modify yoloxpose test settings

open-mmlab · Sep 19, 2023 · e63cd04 · e63cd04
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Showing 7 changed files with 27 additions and 27 deletions.
diff --git a/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_coco.md b/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_coco.md
@@ -53,7 +53,7 @@ Results on COCO val2017 with detector having human AP of 56.4 on COCO val2017 da
 
 | Arch                                          | Input Size |  AP   | AP<sup>50</sup> | AP<sup>75</sup> |  AR   | AR<sup>50</sup> |                     ckpt                      |                      log                      |
 | :-------------------------------------------- | :--------: | :---: | :-------------: | :-------------: | :---: | :-------------: | :-------------------------------------------: | :-------------------------------------------: |
-| [yoloxpose_tiny](/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_tiny_4xb64-300e_coco-416.py) |  416x416   | 0.527 |      0.794      |      0.557      | 0.577 |      0.843      | [ckpt](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_tiny_4xb64-300e_coco-416-76eb44ca_20230829.pth) | [log](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_tiny_4xb64-300e_coco-416-20230829.json) |
-| [yoloxpose_s](/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_s_8xb32-300e_coco-640.py) |  640x640   | 0.642 |      0.873      |      0.702      | 0.688 |      0.912      | [ckpt](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_s_8xb32-300e_coco-640-56c79c1f_20230829.pth) | [log](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_s_8xb32-300e_coco-640-20230829.json) |
-| [yoloxpose_m](/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_m_8xb32-300e_coco-640.py) |  640x640   | 0.697 |      0.903      |      0.766      | 0.739 |      0.933      | [ckpt](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_m_8xb32-300e_coco-640-84e9a538_20230829.pth) | [log](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_m_8xb32-300e_coco-640-20230829.json) |
-| [yoloxpose_l](/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_l_8xb32-300e_coco-640.py) |  640x640   | 0.714 |      0.906      |      0.785      | 0.756 |      0.934      | [ckpt](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_l_8xb32-300e_coco-640-de0f8dee_20230829.pth) | [log](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_l_8xb32-300e_coco-640-20230829.json) |
+| [yoloxpose_tiny](/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_tiny_4xb64-300e_coco-416.py) |  416x416   | 0.526 |      0.793      |      0.556      | 0.571 |      0.833      | [ckpt](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_tiny_4xb64-300e_coco-416-76eb44ca_20230829.pth) | [log](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_tiny_4xb64-300e_coco-416-20230829.json) |
+| [yoloxpose_s](/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_s_8xb32-300e_coco-640.py) |  640x640   | 0.641 |      0.872      |      0.702      | 0.682 |      0.902      | [ckpt](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_s_8xb32-300e_coco-640-56c79c1f_20230829.pth) | [log](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_s_8xb32-300e_coco-640-20230829.json) |
+| [yoloxpose_m](/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_m_8xb32-300e_coco-640.py) |  640x640   | 0.695 |      0.899      |      0.766      | 0.733 |      0.926      | [ckpt](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_m_8xb32-300e_coco-640-84e9a538_20230829.pth) | [log](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_m_8xb32-300e_coco-640-20230829.json) |
+| [yoloxpose_l](/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_l_8xb32-300e_coco-640.py) |  640x640   | 0.712 |      0.901      |      0.782      | 0.749 |      0.926      | [ckpt](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_l_8xb32-300e_coco-640-de0f8dee_20230829.pth) | [log](https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_l_8xb32-300e_coco-640-20230829.json) |
diff --git a/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_coco.yml b/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_coco.yml
@@ -15,11 +15,11 @@ Models:
   Results:
   - Dataset: COCO
     Metrics:
-      AP: 0.527
-      AP@0.5: 0.794
-      AP@0.75: 0.557
-      AR: 0.577
-      AR@0.5: 0.843
+      AP: 0.526
+      AP@0.5: 0.793
+      AP@0.75: 0.556
+      AR: 0.571
+      AR@0.5: 0.833
     Task: Body 2D Keypoint
   Weights: https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_tiny_4xb64-300e_coco-416-76eb44ca_20230829.pth
 - Config: configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_s_8xb32-300e_coco-640.py
@@ -31,11 +31,11 @@ Models:
   Results:
   - Dataset: COCO
     Metrics:
-      AP: 0.642
-      AP@0.5: 0.873
+      AP: 0.641
+      AP@0.5: 0.872
       AP@0.75: 0.702
-      AR: 0.688
-      AR@0.5: 0.912
+      AR: 0.682
+      AR@0.5: 0.902
     Task: Body 2D Keypoint
   Weights: https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_s_8xb32-300e_coco-640-56c79c1f_20230829.pth
 - Config: configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_m_8xb32-300e_coco-640.py
@@ -47,11 +47,11 @@ Models:
   Results:
   - Dataset: COCO
     Metrics:
-      AP: 0.697
-      AP@0.5: 0.903
+      AP: 0.695
+      AP@0.5: 0.899
       AP@0.75: 0.766
-      AR: 0.739
-      AR@0.5: 0.933
+      AR: 0.733
+      AR@0.5: 0.926
     Task: Body 2D Keypoint
   Weights: https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_m_8xb32-300e_coco-640-84e9a538_20230829.pth
 - Config: configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_l_8xb32-300e_coco-640.py
@@ -63,10 +63,10 @@ Models:
   Results:
   - Dataset: COCO
     Metrics:
-      AP: 0.714
-      AP@0.5: 0.906
-      AP@0.75: 0.785
-      AR: 0.756
-      AR@0.5: 0.934
+      AP: 0.712
+      AP@0.5: 0.901
+      AP@0.75: 0.782
+      AR: 0.749
+      AR@0.5: 0.926
     Task: Body 2D Keypoint
   Weights: https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/yolox_pose/yoloxpose_l_8xb32-300e_coco-640-de0f8dee_20230829.pth
diff --git a/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_l_8xb32-300e_coco-640.py b/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_l_8xb32-300e_coco-640.py
@@ -1,4 +1,4 @@
-_base_ = './yolopose_s_8xb32-300e_coco-640.py'
+_base_ = './yoloxpose_s_8xb32-300e_coco-640.py'
 
 widen_factor = 1
 deepen_factor = 1

diff --git a/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_m_8xb32-300e_coco-640.py b/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_m_8xb32-300e_coco-640.py
@@ -1,4 +1,4 @@
-_base_ = './yolopose_s_8xb32-300e_coco-640.py'
+_base_ = './yoloxpose_s_8xb32-300e_coco-640.py'
 
 widen_factor = 0.75
 deepen_factor = 0.67

diff --git a/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_s_8xb32-300e_coco-640.py b/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_s_8xb32-300e_coco-640.py
@@ -132,7 +132,7 @@
         loss_bbox_aux=dict(type='L1Loss', reduction='sum', loss_weight=1.0),
     ),
     test_cfg=dict(
-        score_thr=0.001,
+        score_thr=0.01,
         nms_thr=0.65,
     ))
 

diff --git a/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_tiny_4xb64-300e_coco-416.py b/configs/body_2d_keypoint/yoloxpose/coco/yoloxpose_tiny_4xb64-300e_coco-416.py
@@ -1,4 +1,4 @@
-_base_ = './yolopose_s_8xb32-300e_coco-640.py'
+_base_ = './yoloxpose_s_8xb32-300e_coco-640.py'
 
 # model settings
 widen_factor = 0.375

diff --git a/mmpose/evaluation/functional/nms.py b/mmpose/evaluation/functional/nms.py
@@ -356,7 +356,7 @@ def nms_torch(bboxes: Tensor,
         idx, indices = indices[0], indices[1:]
         bbox = bboxes[idx]
         ious = iou_calculator(bbox, bboxes[indices])
-        close_indices = torch.where(ious > threshold)[0]
+        close_indices = torch.where(ious > threshold)[1]
         keep_indices = torch.ones_like(indices, dtype=torch.bool)
         keep_indices[close_indices] = 0
         groups.append(torch.cat((idx[None], indices[close_indices])))