better score presentation

ade.py

@@ -920,7 +920,7 @@ class AffHQ12(_DatasetBySample):
                 seg_img = cv2.imread(filename)
                 assert seg_img is not None, 'image not found: {}'.format(filename)
 
-            seg += [self.threshold(seg_img)]
+            seg += [np.uint8(seg_img[:, :, 0] > 0)]
 
         seg = np.array(seg, dtype='float32')
         # seg = seg.argmax(0)

paths.yaml

 ADE20K_PATH: data
-HQ_AFF: data/Expert
+HQ_AFF: data/aff_expert
 OREGON_AFFORDANCES: data/Oregon_Affordance
 AVA_DATA: data
 CACHE: cache

score.py

@@ -56,6 +56,8 @@ def score(model_name, dataset_name, batch_size):
         for j in range(len(metrics)):
             metrics[j].add(pred, vars_y)
 
+    print('\n\nFinal scores:')
+
     for i in range(len(metrics)):
         score = metrics[i].value()
         for name, s in zip(metrics[i].names(), score):