, kernel_size=(1, 1), stride=(1, 1), bias=False)
|
332 |
+
)
|
333 |
+
)
|
334 |
+
2022-04-06 13:48:13.561954:
|
335 |
+
|
336 |
+
2022-04-06 13:48:13.574286: svmem(total=99932160000, available=89355911168, percent=10.6, used=7974862848, free=74463080448, active=7446126592, inactive=15933480960, buffers=14180352, cached=17480036352, shared=786059264, slab=754434048)
|
337 |
+
2022-04-06 13:48:13.587833:
|
338 |
+
epoch: 0
|
339 |
+
2022-04-06 13:49:16.764398: train loss : 1.2657
|
340 |
+
2022-04-06 13:49:29.162044: validation loss: 1.0054
|
341 |
+
2022-04-06 13:49:29.184389: Average global foreground Dice: [0.0002, 0.6649, 0.0923, 0.0013]
|
342 |
+
2022-04-06 13:49:29.186826: (interpret this as an estimate for the Dice of the different classes. This is not exact.)
|
343 |
+
2022-04-06 13:49:30.284652: lr: 0.0
|
344 |
+
2022-04-06 13:49:30.286498: saving scheduled checkpoint file...
|
345 |
+
2022-04-06 13:49:30.449905: saving checkpoint...
|
346 |
+
2022-04-06 13:49:35.022912: done, saving took 4.73 seconds
|
347 |
+
2022-04-06 13:49:35.052222: done
|
348 |
+
2022-04-06 13:49:35.057490: This epoch took 81.447241 s
|
349 |
+
|
350 |
+
2022-04-06 13:49:35.205750: saving checkpoint...
|
351 |
+
2022-04-06 13:49:39.567125: done, saving took 4.51 seconds
|
352 |
+
2022-04-06 13:59:38.934049: finished prediction
|
353 |
+
2022-04-06 13:59:38.935330: evaluation of raw predictions
|
Task500_Glacier_zonefronts/fold_0/training_log_2022_4_6_14_16_01.txt
ADDED
The diff for this file is too large to render.
See raw diff
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|
Task500_Glacier_zonefronts/fold_1/debug.json
ADDED
@@ -0,0 +1,87 @@
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|
1 |
+
{
|
2 |
+
"all_tr_losses": "[]",
|
3 |
+
"all_val_eval_metrics": "[]",
|
4 |
+
"all_val_losses": "[]",
|
5 |
+
"all_val_losses_tr_mode": "[]",
|
6 |
+
"also_val_in_tr_mode": "False",
|
7 |
+
"amp_grad_scaler": "None",
|
8 |
+
"base_num_features": "32",
|
9 |
+
"basic_generator_patch_size": "[1505 1505]",
|
10 |
+
"batch_dice": "True",
|
11 |
+
"batch_size": "2",
|
12 |
+
"best_MA_tr_loss_for_patience": "None",
|
13 |
+
"best_epoch_based_on_MA_tr_loss": "None",
|
14 |
+
"best_val_eval_criterion_MA": "None",
|
15 |
+
"classes": "[[1, 2, 3, 4]]",
|
16 |
+
"conv_per_stage": "2",
|
17 |
+
"data_aug_params": "{'selected_data_channels': None, 'selected_seg_channels': [0], 'do_elastic': False, 'elastic_deform_alpha': (0.0, 200.0), 'elastic_deform_sigma': (9.0, 13.0), 'p_eldef': 0.2, 'do_scaling': True, 'scale_range': (0.7, 1.4), 'independent_scale_factor_for_each_axis': False, 'p_independent_scale_per_axis': 1, 'p_scale': 0.2, 'do_rotation': True, 'rotation_x': (-3.141592653589793, 3.141592653589793), 'rotation_y': (-0.0, 0.0), 'rotation_z': (-0.0, 0.0), 'rotation_p_per_axis': 1, 'p_rot': 0.2, 'random_crop': False, 'random_crop_dist_to_border': None, 'do_gamma': True, 'gamma_retain_stats': True, 'gamma_range': (0.7, 1.5), 'p_gamma': 0.3, 'do_mirror': True, 'mirror_axes': (0, 1), 'dummy_2D': False, 'mask_was_used_for_normalization': OrderedDict([(0, False)]), 'border_mode_data': 'constant', 'all_segmentation_labels': None, 'move_last_seg_chanel_to_data': False, 'cascade_do_cascade_augmentations': False, 'cascade_random_binary_transform_p': 0.4, 'cascade_random_binary_transform_p_per_label': 1, 'cascade_random_binary_transform_size': (1, 8), 'cascade_remove_conn_comp_p': 0.2, 'cascade_remove_conn_comp_max_size_percent_threshold': 0.15, 'cascade_remove_conn_comp_fill_with_other_class_p': 0.0, 'do_additive_brightness': False, 'additive_brightness_p_per_sample': 0.15, 'additive_brightness_p_per_channel': 0.5, 'additive_brightness_mu': 0.0, 'additive_brightness_sigma': 0.1, 'num_threads': 12, 'num_cached_per_thread': 2, 'patch_size_for_spatialtransform': array([1280, 1024])}",
|
18 |
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"dataset_directory": "/home/woody/iwi5/iwi5039h/nnUNet_data/nnUNet_preprocessed/Task500_Glacier_zonefronts",
|
19 |
+
"deep_supervision_scales": "[[1, 1, 1], [0.5, 0.5], [0.25, 0.25], [0.125, 0.125], [0.0625, 0.0625], [0.03125, 0.03125], [0.015625, 0.015625], [0.0078125, 0.0078125]]",
|
20 |
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"deterministic": "False",
|
21 |
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"dl_tr": "<nnunet.training.dataloading.dataset_loading.DataLoader2D object at 0x7f7ed281c520>",
|
22 |
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"dl_val": "<nnunet.training.dataloading.dataset_loading.DataLoader2D object at 0x7f7ed2401f10>",
|
23 |
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"do_dummy_2D_aug": "False",
|
24 |
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"ds_loss_weights": "[0.50393701 0.2519685 0.12598425 0.06299213 0.03149606 0.01574803\n 0.00787402 0. ]",
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25 |
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"epoch": "0",
|
26 |
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"experiment_name": "nnUNetTrainerV2",
|
27 |
+
"fold": "1",
|
28 |
+
"folder_with_preprocessed_data": "/home/woody/iwi5/iwi5039h/nnUNet_data/nnUNet_preprocessed/Task500_Glacier_zonefronts/nnUNetData_plans_v2.1_2D_stage0",
|
29 |
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"fp16": "True",
|
30 |
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"gt_niftis_folder": "/home/woody/iwi5/iwi5039h/nnUNet_data/nnUNet_preprocessed/Task500_Glacier_zonefronts/gt_segmentations",
|
31 |
+
"inference_pad_border_mode": "constant",
|
32 |
+
"inference_pad_kwargs": "{'constant_values': 0}",
|
33 |
+
"init_args": "('/home/woody/iwi5/iwi5039h/nnUNet_data/nnUNet_preprocessed/Task500_Glacier_zonefronts/nnUNetPlansv2.1_plans_2D.pkl', 1, '/home/woody/iwi5/iwi5039h/nnUNet_data/RESULTS_FOLDER/nnUNet/2d/Task500_Glacier_zonefronts/nnUNetTrainerV2__nnUNetPlansv2.1', '/home/woody/iwi5/iwi5039h/nnUNet_data/nnUNet_preprocessed/Task500_Glacier_zonefronts', True, 0, True, False, True)",
|
34 |
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"initial_lr": "0.01",
|
35 |
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"log_file": "/home/woody/iwi5/iwi5039h/nnUNet_data/RESULTS_FOLDER/nnUNet/2d/Task500_Glacier_zonefronts/nnUNetTrainerV2__nnUNetPlansv2.1/fold_1/training_log_2022_4_11_16_28_44.txt",
|
36 |
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"lr_scheduler": "None",
|
37 |
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"lr_scheduler_eps": "0.001",
|
38 |
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"lr_scheduler_patience": "30",
|
39 |
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"lr_threshold": "1e-06",
|
40 |
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"max_num_epochs": "500",
|
41 |
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"min_region_size_per_class": "None",
|
42 |
+
"min_size_per_class": "None",
|
43 |
+
"net_conv_kernel_sizes": "[[3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3]]",
|
44 |
+
"net_num_pool_op_kernel_sizes": "[[2, 2], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2]]",
|
45 |
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"net_pool_per_axis": "[8, 8]",
|
46 |
+
"normalization_schemes": "OrderedDict([(0, 'nonCT')])",
|
47 |
+
"num_batches_per_epoch": "250",
|
48 |
+
"num_classes": "[5]",
|
49 |
+
"num_input_channels": "1",
|
50 |
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"num_val_batches_per_epoch": "50",
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Task500_Glacier_zonefronts/fold_2/eval_results.json
ADDED
@@ -0,0 +1 @@
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Task500_Glacier_zonefronts/fold_4/eval_results.json
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