Update README.md

README.md

@@ -65,6 +65,8 @@ You will get the results:
  Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.83868
 ```
 
+To measure accuracy, download [COCO-annotations for Pycocotools](http://images.cocodataset.org/annotations/annotations_trainval2017.zip).
+
 ## Training
 
 ```
@@ -81,6 +83,9 @@ python -m torch.distributed.launch --nproc_per_node 4 --master_port 9527 train.p
 
 The training code and instruction of p6 models will release soon.
 
+
+Download MS COCO dataset images ([train](http://images.cocodataset.org/zips/train2017.zip), [val](http://images.cocodataset.org/zips/val2017.zip), [test](http://images.cocodataset.org/zips/test2017.zip)) and [labels](https://github.com/WongKinYiu/yolov7/releases/download/v0.1/coco2017labels-segments.zip). If you have previously used a different version of YOLO, we strongly recommend that you delete `train2017.cache` and `val2017.cache` files, and redownload [labels](https://github.com/WongKinYiu/yolov7/releases/download/v0.1/coco2017labels-segments.zip) 
+
 ## Re-parameterization
 
 The re-parameterization code and instruction will release soon.