compatible csv_data_file reader

config/GAN_demo_train_config.ini

@@ -1,6 +1,6 @@
 ############################ input configuration sections
 [usimage]
-csv_path_file=
+csv_file=
 path_to_search = ./example_volumes/gan_test_data
 filename_contains = frame,img
 filename_not_contains =

config/default_multimodal_segmentation.ini

@@ -1,38 +1,38 @@
 ############################ input configuration sections
 [T1]
-csv_path_file=
+csv_file=
 path_to_search = ./example_volumes/multimodal_BRATS
 filename_contains = T1
 filename_not_contains = T1c
 spatial_window_size = (64, 64, 64)
 interp_order = 3
 
 [T2]
-csv_path_file=
+csv_file=
 path_to_search = ./example_volumes/multimodal_BRATS
 filename_contains = T2
 filename_not_contains =
 spatial_window_size = (64, 64, 64)
 interp_order = 3
 
 [T1c]
-csv_path_file=
+csv_file=
 path_to_search = ./example_volumes/multimodal_BRATS
 filename_contains = T1c
 filename_not_contains =
 spatial_window_size = (64, 64, 64)
 interp_order = 3
 
 [Flair]
-csv_path_file=
+csv_file=
 path_to_search = ./example_volumes/multimodal_BRATS
 filename_contains = Flair
 filename_not_contains =
 spatial_window_size = (64, 64, 64)
 interp_order = 3
 
 [label]
-csv_path_file=
+csv_file=
 path_to_search = ./example_volumes/multimodal_BRATS
 filename_contains = Label
 filename_not_contains =

config/default_multimodal_segmentation_eval.ini

@@ -1,6 +1,6 @@
 ############################ input configuration sections
 [seg]
-csv_path_file=
+csv_file=
 path_to_search = ./NiftyNetTestEval
 filename_contains = Correct_WS3WT3WC1MergedSPCP_,_corr_corrIT
 filename_not_contains =
@@ -9,7 +9,7 @@ interp_order = 0
 
 
 [label]
-csv_path_file=
+csv_file=
 path_to_search = ./NiftyNetTestEval
 filename_contains = CHJP_,_vote
 filename_not_contains =

config/default_segmentation.ini

@@ -1,6 +1,6 @@
 ############################ input configuration sections
 [modality1]
-csv_path_file=
+csv_file=
 path_to_search = ./example_volumes/monomodal_parcellation
 filename_contains = T1
 filename_removefromid = _T1

config/default_segmentation_bf.ini

@@ -1,6 +1,6 @@
 ############################ input configuration sections
 [modality1]
-csv_path_file=
+csv_file=
 path_to_search = ./example_volumes/monomodal_parcellation
 filename_contains = T1
 filename_not_contains =

config/label_driven_registration.ini

@@ -32,23 +32,23 @@ save_seg_dir = resampled_moving/
 
 ############################ input configuration sections
 [image0]
-csv_path_file= ./image0.csv
+csv_file= ./image0.csv
 path_to_search = /mnt/shared/wenqi/reg_data/us_images
 filename_contains =
 filename_not_contains =
 spatial_window_size = (80, 112, 80)
 interp_order = 3
 
 [label0]
-csv_path_file= ./label0.csv
+csv_file= ./label0.csv
 path_to_search = /mnt/shared/wenqi/reg_data/us_labels
 filename_contains = _label000
 filename_not_contains =
 spatial_window_size = (80, 112, 80)
 interp_order = 3
 
 [image1]
-csv_path_file= ./image1.csv
+csv_file= ./image1.csv
 path_to_search = /mnt/shared/wenqi/reg_data/mr_images
 filename_contains =
 filename_not_contains =
@@ -57,7 +57,7 @@ spatial_window_size = (80, 112, 80)
 interp_order = 3
 
 [label1]
-csv_path_file= ./label1.csv
+csv_file= ./label1.csv
 path_to_search = /mnt/shared/wenqi/reg_data/mr_labels
 filename_contains = _label000
 filename_not_contains =

demos/module_examples/FullCSVReaderDemo.ipynb

@@ -229,7 +229,7 @@
     "# Make sure we accept 'Label', 'label', 'LABEL'\n",
     "task_param = TaskParam(['image'])\n",
     "image_data_param = {'CT': {'path_to_search': '~/niftynet/data/mr_ct_regression/CT_zero_mean', 'filename_contains': 'nii'}}\n",
-    "# Change csv_file -> csv_path_file, csv_data_file is a csv with data\n",
+    "#csv_data_file is a csv with data\n",
     "csv_data_param = {'label': {'csv_data_file': 'label.csv', 'to_ohe': True}}\n",
     "grouping_param = {'image': (['CT'])}\n",
     "\n",

demos/unet/U-Net_Demo.ipynb

@@ -223,7 +223,7 @@
     "############################ input configuration sections\n",
     "-[modality1]\n",
     "+[cells]   # you can name this whatever you want\n",
-    "-csv_path_file=  # we will find the images by searching\n",
+    "-csv_file=  # we will find the images by searching\n",
     "-path_to_search = ./example_volumes/monomodal_parcellation\n",
     "+path_to_search = ./data/u-net/PhC-C2DH-U373/niftynet_data\n",
     "-filename_contains = T1\n",

doc/source/config_spec.md

@@ -155,8 +155,7 @@ understand how files are matched.
 
  Name | Type | Example | Default
  ---- | ---- | ------- | -------
-
-[csv_path_file](#csv-path-file) | `string` | `csv_path_file=file_list.csv` | `''`
+[csv_file](#csv-file) | `string` | `csv_file=file_list.csv` | `''`
 [path_to_search](#path-to-search) | `string` | `path_to_search=my_data/fold_1` | NiftyNet home folder
 [filename_contains](#filename-contains) | `string` or `string array` | `filename_contains=foo, bar` | `''`
 [filename_not_contains](#filename-not-contains) | `string` or `string array` | `filename_not_contains=foo` | `''`
@@ -167,7 +166,7 @@ understand how files are matched.
 [spatial_window_size](#spatial-window-size) | `integer array` | `spatial_window_size=64, 64, 64` | `''`
 [loader](#loader) | `string` | `loader=simpleitk` | `None`
 
-###### `csv_path_file`
+###### `csv_file`
 A file path to a list of input images.  If the file exists, input image name
 list will be loaded from the file; the filename based input image search will
 be disabled; [path_to_search](#path-to-search),
@@ -279,8 +278,8 @@ with an interpolation order of `3`.
 
 A CSV file with the matched filenames and extracted subject names will be
 generated to `T1Image.csv` in [`model_dir`](#model-dir) (by default; the CSV
-file location can be specified by setting [csv_path_file](#csv-path-file)).  To exclude
-particular images, the [csv_path_file](#csv-path-file) can be edited manually.
+file location can be specified by setting [csv_file](#csv-file)).  To exclude
+particular images, the [csv_file](#csv-file) can be edited manually.
 
 This input source can be used alone, as a `T1` MRI input to an application.
 It can also be used along with other modalities, a multi-modality example

niftynet/contrib/csv_reader/class_seg_finnet.py

@@ -13,7 +13,7 @@
 from niftynet.network.base_net import BaseNet
 from niftynet.layer.layer_util import infer_spatial_rank
 from niftynet.layer.fully_connected import FullyConnectedLayer
-from niftynet.layer.pool_full import PoolingLayer
+# from niftynet.layer.pool_full import PoolingLayer
 import tensorflow as tf
 
 
@@ -72,10 +72,11 @@ def layer_op(self, images, is_training, layer_id=-1):
 
         # pooling layer
         params = self.layers[1]
-        pool_layer = PoolingLayer(
-            func=params['func'],
-            name=params['name'])
-        flow_pool = pool_layer(flow)
+        # pool_layer = PoolingLayer(
+        #     func=params['func'],
+        #     name=params['name'])
+        # flow_pool = pool_layer(flow)
+        flow_pool = flow
         flow_pool = tf.reshape(flow_pool, [tf.shape(images)[0], 1, 1, 1,
                                            self.layers[1][
             'n_features']])

niftynet/contrib/csv_reader/default_segmentation_multitask.ini

@@ -1,6 +1,6 @@
 ############################ input configuration sections
 [modality1]
-csv_path_file=
+csv_file=
 path_to_search = ./example_volumes/monomodal_parcellation
 filename_contains = T1
 filename_removefromid = _T1

niftynet/contrib/segmentation_selective_sampler/selective_seg.ini

@@ -1,6 +1,6 @@
 ############################ input configuration sections
 [modality1]
-csv_path_file=
+csv_file=
 path_to_search = ./example_volumes/monomodal_parcellation
 filename_contains = T1
 filename_not_contains =

niftynet/contrib/segmentation_selective_sampler/test_sampler_selective.py

@@ -54,7 +54,7 @@ def check_constraint(data, constraint):
 
 MULTI_MOD_DATA = {
     'T1': ParserNamespace(
-        csv_path_file=os.path.join('testing_data', 'T1sampler.csv'),
+        csv_file=os.path.join('testing_data', 'T1sampler.csv'),
         path_to_search='testing_data',
         filename_contains=('_o_T1_time',),
         filename_not_contains=('Parcellation',),
@@ -65,7 +65,7 @@ def check_constraint(data, constraint):
         loader=None
     ),
     'FLAIR': ParserNamespace(
-        csv_path_file=os.path.join('testing_data', 'FLAIRsampler.csv'),
+        csv_file=os.path.join('testing_data', 'FLAIRsampler.csv'),
         path_to_search='testing_data',
         filename_contains=('FLAIR_',),
         filename_not_contains=('Parcellation',),
@@ -76,7 +76,7 @@ def check_constraint(data, constraint):
         loader=None
     ),
     'Label': ParserNamespace(
-        csv_path_file=os.path.join('testing_data', 'lesion.csv'),
+        csv_file=os.path.join('testing_data', 'lesion.csv'),
         path_to_search='testing_data',
         filename_contains=('LesionFin_',),
         filename_not_constains=('FLAIR_',),
@@ -89,7 +89,7 @@ def check_constraint(data, constraint):
 }
 LABEL_TASK = {
     'Lesion': ParserNamespace(
-        csv_path_file=os.path.join('testing_data', 'lesion.csv'),
+        csv_file=os.path.join('testing_data', 'lesion.csv'),
         path_to_search='testing_data',
         filename_contains=('LesionFin_'),
         filename_not_contains=('Parcellation',),
@@ -104,7 +104,7 @@ def check_constraint(data, constraint):
 
 MOD_2D_DATA = {
     'ultrasound': ParserNamespace(
-        csv_path_file=os.path.join('testing_data', 'T1sampler2d.csv'),
+        csv_file=os.path.join('testing_data', 'T1sampler2d.csv'),
         path_to_search='testing_data',
         filename_contains=('2d_',),
         filename_not_contains=('Parcellation',),
@@ -119,7 +119,7 @@ def check_constraint(data, constraint):
 
 DYNAMIC_MOD_DATA = {
     'T1': ParserNamespace(
-        csv_path_file=os.path.join('testing_data', 'T1sampler.csv'),
+        csv_file=os.path.join('testing_data', 'T1sampler.csv'),
         path_to_search='testing_data',
         filename_contains=('_o_T1_time',),
         filename_not_contains=('Parcellation',),
@@ -130,7 +130,7 @@ def check_constraint(data, constraint):
         loader=None
     ),
     'FLAIR': ParserNamespace(
-        csv_path_file=os.path.join('testing_data', 'FLAIRsampler.csv'),
+        csv_file=os.path.join('testing_data', 'FLAIRsampler.csv'),
         path_to_search='testing_data',
         filename_contains=('FLAIR_',),
         filename_not_contains=('Parcellation',),
@@ -141,7 +141,7 @@ def check_constraint(data, constraint):
         loader=None
     ),
     'Label': ParserNamespace(
-        csv_path_file=os.path.join('testing_data', 'labels.csv'),
+        csv_file=os.path.join('testing_data', 'labels.csv'),
         path_to_search='testing_data',
         filename_contains=('T1_', '_NeuroMorph_Parcellation',),
         filename_not_constains=('FLAIR_',),
@@ -155,7 +155,7 @@ def check_constraint(data, constraint):
 
 # LABEL_TASK = {
 #     'Parcellation': ParserNamespace(
-#         csv_path_file=os.path.join('testing_data', 'labels.csv'),
+#         csv_file=os.path.join('testing_data', 'labels.csv'),
 #         path_to_search='testing_data',
 #         filename_contains=('Parcellation',),
 #         filename_not_constains=('FLAIR_',),

niftynet/io/image_reader.py

@@ -21,7 +21,7 @@
 DEFAULT_INTERP_ORDER = 1
 SUPPORTED_DATA_SPEC = {
 
-    'csv_path_file', 'path_to_search', 'csv_data_file', 'filename_removefromid',
+    'csv_file', 'path_to_search', 'csv_data_file', 'filename_removefromid',
     'filename_contains', 'filename_not_contains', 'to_ohe',
     'interp_order', 'loader', 'pixdim', 'axcodes', 'spatial_window_size'}
 
@@ -410,7 +410,7 @@ def _filename_to_image_list(file_list, mod_dict, data_param):
     if not volume_list:
         tf.logging.fatal(
             "Empty filename lists, please check the csv "
-            "files. (removing csv_path_file keyword if it is"
+            "files. (removing csv_file keyword if it is"
             " in the config file "
             "to automatically search folders and generate new csv "
             "files again)\n\n"