add : out_dit for fig as args

image_ref/config.py

@@ -16,6 +16,7 @@ def load_args_contrastive():
     parser.add_argument('--dataset_train_dir', type=str, default='data/processed_data/npy_image/data_training_contrastive')
     parser.add_argument('--dataset_val_dir', type=str, default='data/processed_data/npy_image/data_test_contrastive')
     parser.add_argument('--dataset_test_dir', type=str, default=None)
+    parser.add_argument('--base_out', type=str, default='output/baseline')
     parser.add_argument('--dataset_ref_dir', type=str, default='image_ref/img_ref')
     parser.add_argument('--output', type=str, default='output/out_contrastive.csv')
     parser.add_argument('--save_path', type=str, default='output/best_model_constrastive.pt')

image_ref/main.py

@@ -174,13 +174,11 @@ def run_duo(args):
     # load and evaluate best model
     load_model(model, args.save_path)
     if args.args.dataset_test_dir is not None :
-        make_prediction_duo(model, data_test_batch,
-                            'output/confusion_matrix_contractive_{}_bis_test.png'.format(args.positive_prop),
-                            'output/confidence_matrix_contractive_{}_bis_test.png'.format(args.positive_prop))
+        make_prediction_duo(model, data_test_batch,args.base_out+'_confusion_matrix_test.png',
+                            args.base_out+'confidence_matrix_.png')
 
-    make_prediction_duo(model, data_val_batch,
-                            'output/confusion_matrix_contractive_{}_bis_val.png'.format(args.positive_prop),
-                            'output/confidence_matrix_contractive_{}_bis_val.png'.format(args.positive_prop))
+    make_prediction_duo(model, data_val_batch,args.base_out+'_confusion_matrix_val.png',
+                        args.base_out+'_confusion_matrix_val.png')
 
     if args.wandb is not None:
         wdb.finish()