diff --git a/samplelib/PackedFaceset.py b/samplelib/PackedFaceset.py
index 055efd7..3805281 100644
--- a/samplelib/PackedFaceset.py
+++ b/samplelib/PackedFaceset.py
@@ -73,7 +73,10 @@ class PackedFaceset():
                 offsets.append ( of.tell() - data_start_offset )
                 of.write(b)
             except:
-                raise Exception(f"error while processing sample {sample.filename}")
+                import code
+                code.interact(local=dict(globals(), **locals()))
+
+                raise Exception(f"error while processing sample {sample_path}")
 
         offsets.append ( of.tell() )
 
diff --git a/samplelib/SampleHost.py b/samplelib/SampleHost.py
index 83955bf..ce8e9a7 100644
--- a/samplelib/SampleHost.py
+++ b/samplelib/SampleHost.py
@@ -1,15 +1,17 @@
+import multiprocessing
 import operator
 import traceback
 from pathlib import Path
 
+import samplelib.PackedFaceset
+from DFLIMG import *
 from facelib import FaceType, LandmarksProcessor
 from interact import interact as io
+from joblib import Subprocessor
 from utils import Path_utils, mp_utils
-from DFLIMG import *
 
 from .Sample import Sample, SampleType
 
-import samplelib.PackedFaceset
 
 class SampleHost:
     samples_cache = dict()
@@ -79,17 +81,32 @@ class SampleHost:
         return hosts[sample_type]
 
     @staticmethod
-    def load_face_samples ( image_paths, silent=False):
+    def load_face_samples ( image_paths):        
+        result = FaceSamplesLoaderSubprocessor(image_paths).run()
         sample_list = []
 
-        for filename in (image_paths if silent else io.progress_bar_generator( image_paths, "Loading")):
+        for filename,dflimg in io.progress_bar_generator(result, "Processing"):
+            sample_list.append( Sample(filename=filename,
+                                        sample_type=SampleType.FACE,
+                                        face_type=FaceType.fromString (dflimg.get_face_type()),
+                                        shape=dflimg.get_shape(),
+                                        landmarks=dflimg.get_landmarks(),
+                                        ie_polys=dflimg.get_ie_polys(),
+                                        pitch_yaw_roll=dflimg.get_pitch_yaw_roll(),
+                                        eyebrows_expand_mod=dflimg.get_eyebrows_expand_mod(),
+                                        source_filename=dflimg.get_source_filename(),                                       
+                                    ))
+        return sample_list
+        
+        """
+        sample_list = []
+
+        for filename in io.progress_bar_generator(image_paths, "Loading"):
             filename_path = Path(filename)
             try:
                 dflimg = DFLIMG.load (filename_path)                    
 
-                if dflimg is None:
-                    io.log_err ("load_face_samples: %s is not a dfl image file required for training" % (filename_path.name) )
-                    continue
+                
                 
                 sample_list.append( Sample(filename=filename,
                                            sample_type=SampleType.FACE,
@@ -105,6 +122,7 @@ class SampleHost:
                 io.log_err ("Unable to load %s , error: %s" % (filename, traceback.format_exc() ) )
 
         return sample_list
+        """
 
     @staticmethod
     def upgradeToFaceTemporalSortedSamples( samples ):
@@ -112,3 +130,70 @@ class SampleHost:
         new_s = sorted(new_s, key=operator.itemgetter(1))
 
         return [ s[0] for s in new_s]
+        
+
+class FaceSamplesLoaderSubprocessor(Subprocessor):
+    #override
+    def __init__(self, image_paths ):
+        self.image_paths = image_paths
+        self.image_paths_len = len(image_paths)
+        self.idxs = [*range(self.image_paths_len)]        
+        self.result = [None]*self.image_paths_len
+        super().__init__('FaceSamplesLoader', FaceSamplesLoaderSubprocessor.Cli, 60, initialize_subprocesses_in_serial=False)
+
+    #override
+    def on_clients_initialized(self):
+        io.progress_bar ("Loading", len (self.image_paths))
+
+    #override
+    def on_clients_finalized(self):
+        io.progress_bar_close()
+
+    #override
+    def process_info_generator(self):
+        for i in range(min(multiprocessing.cpu_count(), 8) ):
+            yield 'CPU%d' % (i), {}, {'device_idx': i,
+                                      'device_name': 'CPU%d' % (i),
+                                      }
+
+    #override
+    def get_data(self, host_dict):
+        if len (self.idxs) > 0:
+            idx = self.idxs.pop(0)
+            return idx, self.image_paths[idx]
+
+        return None
+
+    #override
+    def on_data_return (self, host_dict, data):
+        self.idxs.insert(0, data[0])
+
+    #override
+    def on_result (self, host_dict, data, result):
+        idx, dflimg = result
+        self.result[idx] = (self.image_paths[idx], dflimg)
+        io.progress_bar_inc(1)
+
+    #override
+    def get_result(self):
+        return self.result
+
+    class Cli(Subprocessor.Cli):
+        #override
+        def on_initialize(self, client_dict):
+            self.log_info ('Running on %s.' % (client_dict['device_name']) )
+
+        #override
+        def process_data(self, data):
+            idx, filename = data
+            dflimg = DFLIMG.load (Path(filename))
+                        
+            if dflimg is None:
+                self.log_err (f"FaceSamplesLoader: {filename} is not a dfl image file.")
+                            
+            return idx, dflimg
+
+        #override
+        def get_data_name (self, data):
+            #return string identificator of your data
+            return data[1]