Commit 758c8a5d authored by Andrey Filippov's avatar Andrey Filippov

Trying next versions with partial second stage - 5x5+3x3+1x1

parent 17e64c60
...@@ -1030,7 +1030,7 @@ if __name__ == "__main__": ...@@ -1030,7 +1030,7 @@ if __name__ == "__main__":
ml_list_train=ex_data.getMLList(ml_subdir, ex_data.files_train) ml_list_train=ex_data.getMLList(ml_subdir, ex_data.files_train)
ml_list_test= ex_data.getMLList(ml_subdir, ex_data.files_test) ml_list_test= ex_data.getMLList(ml_subdir, ex_data.files_test)
num_test_scenes = [ex_data.files_test, ex_data.files_train][TEST_SAME_LENGTH_AS_TRAIN] num_test_scenes = len([ex_data.files_test, ex_data.files_train][TEST_SAME_LENGTH_AS_TRAIN])
if RADIUS == 0 : if RADIUS == 0 :
......
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...@@ -58,13 +58,13 @@ SHUFFLE_EPOCH = True ...@@ -58,13 +58,13 @@ SHUFFLE_EPOCH = True
NET_ARCH1 = 0 # 4 # #4 # 8 # 4 # 0 #3 # 0 # 0 # 0 # 0 # 8 # 0 # 7 # 2 #0 # 6 #0 # 4 # 3 # overwrite with argv? NET_ARCH1 = 0 # 4 # #4 # 8 # 4 # 0 #3 # 0 # 0 # 0 # 0 # 8 # 0 # 7 # 2 #0 # 6 #0 # 4 # 3 # overwrite with argv?
NET_ARCH2 = 0 # 4 # 0 # 0 # 4 # 0 # 0 # 3 # 0 # 3 # 0 # 3 # 0 # 2 #0 # 6 # 0 # 3 # overwrite with argv? NET_ARCH2 = 0 # 4 # 0 # 0 # 4 # 0 # 0 # 3 # 0 # 3 # 0 # 3 # 0 # 2 #0 # 6 # 0 # 3 # overwrite with argv?
SYM8_SUB = False # True #False # True # False # True # False # True # False # enforce inputs from 2d correlation have symmetrical ones (groups of 8) SYM8_SUB = False # True #False # True # False # True # False # True # False # enforce inputs from 2d correlation have symmetrical ones (groups of 8)
ONLY_TILE = None # 4 # None # 0 # 4# None # (remove all but center tile data), put None here for normal operation) ONLY_TILE = 12 # None # 4 # None # 0 # 4# None # (remove all but center tile data), put None here for normal operation)
ZIP_LHVAR = True # combine _lvar and _hvar as odd/even elements ZIP_LHVAR = True # combine _lvar and _hvar as odd/even elements
#DEBUG_PACK_TILES = True #DEBUG_PACK_TILES = True
# CLUSTER_RADIUS should match input data # CLUSTER_RADIUS should match input data
CLUSTER_RADIUS = 2 # 1 # 1 - 3x3, 2 - 5x5 tiles CLUSTER_RADIUS = 2 # 1 # 1 - 3x3, 2 - 5x5 tiles
SHUFFLE_FILES = True SHUFFLE_FILES = True
WLOSS_LAMBDA = 0.0 # 50.0 # 5.0 # 1.0 # fraction of the W_loss (input layers weight non-uniformity) added to G_loss WLOSS_LAMBDA = 2.0 #3.0 # 1.0 # 0.3 # 0.0 # 50.0 # 5.0 # 1.0 # fraction of the W_loss (input layers weight non-uniformity) added to G_loss
WBORDERS_ZERO = True # Border conditions for first layer weights: False - free, True - tied to 0 WBORDERS_ZERO = True # Border conditions for first layer weights: False - free, True - tied to 0
MAX_FILES_PER_GROUP = 6 # just to try, normally should be 8 MAX_FILES_PER_GROUP = 6 # just to try, normally should be 8
FILE_UPDATE_EPOCHS = 2 # update train files each this many epochs. 0 - do not update FILE_UPDATE_EPOCHS = 2 # update train files each this many epochs. 0 - do not update
...@@ -439,7 +439,8 @@ dir_train_hvar = data_dir # "/home/eyesis/x3d_data/data_sets/tf_data_5x5_main" ...@@ -439,7 +439,8 @@ dir_train_hvar = data_dir # "/home/eyesis/x3d_data/data_sets/tf_data_5x5_main"
dir_train_lvar1 = data_dir1 #"/home/eyesis/x3d_data/data_sets/tf_data_5x5_main_1" # data_dir # "/home/eyesis/x3d_data/data_sets/tf_data_5x5_main" dir_train_lvar1 = data_dir1 #"/home/eyesis/x3d_data/data_sets/tf_data_5x5_main_1" # data_dir # "/home/eyesis/x3d_data/data_sets/tf_data_5x5_main"
dir_train_hvar1 = data_dir1 # "/home/eyesis/x3d_data/data_sets/tf_data_5x5_main" dir_train_hvar1 = data_dir1 # "/home/eyesis/x3d_data/data_sets/tf_data_5x5_main"
dir_test_lvar = data_dir # data_dir #"/home/eyesis/x3d_data/data_sets/tf_data_5x5_center/" # data_dir # "/home/eyesis/x3d_data/data_sets/tf_data_5x5_main" dir_test_lvar = data_dir # data_dir #"/home/eyesis/x3d_data/data_sets/tf_data_5x5_center/" # data_dir # "/home/eyesis/x3d_data/data_sets/tf_data_5x5_main"
dir_test_hvar = "/home/eyesis/x3d_data/data_sets/tf_data_5x5_main_3" # data_dir #"/home/eyesis/x3d_data/data_sets/tf_data_5x5_center" # data_dir # "/home/eyesis/x3d_data/data_sets/tf_data_5x5_main" #dir_test_hvar = "/home/eyesis/x3d_data/data_sets/tf_data_5x5_main_3" # data_dir #"/home/eyesis/x3d_data/data_sets/tf_data_5x5_center" # data_dir # "/home/eyesis/x3d_data/data_sets/tf_data_5x5_main"
dir_test_hvar = "/home/eyesis/x3d_data/data_sets/tf_data_5x5_main_5" # data_dir #"/home/eyesis/x3d_data/data_sets/tf_data_5x5_center" # data_dir # "/home/eyesis/x3d_data/data_sets/tf_data_5x5_main"
dir_img = os.path.join(img_dir,"img") # "/home/eyesis/x3d_data/data_sets/tf_data_5x5_main/img" dir_img = os.path.join(img_dir,"img") # "/home/eyesis/x3d_data/data_sets/tf_data_5x5_main/img"
dir_result = os.path.join(data_dir,"result") # "/home/eyesis/x3d_data/data_sets/tf_data_5x5_main/result" dir_result = os.path.join(data_dir,"result") # "/home/eyesis/x3d_data/data_sets/tf_data_5x5_main/result"
...@@ -574,7 +575,7 @@ Compare with other (not used) train sets (use 7 of each instead of 8, 8-th as te ...@@ -574,7 +575,7 @@ Compare with other (not used) train sets (use 7 of each instead of 8, 8-th as te
#just testing: #just testing:
#files_train_lvar = files_train_hvar #files_train_lvar = files_train_hvar
files_test_lvar = ["train004_R2_GT_1.5.tfrecords"]# ["train007_R2_LE_1.5.tfrecords"]# "testTEST_R2_LE_1.5.tfrecords"] # testTEST_R2_LE_1.5.tfrecords"] files_test_lvar = ["train004_R2_GT_1.5.tfrecords"]# ["train007_R2_LE_1.5.tfrecords"]# "testTEST_R2_LE_1.5.tfrecords"] # testTEST_R2_LE_1.5.tfrecords"]
files_test_hvar = ["train000_R2_GT_1.5.tfrecords"]#"testTEST_R2_GT_1.5.tfrecords"] # "testTEST_R2_GT_1.5.tfrecords"] files_test_hvar = ["testTEST_R2_GT_1.5.tfrecords"] # Now same size as train! # ["train000_R2_GT_1.5.tfrecords"]#"testTEST_R2_GT_1.5.tfrecords"] # "testTEST_R2_GT_1.5.tfrecords"]
#files_img = ['1527257933_150165-v04'] # overlook #files_img = ['1527257933_150165-v04'] # overlook
#files_img = ['1527256858_150165-v01'] # State Street #files_img = ['1527256858_150165-v01'] # State Street
#files_img = ['1527256816_150165-v02'] # State Street #files_img = ['1527256816_150165-v02'] # State Street
...@@ -1066,8 +1067,8 @@ def weightsLoss(inp_weights): # [batch_size,(1..2)] tf_result ...@@ -1066,8 +1067,8 @@ def weightsLoss(inp_weights): # [batch_size,(1..2)] tf_result
# Adding 1 tile border # Adding 1 tile border
tf_inp = tf.reshape(inp_weights[:TILE_LAYERS * TILE_SIZE,:], [TILE_LAYERS, FILE_TILE_SIDE, FILE_TILE_SIDE, inp_weights.shape[1]], name = "tf_inp") tf_inp = tf.reshape(inp_weights[:TILE_LAYERS * TILE_SIZE,:], [TILE_LAYERS, FILE_TILE_SIDE, FILE_TILE_SIDE, inp_weights.shape[1]], name = "tf_inp")
if WBORDERS_ZERO: if WBORDERS_ZERO:
tf_zero_col = tf.constant(0.0, dtype=tf.float32, shape=[tf_inp.shape[0], tf_inp.shape[1], 1, tf_inp.shape[3]], name = "tf_zero_col") tf_zero_col = tf.constant(0.0, dtype=tf.float32, shape=[tf_inp.shape[0], tf_inp.shape[1], 1, tf_inp.shape[3]], name = "tf_zero_col")
tf_zero_row = tf.constant(0.0, dtype=tf.float32, shape=[tf_inp.shape[0], 1 , tf_inp.shape[2], tf_inp.shape[3]], name = "tf_zero_row") tf_zero_row = tf.constant(0.0, dtype=tf.float32, shape=[tf_inp.shape[0], 1 , tf_inp.shape[2] + 2, tf_inp.shape[3]], name = "tf_zero_row")
tf_inp_ext_h = tf.concat([tf_zero_col, tf_inp, tf_zero_col ], axis = 2, name ="tf_inp_ext_h") tf_inp_ext_h = tf.concat([tf_zero_col, tf_inp, tf_zero_col ], axis = 2, name ="tf_inp_ext_h")
tf_inp_ext = tf.concat([tf_zero_row, tf_inp_ext_h, tf_zero_row ], axis = 1, name ="tf_inp_ext") tf_inp_ext = tf.concat([tf_zero_row, tf_inp_ext_h, tf_zero_row ], axis = 1, name ="tf_inp_ext")
else: else:
......
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