修改mmpose的readme

openmmlab_test/mmpose-0.28.1/train.md

@@ -33,7 +33,7 @@ pip3 install -e .
 ## ResNet50-Bottom-Up测试
 ### 单卡测试（单精度）
 ```python
-./sing_test.sh configs/body/2d_kpt_sview_rgb_img/res50_coco_256x192_dummy.py
+./sing_test.sh configs/body/2d_kpt_sview_rgb_img/topdown_heatmap/coco/res50_coco_256x192.py
 ```
 #### 参数说明
 configs/body/2d_kpt_sview_rgb_img/res50_coco_256x192_dummy.py 中batch_size=samples_per_gpu*卡数,性能计算方法：batch_size/time
@@ -44,7 +44,7 @@ configs/body/2d_kpt_sview_rgb_img/res50_coco_256x192_dummy.py 中batch_size=samp
 1.pytorch单机多卡训练
 
 ```python
-./tools/dist_train.sh configs/body/2d_kpt_sview_rgb_img/res50_coco_256x192_dummy.py $GPUS
+./tools/dist_train.sh configs/body/2d_kpt_sview_rgb_img/topdown_heatmap/coco/res50_coco_256x192.py $GPUS
 ```
 
 #### 多机多卡训练
@@ -69,6 +69,6 @@ NODES=$NNODES NODE_RANK=$NODE_RANK PORT=$PORT MASTER_ADDR=$MASTER_ADDR sh tools/
 
 | 模型               | configs                                                      |
 | ------------------ | ------------------------------------------------------------ |
-| ResNet50-Top-Down  | configs/body/2d_kpt_sview_rgb_img/res50_coco_256x192_dummy.py |
+| ResNet50-Top-Down  | configs/body/2d_kpt_sview_rgb_img/topdown_heatmap/coco/res50_coco_256x192.py |
 | HrNet-Top-Down     | configs/body/2d_kpt_sview_rgb_img/topdown_heatmap/coco/hrnet_w32_coco_256x192.py |
 | ResNet50-Bottom-Up | configs/body/2d_kpt_sview_rgb_img/associative_embedding/coco/hrnet_w32_coco_512x512.py |