diff --git a/Makefile b/Makefile
index e3ad1dd..fc24281 100644
--- a/Makefile
+++ b/Makefile
@@ -41,12 +41,12 @@ build-%: version Dockerfile-%
 quick_test: $(addprefix test-,$(PYMAIN))
 
 dev-%:
-	@docker start $(NAME)-dev || (\
+	@docker start $(NAME)-dev$* || (\
 		$(MAKE) build-$*; \
-		docker run -d -w /usr/src/app/ -v $$PWD:/usr/src/app --entrypoint=/bin/bash -p 5000:5000 -ti --name $(NAME)-dev '$(IMAGEWTAG)-python$*'; \
+		docker run -d -w /usr/src/app/ -v $$PWD:/usr/src/app --entrypoint=/bin/bash -ti --name $(NAME)-dev$* '$(IMAGEWTAG)-python$*'; \
 	)\
 
-	docker exec -ti $(NAME)-dev bash
+	docker exec -ti $(NAME)-dev$* bash
 
 dev: dev-$(PYMAIN)
 
diff --git a/senpy/extensions.py b/senpy/extensions.py
index 861dc89..3686ae7 100644
--- a/senpy/extensions.py
+++ b/senpy/extensions.py
@@ -17,7 +17,7 @@ import copy
 import fnmatch
 import inspect
 import sys
-import imp
+import importlib
 import logging
 import traceback
 import yaml
@@ -181,7 +181,7 @@ class Senpy(object):
         newentries = []
         for i in resp.entries:
             if output == "full":
-                newemotions = copy.copy(i.emotions)
+                newemotions = copy.deepcopy(i.emotions)
             else:
                 newemotions = []
             for j in i.emotions:
@@ -303,6 +303,13 @@ class Senpy(object):
             logger.info('Installing requirements: ' + str(requirements))
             pip.main(pip_args)
 
+    @classmethod
+    def _load_module(cls, name, root):
+        sys.path.append(root)
+        tmp = importlib.import_module(name)
+        sys.path.remove(root)
+        return tmp
+
     @classmethod
     def _load_plugin_from_info(cls, info, root):
         if not cls.validate_info(info):
@@ -310,11 +317,10 @@ class Senpy(object):
             return None, None
         module = info["module"]
         name = info["name"]
-        sys.path.append(root)
-        (fp, pathname, desc) = imp.find_module(module, [root, ])
+
         cls._install_deps(info)
-        tmp = imp.load_module(module, fp, pathname, desc)
-        sys.path.remove(root)
+        tmp = cls._load_module(module, root)
+
         candidate = None
         for _, obj in inspect.getmembers(tmp):
             if inspect.isclass(obj) and inspect.getmodule(obj) == tmp:
diff --git a/senpy/plugins.py b/senpy/plugins/__init__.py
similarity index 99%
rename from senpy/plugins.py
rename to senpy/plugins/__init__.py
index 693cb43..fdc6882 100644
--- a/senpy/plugins.py
+++ b/senpy/plugins/__init__.py
@@ -7,7 +7,7 @@ import pickle
 import logging
 import tempfile
 import copy
-from . import models
+from .. import models
 
 logger = logging.getLogger(__name__)
 
diff --git a/senpy/plugins/conversion/__init__.py b/senpy/plugins/conversion/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/senpy/plugins/conversion/centroids.py b/senpy/plugins/conversion/centroids.py
new file mode 100644
index 0000000..0d0b899
--- /dev/null
+++ b/senpy/plugins/conversion/centroids.py
@@ -0,0 +1,52 @@
+from senpy.plugins import EmotionConversionPlugin
+from senpy.models import EmotionSet, Emotion, Error
+
+import logging
+logger = logging.getLogger(__name__)
+
+
+class CentroidConversion(EmotionConversionPlugin):
+
+    def _forward_conversion(self, original):
+        """Sum the VAD value of all categories found."""
+        res = Emotion()
+        for e in original.onyx__hasEmotion:
+            category = e.onyx__hasEmotionCategory
+            if category in self.centroids:
+                for dim, value in self.centroids[category].iteritems():
+                    try:
+                        res[dim] += value
+                    except Exception:
+                        res[dim] = value
+        return res
+
+    def _backwards_conversion(self, original):
+        """Find the closest category"""
+        dimensions = list(self.centroids.values())[0]
+
+        def distance(e1, e2):
+            return sum((e1[k] - e2.get(self.aliases[k], 0)) for k in dimensions)
+
+        emotion = ''
+        mindistance = 10000000000000000000000.0
+        for state in self.centroids:
+            d = distance(self.centroids[state], original)
+            if d < mindistance:
+                mindistance = d
+                emotion = state
+        result = Emotion(onyx__hasEmotionCategory=emotion)
+        return result
+
+    def convert(self, emotionSet, fromModel, toModel, params):
+
+        cf, ct = self.centroids_direction
+        logger.debug('{}\n{}\n{}\n{}'.format(emotionSet, fromModel, toModel, params))
+        e = EmotionSet()
+        if fromModel == cf:
+            e.onyx__hasEmotion.append(self._forward_conversion(emotionSet))
+        elif fromModel == ct:
+            for i in emotionSet.onyx__hasEmotion:
+                e.onyx__hasEmotion.append(self._backwards_conversion(i))
+        else:
+            raise Error('EMOTION MODEL NOT KNOWN')
+        yield e
diff --git a/senpy/plugins/conversion/emotion/ekman2vad.py b/senpy/plugins/conversion/emotion/ekman2vad.py
deleted file mode 100644
index f38f83d..0000000
--- a/senpy/plugins/conversion/emotion/ekman2vad.py
+++ /dev/null
@@ -1,58 +0,0 @@
-from senpy.plugins import EmotionConversionPlugin
-from senpy.models import EmotionSet, Emotion, Error
-
-import logging
-logger = logging.getLogger(__name__)
-
-import math
-
-
-class WNA2VAD(EmotionConversionPlugin):
-
-    def _ekman_to_vad(self, ekmanSet):
-        """Sum the VAD value of all categories found."""
-        valence = 0
-        arousal = 0
-        dominance = 0
-        for e in ekmanSet.onyx__hasEmotion:
-            category = e.onyx__hasEmotionCategory
-            centroid = self.centroids[category]
-            valence += centroid['V']
-            arousal += centroid['A']
-            dominance += centroid['D']
-        e = Emotion({'emoml:valence': valence,
-                     'emoml:arousal': arousal,
-                     'emoml:potency': dominance})
-        return e
-
-    def _vad_to_ekman(self, VADEmotion):
-        """Find the closest category"""
-        V = VADEmotion['emoml:valence']
-        A = VADEmotion['emoml:arousal']
-        D = VADEmotion['emoml:potency']
-        emotion = ''
-        value = 10000000000000000000000.0
-        for state in self.centroids:
-            valence = V - self.centroids[state]['V']
-            arousal = A - self.centroids[state]['A']
-            dominance = D - self.centroids[state]['D']
-            new_value = math.sqrt((valence**2) +
-                                  (arousal**2) +
-                                  (dominance**2))
-            if new_value < value:
-                value = new_value
-                emotion = state
-        result = Emotion(onyx__hasEmotionCategory=emotion)
-        return result
-
-    def convert(self, emotionSet, fromModel, toModel, params):
-        logger.debug('{}\n{}\n{}\n{}'.format(emotionSet, fromModel, toModel, params))
-        e = EmotionSet()
-        if fromModel == 'emoml:big6':
-            e.onyx__hasEmotion.append(self._ekman_to_vad(emotionSet))
-        elif fromModel == 'emoml:fsre-dimensions':
-            for i in emotionSet.onyx__hasEmotion:
-                e.onyx__hasEmotion.append(self._vad_to_ekman(i))
-        else:
-            raise Error('EMOTION MODEL NOT KNOWN')
-        yield e
diff --git a/senpy/plugins/conversion/emotion/ekman2vad.senpy b/senpy/plugins/conversion/emotion/ekman2vad.senpy
index 80cb0fc..4246ba7 100644
--- a/senpy/plugins/conversion/emotion/ekman2vad.senpy
+++ b/senpy/plugins/conversion/emotion/ekman2vad.senpy
@@ -1,6 +1,6 @@
 ---
 name: Ekman2VAD
-module: ekman2vad
+module: senpy.plugins.conversion.centroids
 description: Plugin to convert emotion sets from Ekman to VAD
 version: 0.1
 onyx:doesConversion:
@@ -29,6 +29,9 @@ centroids:
     A: 5.21
     D: 2.82
     V: 2.21
+centroids_direction:
+  - emoml:big6
+  - emoml:fsre-dimensions
 aliases:
   A: emoml:arousal
   V: emoml:valence