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qcstereo_conf_sample.xml
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qcstereo_conf_sample.xml
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<?xml version="1.0" encoding="UTF-8"?>
<properties>
<parameters>
<EPOCHS_TO_RUN> 650 </EPOCHS_TO_RUN> <!-- 752# 3000#0 #0 -->
<NET_ARCH1> 13 </NET_ARCH1> <!--1-st stage network -->
<NET_ARCH2> 9 </NET_ARCH2> <!-- 2-nd stage network -->
<SYM8_SUB> False </SYM8_SUB> <!-- enforce inputs from 2d correlation have symmetrical ones (groups of 8) -->
<SPREAD_CONVERGENCE> False </SPREAD_CONVERGENCE><!-- Input target disparity to all nodes of the 1-st stage -->
<INTER_CONVERGENCE> False </INTER_CONVERGENCE><!-- Input target disparity to all nodes of the 2-nd stage -->
<LR> 3e-4 </LR> <!-- learning rate -->
<LR100> 1e-4 </LR100> <!-- LR # 1e-4 -->
<LR200> 3e-5 </LR200> <!-- LR100 # 3e-5 -->
<LR400> 1e-5 </LR400> <!-- LR200 # 1e-5 -->
<LR600> 3e-6 </LR600> <!-- LR400 # 3e-6 -->
<USE_CONFIDENCE> False </USE_CONFIDENCE>
<ABSOLUTE_DISPARITY> False </ABSOLUTE_DISPARITY> <!-- True # False # True # False -->
<DEBUG_PLT_LOSS> True </DEBUG_PLT_LOSS> <!-- -->
<TILE_LAYERS> 4 </TILE_LAYERS> <!-- -->
<TILE_SIDE> 9 </TILE_SIDE> <!-- 7 -->
<EPOCHS_FULL_TEST> 5 </EPOCHS_FULL_TEST> <!-- 10 # 25# repeat full image test after this number of epochs -->
<TWO_TRAINS> True </TWO_TRAINS> <!-- use 2 train sets -->
<ONLY_TILE> None </ONLY_TILE> <!-- (remove all but center tile data), put None here for normal operation) -->
<CLUSTER_RADIUS> 2 </CLUSTER_RADIUS> <!-- 1 # 1 - 3x3, 2 - 5x5 tiles -->
<SHUFFLE_FILES> True </SHUFFLE_FILES>
<WLOSS_LAMBDA> 0.5 </WLOSS_LAMBDA> <!-- fraction of the W_loss (input layers weight non-uniformity) added to G_loss -->
<SLOSS_LAMBDA> 0.1 </SLOSS_LAMBDA> <!-- weight of loss for smooth fg/bg transitions -->
<SLOSS_CLIP> 0.2 </SLOSS_CLIP> <!-- limit punishment for cutting corners (disparity pix) -->
<WBORDERS_ZERO> True </WBORDERS_ZERO> <!-- Border conditions for first layer weights: False - free, True - tied to 0 -->
<MAX_FILES_PER_GROUP> 4 </MAX_FILES_PER_GROUP> <!-- Reduces memory footprint - file shuffle buffer -->
<MAX_IMGS_IN_MEM> 1 </MAX_IMGS_IN_MEM> <!-- Number of simultaneously loaded images -->
<FILE_UPDATE_EPOCHS> 2 </FILE_UPDATE_EPOCHS> <!-- Update train files each this many epochs. 0 - do not update. Adjust to match speed of HDD/SDD with GPU)-->
<PARTIALS_WEIGHTS> [2.0,0.5,0.2] </PARTIALS_WEIGHTS><!-- weight of full 5x5, center 3x3 and center 1x1. len(PARTIALS_WEIGHTS) == CLUSTER_RADIUS + 1. Set to None -->
<HOR_FLIP> True </HOR_FLIP><!-- randomly flip training data horizontally -->
<SAVE_TIFFS> True </SAVE_TIFFS><!-- save Tiff files after each image evaluation -->
<BATCH_WEIGHTS> [0.9, 1.0, 0.1, 0.1]</BATCH_WEIGHTS> <!-- lvar, hvar, lvar1, hvar1 (increase importance of non-flat clusters -->
<DISP_DIFF_CAP> 0.3 </DISP_DIFF_CAP><!-- cap disparity difference (do not increase loss above)-->
<DISP_DIFF_SLOPE> 0.03 </DISP_DIFF_SLOPE><!-- allow squared error to grow above DISP_DIFF_CAP -->
<TRAIN_BUFFER_GPU> 79 </TRAIN_BUFFER_GPU> <!-- in batches merged (now quad) batches-->
<TRAIN_BUFFER_CPU> 4 </TRAIN_BUFFER_CPU> <!-- in TRAIN_BUFFER_GPU-s -->
<!-- if TEST_TITLES is present, it should have 8 entries, use None to skip certain modes -->
<TEST_TITLES>["Test flat heuristic",
"Test edge heuristic",
"Test flat random",
"Test edge random",
"Fake flat heuristic",
"Fake edge heuristic",
"Fake flat random",
"Fake edge random"]</TEST_TITLES>
<CHECKPOINT_PERIOD>100</CHECKPOINT_PERIOD>
<!-- <FIGS_ESXTENSIONS>["png","pdf","svg"]</FIGS_ESXTENSIONS> -->
<FIGS_EXTENSIONS>["pdf"]</FIGS_EXTENSIONS>
<!-- <FIGS_SAVESHOW>['save','show']</FIGS_SAVESHOW> -->
<FIGS_SAVESHOW>['save']</FIGS_SAVESHOW>
<EVAL_MODES>["train","infer"]</EVAL_MODES>
</parameters>
<dbg_parameters>
<disparity_ranges>
[[[0.0, 5.0,[0, 323,0,241]], "City Creek 1"],
[[0.0, 4.0,[180,240, 90,140]], "City Creek 2"],
[[1.0, 2.0,[180,240, 90,140]], "City Creek 3"],
[[1.0, 1.5,[280,320, 70,120]], "City Creek 4"],
[[0.0, 0.5,[ 10,120, 60,120]], "City Creek 5"],
[[0.0, 2.0,[210,303, 70,130]], "City Creek 6"],
[[0.0, 3.0,[ 75,225, 50,140]], "State Capitol"],
[[0.0, 3.0,[170,225, 95,140]], "Stop Sign"],
[[0.0, 1.0,[ 75,135,100,135]], "SLC from Capitol Hill 1"],
[[0.0, 1.5,[ 90,190,125,170]], "SLC from Capitol Hill 2"],
[[0.0, 0.6,[ 95,210, 65,140]], "Overlook approach"],
[[0.0,10.0,[ 60,190, 95,145]], "North Salt Lake 1"],
[[0.0, 5.0,[120,230, 85,145]], "North Salt Lake 2"], <!-- bad pole -->
[[0.0, 2.0,[ 10,155, 90,150]], "North Salt Lake 3"], <!-- LPF? misaligned? -->
[[0.0, 0.6,[140,230,135,60]], "Overlook"],
[[0.0, 1.0,[120,180,125,80]],[2.0, 4.0, [50,130,125, 70]], "State Street1"],
[[0.0, 1.0,[130,210,135,95]],[0.5, 2.5, [50,150,150, 75]], "State Street2"],
[ [1.0, 2.5, [90,170, 50, 0]], "B737 near"],
[ [0.75, 1.5, [125,150, 90, 70]], "B737 midrange"],
[ [0.4, 0.8, [135,150,102,112]], "B737 far"]
]
</disparity_ranges>
</dbg_parameters>
<directories>
<train_lvar>
"tf_data_5x5_main_13_heur"
</train_lvar>
<train_hvar>
"tf_data_5x5_main_13_heur"
</train_hvar>
<train_lvar1>
"tf_data_5x5_main_11_rnd"
</train_lvar1>
<train_hvar1>
"tf_data_5x5_main_11_rnd"
</train_hvar1>
<test_lvar>
"tf_data_5x5_main_10_heur" <!-- test file, no offset from hieuristic-->
</test_lvar>
<test_hvar>
"tf_data_5x5_main_10_heur" <!-- test file, no offset from hieuristic-->
</test_hvar>
<test_lvar1>
"tf_data_5x5_main_11_rnd" <!-- test file, random +/1 2pix offset-->
</test_lvar1>
<test_hvar1>
"tf_data_5x5_main_11_rnd" <!-- test file, random +/1 2pix offset-->
</test_hvar1>
<fake_lvar>
"tf_data_5x5_main_10_heur" <!-- test file, no offset from hieuristic-->
</fake_lvar>
<fake_hvar>
"tf_data_5x5_main_10_heur" <!-- test file, no offset from hieuristic-->
</fake_hvar>
<fake_lvar1>
"tf_data_5x5_main_11_rnd" <!-- test file, random +/1 2pix offset-->
</fake_lvar1>
<fake_hvar1>
"tf_data_5x5_main_11_rnd" <!-- test file, random +/1 2pix offset-->
</fake_hvar1>
<images>
"tf_data_5x5_main_13_heur/img"
</images>
<result>
"tf_data_5x5_main_13_heur/result"
</result>
<figures>
"tf_data_5x5_main_13_heur/result/figs"
</figures>
<checkpoints>
"tf_data_5x5_main_13_heur/checkpoints"
</checkpoints>
<inference>
"tf_data_5x5_main_13_heur/inference"
</inference>
<exportdir>
"tf_data_5x5_main_13_heur/trained_model"
</exportdir>
</directories>
<files>
<train_lvar>
["train000_R2_LE_0.4.tfrecords",
"train001_R2_LE_0.4.tfrecords",
"train002_R2_LE_0.4.tfrecords",
"train003_R2_LE_0.4.tfrecords",
"train004_R2_LE_0.4.tfrecords",
"train005_R2_LE_0.4.tfrecords",
"train006_R2_LE_0.4.tfrecords",
"train007_R2_LE_0.4.tfrecords",
"train008_R2_LE_0.4.tfrecords",
"train009_R2_LE_0.4.tfrecords",
"train010_R2_LE_0.4.tfrecords",
"train011_R2_LE_0.4.tfrecords",
"train012_R2_LE_0.4.tfrecords",
"train013_R2_LE_0.4.tfrecords",
"train014_R2_LE_0.4.tfrecords",
"train015_R2_LE_0.4.tfrecords",
<!--
"train016_R2_LE_0.4.tfrecords",
"train017_R2_LE_0.4.tfrecords",
"train018_R2_LE_0.4.tfrecords",
"train019_R2_LE_0.4.tfrecords",
"train020_R2_LE_0.4.tfrecords",
"train021_R2_LE_0.4.tfrecords",
"train022_R2_LE_0.4.tfrecords",
"train023_R2_LE_0.4.tfrecords",
"train024_R2_LE_0.4.tfrecords",
"train025_R2_LE_0.4.tfrecords",
"train026_R2_LE_0.4.tfrecords",
"train027_R2_LE_0.4.tfrecords",
"train028_R2_LE_0.4.tfrecords",
"train029_R2_LE_0.4.tfrecords",
"train030_R2_LE_0.4.tfrecords",
"train031_R2_LE_0.4.tfrecords" -->]
</train_lvar>
<train_hvar>
["train000_R2_GT_0.4.tfrecords",
"train001_R2_GT_0.4.tfrecords",
"train002_R2_GT_0.4.tfrecords",
"train003_R2_GT_0.4.tfrecords",
"train004_R2_GT_0.4.tfrecords",
"train005_R2_GT_0.4.tfrecords",
"train006_R2_GT_0.4.tfrecords",
"train007_R2_GT_0.4.tfrecords",
"train008_R2_GT_0.4.tfrecords",
"train009_R2_GT_0.4.tfrecords",
"train010_R2_GT_0.4.tfrecords",
"train011_R2_GT_0.4.tfrecords",
"train012_R2_GT_0.4.tfrecords",
"train013_R2_GT_0.4.tfrecords",
"train014_R2_GT_0.4.tfrecords",
"train015_R2_GT_0.4.tfrecords",
<!--
"train016_R2_GT_0.4.tfrecords",
"train017_R2_GT_0.4.tfrecords",
"train018_R2_GT_0.4.tfrecords",
"train019_R2_GT_0.4.tfrecords",
"train020_R2_GT_0.4.tfrecords",
"train021_R2_GT_0.4.tfrecords",
"train022_R2_GT_0.4.tfrecords",
"train023_R2_GT_0.4.tfrecords",
"train024_R2_GT_0.4.tfrecords",
"train025_R2_GT_0.4.tfrecords",
"train026_R2_GT_0.4.tfrecords",
"train027_R2_GT_0.4.tfrecords",
"train028_R2_GT_0.4.tfrecords",
"train029_R2_GT_0.4.tfrecords",
"train030_R2_GT_0.4.tfrecords",
"train031_R2_GT_0.4.tfrecords"-->]
</train_hvar>
<train_lvar1>
["train000_R2_LE_0.4.tfrecords",
"train001_R2_LE_0.4.tfrecords",
"train002_R2_LE_0.4.tfrecords",
"train003_R2_LE_0.4.tfrecords",
"train004_R2_LE_0.4.tfrecords",
"train005_R2_LE_0.4.tfrecords",
"train006_R2_LE_0.4.tfrecords",
"train007_R2_LE_0.4.tfrecords",
"train008_R2_LE_0.4.tfrecords",
"train009_R2_LE_0.4.tfrecords",
"train010_R2_LE_0.4.tfrecords",
"train011_R2_LE_0.4.tfrecords",
"train012_R2_LE_0.4.tfrecords",
"train013_R2_LE_0.4.tfrecords",
"train014_R2_LE_0.4.tfrecords",
"train015_R2_LE_0.4.tfrecords",
"train016_R2_LE_0.4.tfrecords",
"train017_R2_LE_0.4.tfrecords",
"train018_R2_LE_0.4.tfrecords",
"train019_R2_LE_0.4.tfrecords",
"train020_R2_LE_0.4.tfrecords",
"train021_R2_LE_0.4.tfrecords",
"train022_R2_LE_0.4.tfrecords",
"train023_R2_LE_0.4.tfrecords",
"train024_R2_LE_0.4.tfrecords",
"train025_R2_LE_0.4.tfrecords",
"train026_R2_LE_0.4.tfrecords",
"train027_R2_LE_0.4.tfrecords",
"train028_R2_LE_0.4.tfrecords",
"train029_R2_LE_0.4.tfrecords",
"train030_R2_LE_0.4.tfrecords",
"train031_R2_LE_0.4.tfrecords"]
</train_lvar1>
<train_hvar1>
["train000_R2_GT_0.4.tfrecords",
"train001_R2_GT_0.4.tfrecords",
"train002_R2_GT_0.4.tfrecords",
"train003_R2_GT_0.4.tfrecords",
"train004_R2_GT_0.4.tfrecords",
"train005_R2_GT_0.4.tfrecords",
"train006_R2_GT_0.4.tfrecords",
"train007_R2_GT_0.4.tfrecords",
"train008_R2_GT_0.4.tfrecords",
"train009_R2_GT_0.4.tfrecords",
"train010_R2_GT_0.4.tfrecords",
"train011_R2_GT_0.4.tfrecords",
"train012_R2_GT_0.4.tfrecords",
"train013_R2_GT_0.4.tfrecords",
"train014_R2_GT_0.4.tfrecords",
"train015_R2_GT_0.4.tfrecords",
"train016_R2_GT_0.4.tfrecords",
"train017_R2_GT_0.4.tfrecords",
"train018_R2_GT_0.4.tfrecords",
"train019_R2_GT_0.4.tfrecords",
"train020_R2_GT_0.4.tfrecords",
"train021_R2_GT_0.4.tfrecords",
"train022_R2_GT_0.4.tfrecords",
"train023_R2_GT_0.4.tfrecords",
"train024_R2_GT_0.4.tfrecords",
"train025_R2_GT_0.4.tfrecords",
"train026_R2_GT_0.4.tfrecords",
"train027_R2_GT_0.4.tfrecords",
"train028_R2_GT_0.4.tfrecords",
"train029_R2_GT_0.4.tfrecords",
"train030_R2_GT_0.4.tfrecords",
"train031_R2_GT_0.4.tfrecords"]
</train_hvar1>
<!-- Currently test* and fake* should have exactly one entry each.Should be defined for each non-None TEST_TITLES element-->
<test_lvar>
["testTEST_R2_LE_0.4.tfrecords"] <!-- test file, low variance, no offset-->
</test_lvar>
<test_hvar>
["testTEST_R2_GT_0.4.tfrecords"] <!-- test file, high variance, no offset-->
</test_hvar>
<test_lvar1>
["testTEST_R2_LE_0.4.tfrecords"] <!-- test file, low variance, +/-2 pix offset-->
</test_lvar1>
<test_hvar1>
["testTEST_R2_GT_0.4.tfrecords"] <!-- test file, high variance, +/-2 pix offset-->
</test_hvar1>
<fake_lvar>
["testFAKE_R2_LE_0.4.tfrecords"] <!-- fake test (made from train data) file, low variance, no offset-->
</fake_lvar>
<fake_hvar>
["testFAKE_R2_GT_0.4.tfrecords"] <!-- fake test (made from train data) file, high variance, no offset-->
</fake_hvar>
<fake_lvar1>
["testFAKE_R2_LE_0.4.tfrecords"] <!-- fake test (made from train data) file, low variance, +/-2 pix offset-->
</fake_lvar1>
<fake_hvar1>
["testFAKE_R2_GT_0.4.tfrecords"] <!-- fake test (made from train data) file, high variance, +/-2 pix offset-->
</fake_hvar1>
<images>
["1527257235_150165-v02", <!-- City Creek 1 -->
"1527257235_350165-v02", <!-- City Creek 2 -->
"1527257235_550165-v02", <!-- City Creek 3 -->
"1527257235_750165-v02", <!-- City Creek 4 -->
"1527257235_950165-v02", <!-- City Creek 5 -->
"1527257244_350165-v02", <!-- City Creek 6 -->
"1527257370_950165-v02", <!-- State Capitol -->
"1527257406_950165-v02", <!-- Stop Sign -->
"1527257757_950165-v02", <!-- SLC from Capitol Hill 1 -->
"1527257787_950165-v02", <!-- SLC from Capitol Hill 2 -->
"1527257894_750165-v02", <!-- Overlook approach -->
"1527258897_071435-v02", <!-- North Salt Lake 1 -->
"1527258936_671435-v02", <!-- North Salt Lake 2 -->
"1527259003_271435-v02", <!-- North Salt Lake 3 -->
"1527257933_150165-v04", <!-- overlook -->
"1527256858_150165-v01", <!-- State Street -->
"1527256816_150165-v02", <!-- State Street -->
"1527182802_096892-v02", <!-- plane near plane -->
"1527182805_096892-v02", <!-- plane midrange used up to -49 plane -->
"1527182810_096892-v02" <!-- plane far -->
]
</images>
<checkpoints>
"model_checkpoints"
</checkpoints>
<inference>
"model"
</inference>
<exportdir>
"model"
</exportdir>
</files>
</properties>