Add client id as optional parameter to pass to projection function

bob/bio/base/algorithm/Algorithm.py

@@ -74,6 +74,7 @@ class Algorithm (object):
       self,
       performs_projection = False, # enable if your tool will project the features
       requires_projector_training = True, # by default, the projector needs training, if projection is enabled
+      requires_client_id_for_proj=False, # enable if you need to use the client id in the projection
       split_training_features_by_client = False, # enable if your projector training needs the training files sorted by client
       use_projected_features_for_enrollment = True, # by default, the enroller used projected features for enrollment, if projection is enabled.
       requires_enroller_training = False, # enable if your enroller needs training
@@ -89,6 +90,7 @@ class Algorithm (object):
   ):
     self.performs_projection = performs_projection
     self.requires_projector_training = performs_projection and requires_projector_training
+    self.requires_client_id_for_proj = performs_projection and requires_client_id_for_proj
     self.split_training_features_by_client = split_training_features_by_client
     self.use_projected_features_for_enrollment = performs_projection and use_projected_features_for_enrollment
     self.requires_enroller_training = requires_enroller_training

bob/bio/base/tools/algorithm.py

@@ -97,6 +97,7 @@ def project(algorithm, extractor, groups = None, indices = None, allow_missing_f
   # load the projector
   algorithm.load_projector(fs.projector_file)
 
+  original_data_files = fs.original_data_list(groups=groups) # the actual file objects
   feature_files = fs.feature_list(groups=groups)
   projected_files = fs.projected_list(groups=groups)
 
@@ -129,7 +130,11 @@ def project(algorithm, extractor, groups = None, indices = None, allow_missing_f
       # load feature
       feature = extractor.read_feature(feature_file)
       # project feature
-      projected = algorithm.project(feature)
+      if algorithm.requires_client_id_for_proj:
+        file_object = original_data_files[i]
+        projected = algorithm.project(feature, file_object.client_id)
+      else:
+        projected = algorithm.project(feature)
 
       if projected is None:
         if allow_missing_files: