Update app_util.py

app_util.py

@@ -34,14 +34,14 @@ def parse_args() -> argparse.Namespace:
                         help="Type of positional embedding to use on top of the image features")
     parser.add_argument('--position_embedding_scale', default=2 * np.pi, type=float,
                         help="position / size * scale")
-    parser.add_argument('--num_feature_levels', default=5, type=int, help='number of feature levels')
+    parser.add_argument('--num_feature_levels', default=4, type=int, help='number of feature levels')
 
     # * Transformer
     parser.add_argument('--enc_layers', default=6, type=int,
                         help="Number of encoding layers in the transformer")
     parser.add_argument('--dec_layers', default=6, type=int,
                         help="Number of decoding layers in the transformer")
-    parser.add_argument('--dim_feedforward', default=2048, type=int,
+    parser.add_argument('--dim_feedforward', default=1024, type=int,
                         help="Intermediate size of the feedforward layers in the transformer blocks")
     parser.add_argument('--hidden_dim', default=256, type=int,
                         help="Size of the embeddings (dimension of the transformer)")
@@ -49,7 +49,7 @@ def parse_args() -> argparse.Namespace:
                         help="Dropout applied in the transformer")
     parser.add_argument('--nheads', default=8, type=int,
                         help="Number of attention heads inside the transformer's attentions")
-    parser.add_argument('--num_queries', default=900, type=int,
+    parser.add_argument('--num_queries', default=300, type=int,
                         help="Number of query slots")
     parser.add_argument('--dec_n_points', default=4, type=int)
     parser.add_argument('--enc_n_points', default=4, type=int)
@@ -118,7 +118,7 @@ class ContextDetDemo():
         args.resume = resume
 
         args.device = 'cuda' if torch.cuda.is_available() else 'cpu'
-        num_classes = 2
+        num_classes = 1
         device = torch.device(args.device)
 
         backbone = build_backbone(args)