convert to abs path + csv as input in test

deepmedic/frontEnd/configParsing/testConfig.py

@@ -20,6 +20,8 @@ class TestConfig(Config):
     FOLDER_OUTP = "folderForOutput" #MUST BE GIVEN
     SAVED_MODEL = "cnnModelFilePath" #MUST BE GIVEN
     CHANNELS = "channels" #MUST BE GIVEN
+
+    CSV_TEST = "csvTest"
 
     NAMES_FOR_PRED_PER_CASE = "namesForPredictionsPerCase"
 

deepmedic/frontEnd/configParsing/testSessionParams.py

@@ -7,7 +7,11 @@
 
 from __future__ import absolute_import, print_function, division
 
-from deepmedic.frontEnd.configParsing.utils import getAbsPathEvenIfRelativeIsGiven, parseAbsFileLinesInList, parseFileLinesInList, check_and_adjust_path_to_ckpt
+import pandas as pd
+import os
+
+from deepmedic.frontEnd.configParsing.utils import getAbsPathEvenIfRelativeIsGiven, parseAbsFileLinesInList, parseFileLinesInList, check_and_adjust_path_to_ckpt, get_paths_from_csv
+
 
 class TestSessionParameters(object) :
     #To be called from outside too.
@@ -21,6 +25,14 @@ def errorIntNormZScoreTwoAppliesGiven():
               "\n\tOtherwise, requires ['apply_to_all_channels': False] if ['apply_per_channel': [..list..] ]"
               "\n\tExiting!")
         exit(1)
+
+    @staticmethod
+    def errorRequireValidCsvTest():
+        print(
+            "ERROR: Test CSV file \"csvTest\" does not exist. Exiting.")
+        exit(1)
+
+    errReqCsvTest = errorRequireValidCsvTest
 
     def __init__(self,
                 log,
@@ -42,14 +54,32 @@ def __init__(self,
         self.savedModelFilepath = check_and_adjust_path_to_ckpt( self.log, abs_path_to_saved) if abs_path_to_saved is not None else None
 
         #Input:
-        #[[case1-ch1, ..., caseN-ch1], [case1-ch2,...,caseN-ch2]]
-        listOfAListPerChannelWithFilepathsOfAllCases = [parseAbsFileLinesInList(getAbsPathEvenIfRelativeIsGiven(channelConfPath, abs_path_to_cfg)) for channelConfPath in cfg[cfg.CHANNELS]]
-        self.channelsFilepaths = [ list(item) for item in zip(*tuple(listOfAListPerChannelWithFilepathsOfAllCases)) ] # [[case1-ch1, case1-ch2], ..., [caseN-ch1, caseN-ch2]]
-        self.gtLabelsFilepaths = parseAbsFileLinesInList( getAbsPathEvenIfRelativeIsGiven(cfg[cfg.GT_LABELS], abs_path_to_cfg) ) if cfg[cfg.GT_LABELS] is not None else None
-        self.roiMasksFilepaths = parseAbsFileLinesInList( getAbsPathEvenIfRelativeIsGiven(cfg[cfg.ROI_MASKS], abs_path_to_cfg) ) if cfg[cfg.ROI_MASKS] is not None else None
-
-        #Output:
-        self.namesToSavePredictionsAndFeatures = parseFileLinesInList( getAbsPathEvenIfRelativeIsGiven(cfg[cfg.NAMES_FOR_PRED_PER_CASE], abs_path_to_cfg) ) if cfg[cfg.NAMES_FOR_PRED_PER_CASE] is not None else None #CAREFUL: different parser! #Optional. Not required if not saving results.
+        self.csv_test_fname = getAbsPathEvenIfRelativeIsGiven(cfg[cfg.CSV_TEST], abs_path_to_cfg) \
+            if cfg[cfg.CSV_TEST] is not None else None
+        if self.csv_test_fname is not None:
+            try:
+                self.csv_test = pd.read_csv(self.csv_test_fname)
+            except FileNotFoundError:
+                self.errReqCsvTest()
+        else:
+            self.csv_test = None
+
+        if self.csv_test is None:
+            #[[case1-ch1, ..., caseN-ch1], [case1-ch2,...,caseN-ch2]]
+            listOfAListPerChannelWithFilepathsOfAllCases = [parseAbsFileLinesInList(getAbsPathEvenIfRelativeIsGiven(channelConfPath, abs_path_to_cfg)) for channelConfPath in cfg[cfg.CHANNELS]]
+            self.channelsFilepaths = [ list(item) for item in zip(*tuple(listOfAListPerChannelWithFilepathsOfAllCases)) ] # [[case1-ch1, case1-ch2], ..., [caseN-ch1, caseN-ch2]]
+            self.gtLabelsFilepaths = parseAbsFileLinesInList( getAbsPathEvenIfRelativeIsGiven(cfg[cfg.GT_LABELS], abs_path_to_cfg) ) if cfg[cfg.GT_LABELS] is not None else None
+            self.roiMasksFilepaths = parseAbsFileLinesInList( getAbsPathEvenIfRelativeIsGiven(cfg[cfg.ROI_MASKS], abs_path_to_cfg) ) if cfg[cfg.ROI_MASKS] is not None else None
+
+            #Output:
+            self.namesToSavePredictionsAndFeatures = parseFileLinesInList( getAbsPathEvenIfRelativeIsGiven(cfg[cfg.NAMES_FOR_PRED_PER_CASE], abs_path_to_cfg) ) if cfg[cfg.NAMES_FOR_PRED_PER_CASE] is not None else None #CAREFUL: different parser! #Optional. Not required if not saving results.
+        else:
+            (self.channelsFilepaths,
+             self.gtLabelsFilepaths,
+             self.roiMasksFilepaths,
+             self.namesToSavePredictionsAndFeatures) = get_paths_from_csv(self.csv_test,
+                                                                          os.path.dirname(self.csv_test_fname))
+
         #predictions
         self.saveSegmentation = cfg[cfg.SAVE_SEGM] if cfg[cfg.SAVE_SEGM] is not None else True
         self.saveProbMapsBoolPerClass = cfg[cfg.SAVE_PROBMAPS_PER_CLASS] if (cfg[cfg.SAVE_PROBMAPS_PER_CLASS] is not None and cfg[cfg.SAVE_PROBMAPS_PER_CLASS] != []) else [True]*num_classes

deepmedic/frontEnd/configParsing/trainSessionParams.py

@@ -13,6 +13,7 @@
 from deepmedic.dataManagement.augmentImage import AugmenterAffineParams
 
 import pandas as pd
+import os
 
 
 def get_default(value, default, required=False):
@@ -36,7 +37,6 @@ class TrainSessionParameters(object):
     def getSessionName(sessionName):
         return sessionName if sessionName is not None else "trainSession"
 
-    # REQUIRED:
     @staticmethod
     def errorRequireValidCsvTraining():
         print(
@@ -45,7 +45,6 @@ def errorRequireValidCsvTraining():
 
     errReqCsvTrain = errorRequireValidCsvTraining
 
-    # REQUIRED:
     @staticmethod
     def errorRequireValidCsvValidation():
         print(
@@ -249,10 +248,11 @@ def __init__(self,
             self.gtLabelsFilepathsTrain = \
                 parseAbsFileLinesInList(getAbsPathEvenIfRelativeIsGiven(cfg[cfg.GT_LABELS_TR], abs_path_to_cfg))
         else:
+            print(os.path.dirname(self.csv_train_fname))
             (self.channelsFilepathsTrain,
              self.gtLabelsFilepathsTrain,
              self.roiMasksFilepathsTrain,
-             _) = get_paths_from_csv(self.csv_train)
+             _) = get_paths_from_csv(self.csv_train, os.path.dirname(self.csv_train_fname))
 
         # [Optionals]
         # ~~~~~~~~~Sampling~~~~~~~
@@ -365,7 +365,8 @@ def __init__(self,
                 (self.channelsFilepathsVal,
                  self.gtLabelsFilepathsVal,
                  self.roiMasksFilepathsVal,
-                 self.namesToSavePredictionsAndFeaturesVal) = get_paths_from_csv(self.csv_val)
+                 self.namesToSavePredictionsAndFeaturesVal) = get_paths_from_csv(self.csv_val,
+                                                                                 os.path.dirname(self.csv_val_fname))
 
         else:
             self.channelsFilepathsVal = []

deepmedic/frontEnd/configParsing/utils.py

@@ -94,19 +94,27 @@ def check_and_adjust_path_to_ckpt( log, filepath_to_ckpt ):
     return filepath_to_ckpt
 
 
-def get_paths_from_csv(csv, no_target_okay=False):
+def normfullpath(abspath, relpath):
+    if os.path.isabs(relpath):
+        return relpath
+    else:
+        return os.path.normpath(os.path.join(abspath, relpath))
+
+
+def get_paths_from_csv(csv, abs_path, no_target_okay=False):
     # channels are sorted alphabetically to ensure consistency
     c_names = sorted([c for c in list(csv.columns) if c.startswith('channel_')])
+
     if not c_names:
         # no channels error raise - move to function later
         print('No channel columns on csv. Columns should be named "channel_[channel_name]". Exiting')
         exit(1)
 
     # [[case1-ch1, case1-ch2], ..., [caseN-ch1, caseN-ch2]]
-    channels = [list(item[c_names]) for _, item in csv.iterrows()]
+    channels = [[normfullpath(abs_path, c) for c in list(item[c_names])] for _, item in csv.iterrows()]
 
     try:
-        target = [list(csv['gt'])]
+        target = [normfullpath(abs_path, g) for g in list(csv['gt'])]
     except KeyError:
         target = None
         if not no_target_okay:
@@ -115,13 +123,13 @@ def get_paths_from_csv(csv, no_target_okay=False):
             exit(1)
 
     try:
-        roi = [list(csv['roi'])]
+        roi = [normfullpath(abs_path, r) for r in list(csv['roi'])]
     except KeyError:
         print('No "roi" column in input csv, not using roi masks.')
         roi = None
 
     try:
-        pred = [list(csv['pred'])]
+        pred = [normfullpath(abs_path, p) for p in list(csv['pred'])]
     except KeyError:
         pred = None