Commit 5b0156dc authored by Andrey Filippov's avatar Andrey Filippov
Browse files

fixed spaces in filenames

parent af52aef2

explore_data.py

+7 −6
Original line number Original line Diff line number Diff line
@@ -586,6 +586,7 @@ class ExploreData: 
        if not  '.tfrecords' in tfr_filename:

        if not  '.tfrecords' in tfr_filename:

            tfr_filename += '.tfrecords'

            tfr_filename += '.tfrecords'





        tfr_filename.replace(' ','_')

        if files_list is None:

        if files_list is None:

            files_list = self.files_train

            files_list = self.files_train
@@ -714,7 +715,7 @@ if __name__ == "__main__": 
  try:

  try:

      pathTFR =     sys.argv[3]

      pathTFR =     sys.argv[3]

  except IndexError:

  except IndexError:

      pathTFR = "/mnt/dde6f983-d149-435e-b4a2-88749245cc6c/home/eyesis/x3d_data/data_sets/tf_data/tf"

      pathTFR = "/mnt/dde6f983-d149-435e-b4a2-88749245cc6c/home/eyesis/x3d_data/data_sets/tf_data_3x3/"





  try:

  try:

      ml_subdir =   sys.argv[4]

      ml_subdir =   sys.argv[4]
@@ -824,7 +825,7 @@ if __name__ == "__main__": 
      pass

      pass

#  ex_data.makeBatchLists(data_ds = ex_data.train_ds)

#  ex_data.makeBatchLists(data_ds = ex_data.train_ds)

      for train_var in range (NUM_TRAIN_SETS):

      for train_var in range (NUM_TRAIN_SETS):

          fpath =  train_filenameTFR+("-%03d"%(train_var,))

          fpath =  train_filenameTFR+("%03d"%(train_var,))

          ex_data.writeTFRewcordsEpoch(fpath, ml_list = ml_list_train, files_list = ex_data.files_train, set_ds= ex_data.train_ds)

          ex_data.writeTFRewcordsEpoch(fpath, ml_list = ml_list_train, files_list = ex_data.files_train, set_ds= ex_data.train_ds)

          

          

      list_of_file_lists_test, num_batch_tiles_test = ex_data.makeBatchLists( # results are also saved to self.*

      list_of_file_lists_test, num_batch_tiles_test = ex_data.makeBatchLists( # results are also saved to self.*
@@ -849,7 +850,7 @@ if __name__ == "__main__": 
      num_le_train = num_batch_tiles_train.sum()

      num_le_train = num_batch_tiles_train.sum()

      print("Number of <= %f disparity variance tiles: %d (train)"%(VARIANCE_THRESHOLD, num_le_train))

      print("Number of <= %f disparity variance tiles: %d (train)"%(VARIANCE_THRESHOLD, num_le_train))

      for train_var in range (NUM_TRAIN_SETS):

      for train_var in range (NUM_TRAIN_SETS):

          fpath =  train_filenameTFR+("-%03d_R%d_LE%4.1f"%(train_var,RADIUS,VARIANCE_THRESHOLD))

          fpath =  train_filenameTFR+("%03d_R%d_LE%4.1f"%(train_var,RADIUS,VARIANCE_THRESHOLD))

          ex_data.writeTFRewcordsEpoch(fpath, ml_list = ml_list_train, files_list = ex_data.files_train, set_ds= ex_data.train_ds, radius = RADIUS)

          ex_data.writeTFRewcordsEpoch(fpath, ml_list = ml_list_train, files_list = ex_data.files_train, set_ds= ex_data.train_ds, radius = RADIUS)





      list_of_file_lists_train, num_batch_tiles_train = ex_data.makeBatchLists( # results are also saved to self.*

      list_of_file_lists_train, num_batch_tiles_train = ex_data.makeBatchLists( # results are also saved to self.*
@@ -863,7 +864,7 @@ if __name__ == "__main__": 
      high_fract_train = 1.0 * num_gt_train / (num_le_train + num_gt_train)

      high_fract_train = 1.0 * num_gt_train / (num_le_train + num_gt_train)

      print("Number of > %f disparity variance tiles: %d, fraction = %f (train)"%(VARIANCE_THRESHOLD, num_gt_train, high_fract_train))

      print("Number of > %f disparity variance tiles: %d, fraction = %f (train)"%(VARIANCE_THRESHOLD, num_gt_train, high_fract_train))

      for train_var in range (NUM_TRAIN_SETS):

      for train_var in range (NUM_TRAIN_SETS):

          fpath =  train_filenameTFR+("-%03d_R%d_GT%4.1f"%(train_var,RADIUS,VARIANCE_THRESHOLD))

          fpath =  (train_filenameTFR+("%03d_R%d_GT%4.1f"%(train_var,RADIUS,VARIANCE_THRESHOLD)))

          ex_data.writeTFRewcordsEpoch(fpath, ml_list = ml_list_train, files_list = ex_data.files_train, set_ds= ex_data.train_ds, radius = RADIUS)

          ex_data.writeTFRewcordsEpoch(fpath, ml_list = ml_list_train, files_list = ex_data.files_train, set_ds= ex_data.train_ds, radius = RADIUS)

          

          

      # test

      # test
@@ -877,7 +878,7 @@ if __name__ == "__main__": 
      num_le_test = num_batch_tiles_test.sum()

      num_le_test = num_batch_tiles_test.sum()

      print("Number of <= %f disparity variance tiles: %d (est)"%(VARIANCE_THRESHOLD, num_le_test))

      print("Number of <= %f disparity variance tiles: %d (est)"%(VARIANCE_THRESHOLD, num_le_test))





      fpath =  test_filenameTFR +("-TEST_R%d_LE%4.1f"%(RADIUS,VARIANCE_THRESHOLD))

      fpath =  test_filenameTFR +("TEST_R%d_LE%4.1f"%(RADIUS,VARIANCE_THRESHOLD))

      ex_data.writeTFRewcordsEpoch(fpath, ml_list = ml_list_test, files_list = ex_data.files_test, set_ds= ex_data.test_ds, radius = RADIUS)

      ex_data.writeTFRewcordsEpoch(fpath, ml_list = ml_list_test, files_list = ex_data.files_test, set_ds= ex_data.test_ds, radius = RADIUS)





      list_of_file_lists_test, num_batch_tiles_test = ex_data.makeBatchLists( # results are also saved to self.*

      list_of_file_lists_test, num_batch_tiles_test = ex_data.makeBatchLists( # results are also saved to self.*
@@ -890,7 +891,7 @@ if __name__ == "__main__": 
      num_gt_test = num_batch_tiles_test.sum()

      num_gt_test = num_batch_tiles_test.sum()

      high_fract_test = 1.0 * num_gt_test / (num_le_test + num_gt_test)

      high_fract_test = 1.0 * num_gt_test / (num_le_test + num_gt_test)

      print("Number of > %f disparity variance tiles: %d, fraction = %f (test)"%(VARIANCE_THRESHOLD, num_gt_test, high_fract_test))

      print("Number of > %f disparity variance tiles: %d, fraction = %f (test)"%(VARIANCE_THRESHOLD, num_gt_test, high_fract_test))

      fpath =  test_filenameTFR +("-TEST_R%d_GT%4.1f"%(RADIUS,VARIANCE_THRESHOLD))

      fpath =  test_filenameTFR +("TEST_R%d_GT%4.1f"%(RADIUS,VARIANCE_THRESHOLD))

      ex_data.writeTFRewcordsEpoch(fpath, ml_list = ml_list_test, files_list = ex_data.files_test, set_ds= ex_data.test_ds, radius = RADIUS)

      ex_data.writeTFRewcordsEpoch(fpath, ml_list = ml_list_test, files_list = ex_data.files_test, set_ds= ex_data.test_ds, radius = RADIUS)

  plt.show()

  plt.show()