small fixes fo pickle dumps

src/alexnet.py

@@ -19,11 +19,12 @@ load_weights_of(model, dataset)
 emb_vectors, emb_labels = get_embeddings_of(model.get_embedding_model(), dataset)
 emb_ds = SiameseModel.prepare_dataset(emb_vectors, emb_labels)
 
+MARGIN = 0.5
 siamese = SiameseModel(embedding_model=model.get_embedding_model(), image_vector_dimensions=512)
-siamese.compile(loss_margin=0.05)
+siamese.compile(loss_margin=MARGIN)
 siamese.fit(emb_ds, num_classes=dataset.num_classes)
 
 projection_vectors = siamese.projection_model.predict(emb_vectors)
-save_vectors(projection_vectors, emb_labels, dataset.name + '_' + siamese.name + '_vectors')
-project_embeddings(projection_vectors, emb_labels, siamese.name + '_' + dataset.name)
+# save_vectors(projection_vectors, emb_labels, dataset.name + '_' + siamese.name + '_vectors')
+project_embeddings(projection_vectors, emb_labels, str(MARGIN) + '_' + siamese.name + '_' + dataset.name)
 print('Done!')

src/utils/embeddings.py

@@ -17,7 +17,7 @@ def _save_vectors_path(values, labels, path):
     data = [values, labels]
 
     with bz2.BZ2File(path, 'wb') as f:
-        pickle.dump(data, f, -1)
+        pickle.dump(data, f, 4)
 
 
 def _load_vectors_path(path):
@@ -28,11 +28,11 @@ def _load_vectors_path(path):
 
 
 def load_vectors(name='embeddings'):
-    return _load_vectors_path(get_datadir(name + '.pkl'))
+    return _load_vectors_path(get_datadir(name + '.pbz2'))
 
 
 def save_vectors(values, labels, name='embeddings'):
-    return _save_vectors_path(values, labels, get_datadir(name + '.pkl'))
+    return _save_vectors_path(values, labels, get_datadir(name + '.pbz2'))
 
 
 def export_vectors(values, labels, name='embeddings'):