new nc=len(names) check

train.py

@@ -57,7 +57,7 @@ def train(hyp):
         yaml.dump(hyp, f, sort_keys=False)
     with open(Path(log_dir) / 'opt.yaml', 'w') as f:
         yaml.dump(vars(opt), f, sort_keys=False)
-        
+
     epochs = opt.epochs  # 300
     batch_size = opt.batch_size  # 64
     weights = opt.weights  # initial training weights
@@ -68,7 +68,8 @@ def train(hyp):
         data_dict = yaml.load(f, Loader=yaml.FullLoader)  # model dict
     train_path = data_dict['train']
     test_path = data_dict['val']
-    nc = 1 if opt.single_cls else int(data_dict['nc'])  # number of classes
+    nc, names = (1, ['item']) if opt.single_cls else (int(data_dict['nc']), data_dict['names'])  # number classes, names
+    assert len(names) == nc, '%g names found for nc=%g dataset in %s' % (len(names), nc, opt.data)  # check
 
     # Remove previous results
     for f in glob.glob('*_batch*.jpg') + glob.glob(results_file):