diff --git a/teng_ml/util/data_loader.py b/teng_ml/util/data_loader.py
index e25e421..7e8a770 100644
--- a/teng_ml/util/data_loader.py
+++ b/teng_ml/util/data_loader.py
@@ -9,8 +9,9 @@ import threading
 
 from sklearn.model_selection import train_test_split
 
-# groups: date, name, voltage, distance, index
-re_filename = r"(\d{4}-\d{2}-\d{2})_([a-zA-Z_]+)_(\d{1,2}(?:\.\d*)?)V_(\d+(?:\.\d*)?)mm(\d+).csv"
+# groups: date, name, n_object, voltage, distance, index
+# re_filename = r"(\d{4}-\d{2}-\d{2})_([a-zA-Z_]+)_(\d{1,2}(?:\.\d*)?)V_(\d+(?:\.\d*)?)mm(\d+).csv"
+re_filename = r"(\d{4}-\d{2}-\d{2})_([a-zA-Z0-9_]+)_(\d+)_(\d{1,2}(?:\.\d*)?)V_(\d+(?:\.\d*)?)mm(\d+).csv"
 
 class LabelConverter:
     def __init__(self, class_labels: list[str]):
@@ -40,10 +41,10 @@ class LabelConverter:
 
 
 class Datasample:
-    def __init__(self, date: str, label: str, voltage: str, distance: str, index: str, label_vec, datapath: str, init_data=False):
+    def __init__(self, date: str, label: str, n_object: str, voltage: str, distance: str, index: str, label_vec, datapath: str, init_data=False):
         self.date = date
         self.label = label
-        self.n_object = n_object
+        self.n_object = int(n_object)
         self.voltage = float(voltage)
         self.distance = float(distance)
         self.index = int(index)
@@ -101,9 +102,9 @@ class Dataset:
         return len(self.data)
 
 
-def get_datafiles(datadir, labels: LabelConverter, voltage=None):
+def get_datafiles(datadir, labels: LabelConverter, exclude_n_object=None, filter_voltage=None):
     """
-    get a list of all matching datafiles from datadir that are in the format: yyyy-mm-dd_label_x.xV_xxxmm.csv
+    get a list of all matching datafiles from datadir that are in the format: yyyy-mm-dd_label__n_object_x.xV_xxxmm.csv
     """
     datafiles = []
     files = listdir(datadir)
@@ -115,8 +116,11 @@ def get_datafiles(datadir, labels: LabelConverter, voltage=None):
         label = match.groups()[1]
         if label not in labels: continue
 
-        sample_voltage = float(match.groups()[2])
-        if voltage and voltage != sample_voltage: continue
+        sample_n_object = float(match.groups()[2])
+        if exclude_n_object and exclude_n_object == sample_n_object: continue
+        sample_voltage = float(match.groups()[3])
+        if filter_voltage and filter_voltage != sample_voltage: continue
+
         datafiles.append((datadir + "/" + file, match, label))
     return datafiles
 
@@ -145,7 +149,6 @@ def load_datasets(datadir, labels: LabelConverter, transforms=None, split_functi
         for t in threads:
             t.join()
 
-
     # TODO do the train_test_split after the Dataset split
     # problem: needs to be after transforms
     train_samples, test_samples = train_test_split(datasamples, train_size=train_to_test_ratio, shuffle=True, random_state=random_state)