update README.md for demo.py

README.md

@@ -206,6 +206,15 @@ python -m torch.distributed.launch \
 ```
 
 
+### Visualize Detection Results
+We perform `demo.py`, which is a minimal implementation that allows users to visualize model's detection predictions. It performs detection on images inside the `./images` folder, and stores detection results visualizations on that folder. Taking <b>SAM-DETR-R50 w/ SMCA (50 epochs)</b> for example, simply run:
+```shell
+python demo.py \                       # do NOT use distributed mode
+    --batch_size 1 \
+    --smca \
+    --epochs 50 \                      # you need to set this correct. See models/fast_detr.py L50-79 for details.
+    --resume <path/to/checkpoint.pth>  # trained model weights
+```
 
 
 

demo.py

@@ -26,7 +26,7 @@ def get_args_parser():
     parser.add_argument('--lr_backbone', default=1e-5, type=float)
     parser.add_argument('--lr_linear_proj_names', default=[], type=str, nargs='+')
     parser.add_argument('--lr_linear_proj_mult', default=0.1, type=float)
-    parser.add_argument('--batch_size', default=2, type=int)
+    parser.add_argument('--batch_size', default=1, type=int)
     parser.add_argument('--weight_decay', default=1e-4, type=float)
     parser.add_argument('--epochs', default=50, type=int)
     parser.add_argument('--lr_drop', default=40, type=int)
@@ -99,6 +99,7 @@ def get_args_parser():
 
 
 def main(args):
+
     utils.init_distributed_mode(args)
 
     if args.frozen_weights is not None: