update

README.md

@@ -13,7 +13,7 @@ attributed to the complication in matching object queries to encoded image featu
 in DETR's decoder cross-attention modules.
 
 <div align=center>  
-<img src='.assets/matching_complication.jpg' width="62.5%">
+<img src='.assets/matching_complication.jpg' width="68%">
 </div>
 
 Motivated by this observation, in our paper, we propose SAM-DETR, a
@@ -35,15 +35,15 @@ reference box for each object query, whose center location is used to generate
 corresponding position embeddings.
 
 <div align=center>  
-<img src='.assets/decoder_layer.jpg' width="72.5%">
+<img src='.assets/decoder_layer.jpg' width="86.5%">
 </div>
 
 The figure below illustrates the architecture of the appended "Semantics Aligner", which
 aligns the semantics of "encoded image features" and "object queries" by resampling features 
 from multiple salient points as new object queries.
 
 <div align=center>  
-<img src='.assets/semantics_aligner.jpg' width="65%">
+<img src='.assets/semantics_aligner.jpg' width="75%">
 </div>
 
 Being like a plug-and-play, our approach can be
@@ -118,7 +118,7 @@ python test.py  # unit test (should see all checking is True)
 Please download [COCO 2017 dataset](https://cocodataset.org/) and organize them as following:
 
 ```
-sam_detr_root/
+code_root/
 弩岸岸 data/
     弩岸岸 coco/
         念岸岸 train2017/
@@ -134,7 +134,6 @@ sam_detr_root/
 
 
 
-
 ## Usage
 
 ### Reproducing Paper Results