[Refactor] Add metafile (#2135)

open-mmlab · Apr 6, 2023 · cda64e8 · cda64e8
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diff --git a/configs/animal_2d_keypoint/rtmpose/ap10k/rtmpose_ap10k.yml b/configs/animal_2d_keypoint/rtmpose/ap10k/rtmpose_ap10k.yml
@@ -0,0 +1,18 @@
+Models:
+- Config: configs/animal_2d_keypoint/rtmpose/ap10k/rtmpose-m_8xb64-210e_ap10k-256x256.py
+  In Collection: RTMPose
+  Metadata:
+    Architecture:
+    - RTMPose
+    Training Data: AP-10K
+  Name: rtmpose-m_8xb64-210e_ap10k-256x256
+  Results:
+  - Dataset: AP-10K
+    Metrics:
+      AP: 0.722
+      AP@0.5: 0.939
+      AP@0.75: 0.788
+      AP (L): 0.728
+      AP (M): 0.569
+    Task: Animal 2D Keypoint
+  Weights: https://download.openmmlab.com/mmpose/v1/projects/rtmpose/rtmpose-m_simcc-ap10k_pt-aic-coco_210e-256x256-7a041aa1_20230206.pth
diff --git a/configs/animal_2d_keypoint/topdown_heatmap/animalpose/hrnet_animalpose.yml b/configs/animal_2d_keypoint/topdown_heatmap/animalpose/hrnet_animalpose.yml
@@ -0,0 +1,34 @@
+Models:
+- Config: configs/animal_2d_keypoint/topdown_heatmap/animalpose/td-hm_hrnet-w32_8xb64-210e_animalpose-256x256.py
+  In Collection: HRNet
+  Metadata:
+    Architecture: &id001
+    - HRNet
+    Training Data: Animal-Pose
+  Name: td-hm_hrnet-w32_8xb64-210e_animalpose-256x256
+  Results:
+  - Dataset: Animal-Pose
+    Metrics:
+      AP: 0.740
+      AP@0.5: 0.959
+      AP@0.75: 0.833
+      AR: 0.780
+      AR@0.5: 0.965
+    Task: Animal 2D Keypoint
+  Weights: https://download.openmmlab.com/mmpose/animal/hrnet/hrnet_w32_animalpose_256x256-1aa7f075_20210426.pth
+- Config: configs/animal_2d_keypoint/topdown_heatmap/animalpose/td-hm_hrnet-w48_8xb64-210e_animalpose-256x256.py
+  In Collection: HRNet
+  Metadata:
+    Architecture: *id001
+    Training Data: Animal-Pose
+  Name: td-hm_hrnet-w48_8xb64-210e_animalpose-256x256
+  Results:
+  - Dataset: Animal-Pose
+    Metrics:
+      AP: 0.738
+      AP@0.5: 0.958
+      AP@0.75: 0.831
+      AR: 0.778
+      AR@0.5: 0.962
+    Task: Animal 2D Keypoint
+  Weights: https://download.openmmlab.com/mmpose/animal/hrnet/hrnet_w48_animalpose_256x256-34644726_20210426.pth
diff --git a/configs/animal_2d_keypoint/topdown_heatmap/animalpose/resnet_animalpose.yml b/configs/animal_2d_keypoint/topdown_heatmap/animalpose/resnet_animalpose.yml
@@ -0,0 +1,51 @@
+Models:
+- Config: configs/animal_2d_keypoint/topdown_heatmap/animalpose/td-hm_res50_8xb64-210e_animalpose-256x256.py
+  In Collection: SimpleBaseline2D
+  Metadata:
+    Architecture: &id001
+    - SimpleBaseline2D
+    - ResNet
+    Training Data: Animal-Pose
+  Name: td-hm_res50_8xb64-210e_animalpose-256x256
+  Results:
+  - Dataset: Animal-Pose
+    Metrics:
+      AP: 0.691
+      AP@0.5: 0.947
+      AP@0.75: 0.770
+      AR: 0.736
+      AR@0.5: 0.955
+    Task: Animal 2D Keypoint
+  Weights: https://download.openmmlab.com/mmpose/animal/resnet/res50_animalpose_256x256-e1f30bff_20210426.pth
+- Config: configs/animal_2d_keypoint/topdown_heatmap/animalpose/td-hm_res101_8xb64-210e_animalpose-256x256.py
+  In Collection: SimpleBaseline2D
+  Metadata:
+    Architecture: *id001
+    Training Data: Animal-Pose
+  Name: td-hm_res101_8xb64-210e_animalpose-256x256
+  Results:
+  - Dataset: Animal-Pose
+    Metrics:
+      AP: 0.696
+      AP@0.5: 0.948
+      AP@0.75: 0.774
+      AR: 0.736
+      AR@0.5: 0.951
+    Task: Animal 2D Keypoint
+  Weights: https://download.openmmlab.com/mmpose/animal/resnet/res101_animalpose_256x256-85563f4a_20210426.pth
+- Config: configs/animal_2d_keypoint/topdown_heatmap/animalpose/td-hm_res152_8xb32-210e_animalpose-256x256.py
+  In Collection: SimpleBaseline2D
+  Metadata:
+    Architecture: *id001
+    Training Data: Animal-Pose
+  Name: td-hm_res152_8xb32-210e_animalpose-256x256
+  Results:
+  - Dataset: Animal-Pose
+    Metrics:
+      AP: 0.704
+      AP@0.5: 0.938
+      AP@0.75: 0.786
+      AR: 0.748
+      AR@0.5: 0.946
+    Task: Animal 2D Keypoint
+  Weights: https://download.openmmlab.com/mmpose/animal/resnet/res152_animalpose_256x256-a0a7506c_20210426.pth
diff --git a/configs/animal_2d_keypoint/topdown_heatmap/ap10k/cspnext_udp_ap10k.yml b/configs/animal_2d_keypoint/topdown_heatmap/ap10k/cspnext_udp_ap10k.yml
@@ -0,0 +1,19 @@
+Models:
+- Config: configs/animal_2d_keypoint/topdown_heatmap/ap10k/cspnext-m_udp_8xb64-210e_ap10k-256x256.py
+  In Collection: UDP
+  Metadata:
+    Architecture: &id001
+    - UDP
+    - HRNet
+    Training Data: AP-10K
+  Name: cspnext-m_udp_8xb64-210e_ap10k-256x256
+  Results:
+  - Dataset: AP-10K
+    Metrics:
+      AP: 0.703
+      AP@0.5: 0.944
+      AP@0.75: 0.776
+      AP (L): 0.71
+      AP (M): 0.513
+    Task: Animal 2D Keypoint
+  Weights: https://download.openmmlab.com/mmpose/v1/projects/rtmpose/rtmpose-m_udp-ap10k_pt-in1k_210e-256x256-1f2d947a_20230123.pth
diff --git a/configs/animal_2d_keypoint/topdown_heatmap/ap10k/hrnet_ap10k.yml b/configs/animal_2d_keypoint/topdown_heatmap/ap10k/hrnet_ap10k.yml
@@ -0,0 +1,34 @@
+Models:
+- Config: configs/animal_2d_keypoint/topdown_heatmap/ap10k/td-hm_hrnet-w32_8xb64-210e_ap10k-256x256.py
+  In Collection: HRNet
+  Metadata:
+    Architecture: &id001
+    - HRNet
+    Training Data: AP-10K
+  Name: td-hm_hrnet-w32_8xb64-210e_ap10k-256x256
+  Results:
+  - Dataset: AP-10K
+    Metrics:
+      AP: 0.722
+      AP@0.5: 0.935
+      AP@0.75: 0.789
+      AP (L): 0.729
+      AP (M): 0.557
+    Task: Animal 2D Keypoint
+  Weights: https://download.openmmlab.com/mmpose/animal/hrnet/hrnet_w32_ap10k_256x256-18aac840_20211029.pth
+- Config: configs/animal_2d_keypoint/topdown_heatmap/ap10k/td-hm_hrnet-w48_8xb64-210e_ap10k-256x256.py
+  In Collection: HRNet
+  Metadata:
+    Architecture: *id001
+    Training Data: AP-10K
+  Name: td-hm_hrnet-w48_8xb64-210e_ap10k-256x256
+  Results:
+  - Dataset: AP-10K
+    Metrics:
+      AP: 0.728
+      AP@0.5: 0.936
+      AP@0.75: 0.802
+      AP (L): 0.735
+      AP (M): 0.577
+    Task: Animal 2D Keypoint
+  Weights: https://download.openmmlab.com/mmpose/animal/hrnet/hrnet_w48_ap10k_256x256-d95ab412_20211029.pth
diff --git a/configs/animal_2d_keypoint/topdown_heatmap/ap10k/resnet_ap10k.yml b/configs/animal_2d_keypoint/topdown_heatmap/ap10k/resnet_ap10k.yml
@@ -1,16 +1,11 @@
-Collections:
-- Name: SimpleBaseline2D
-  Paper:
-    Title: Simple baselines for human pose estimation and tracking
-    URL: http://openaccess.thecvf.com/content_ECCV_2018/html/Bin_Xiao_Simple_Baselines_for_ECCV_2018_paper.html
-  README: https://github.com/open-mmlab/mmpose/blob/master/docs/en/papers/algorithms/simplebaseline2d.md
 Models:
 - Config: configs/animal_2d_keypoint/topdown_heatmap/ap10k/td-hm_res50_8xb64-210e_ap10k-256x256.py
   In Collection: SimpleBaseline2D
   Alias: animal
   Metadata:
     Architecture: &id001
     - SimpleBaseline2D
+    - ResNet
     Training Data: AP-10K
   Name: td-hm_res50_8xb64-210e_ap10k-256x256
   Results:
@@ -19,8 +14,8 @@ Models:
       AP: 0.680
       AP@0.5: 0.926
       AP@0.75: 0.738
-      APL: 0.687
-      APM: 0.552
+      AP (L): 0.687
+      AP (M): 0.552
     Task: Animal 2D Keypoint
   Weights: https://download.openmmlab.com/mmpose/animal/resnet/res50_ap10k_256x256-35760eb8_20211029.pth
 - Config: configs/animal_2d_keypoint/topdown_heatmap/ap10k/td-hm_res101_8xb64-210e_ap10k-256x256.py
@@ -35,7 +30,7 @@ Models:
       AP: 0.681
       AP@0.5: 0.921
       AP@0.75: 0.751
-      APL: 0.690
-      APM: 0.545
+      AP (L): 0.690
+      AP (M): 0.545
     Task: Animal 2D Keypoint
   Weights: https://download.openmmlab.com/mmpose/animal/resnet/res101_ap10k_256x256-9edfafb9_20211029.pth
diff --git a/configs/animal_2d_keypoint/topdown_heatmap/locust/resnet_locust.yml b/configs/animal_2d_keypoint/topdown_heatmap/locust/resnet_locust.yml
@@ -0,0 +1,45 @@
+Models:
+- Config: configs/animal_2d_keypoint/topdown_heatmap/locust/td-hm_res50_8xb64-210e_locust-160x160.py
+  In Collection: SimpleBaseline2D
+  Metadata:
+    Architecture: &id001
+    - SimpleBaseline2D
+    - ResNet
+    Training Data: Desert Locust
+  Name: td-hm_res50_8xb64-210e_locust-160x160
+  Results:
+  - Dataset: Desert Locust
+    Metrics:
+      AUC: 0.9
+      EPE: 2.27
+      PCK@0.2: 1
+    Task: Animal 2D Keypoint
+  Weights: https://download.openmmlab.com/mmpose/animal/resnet/res50_locust_160x160-9efca22b_20210407.pth
+- Config: configs/animal_2d_keypoint/topdown_heatmap/locust/td-hm_res101_8xb64-210e_locust-160x160.py
+  In Collection: SimpleBaseline2D
+  Metadata:
+    Architecture: *id001
+    Training Data: Desert Locust
+  Name: td-hm_res101_8xb64-210e_locust-160x160
+  Results:
+  - Dataset: Desert Locust
+    Metrics:
+      AUC: 0.907
+      EPE: 2.03
+      PCK@0.2: 1
+    Task: Animal 2D Keypoint
+  Weights: https://download.openmmlab.com/mmpose/animal/resnet/res101_locust_160x160-d77986b3_20210407.pth
+- Config: configs/animal_2d_keypoint/topdown_heatmap/locust/td-hm_res152_8xb32-210e_locust-160x160.py
+  In Collection: SimpleBaseline2D
+  Metadata:
+    Architecture: *id001
+    Training Data: Desert Locust
+  Name: td-hm_res152_8xb32-210e_locust-160x160
+  Results:
+  - Dataset: Desert Locust
+    Metrics:
+      AUC: 0.925
+      EPE: 1.49
+      PCK@0.2: 1.0
+    Task: Animal 2D Keypoint
+  Weights: https://download.openmmlab.com/mmpose/animal/resnet/res152_locust_160x160-4ea9b372_20210407.pth
diff --git a/configs/animal_2d_keypoint/topdown_heatmap/zebra/resnet_zebra.yml b/configs/animal_2d_keypoint/topdown_heatmap/zebra/resnet_zebra.yml
@@ -0,0 +1,45 @@
+Models:
+- Config: configs/animal_2d_keypoint/topdown_heatmap/zebra/td-hm_res50_8xb64-210e_zebra-160x160.py
+  In Collection: SimpleBaseline2D
+  Metadata:
+    Architecture: &id001
+    - SimpleBaseline2D
+    - ResNet
+    Training Data: "Gr\xE9vy\u2019s Zebra"
+  Name: td-hm_res50_8xb64-210e_zebra-160x160
+  Results:
+  - Dataset: "Gr\xE9vy\u2019s Zebra"
+    Metrics:
+      AUC: 0.914
+      EPE: 1.87
+      PCK@0.2: 1.0
+    Task: Animal 2D Keypoint
+  Weights: https://download.openmmlab.com/mmpose/animal/resnet/res50_zebra_160x160-5a104833_20210407.pth
+- Config: configs/animal_2d_keypoint/topdown_heatmap/zebra/td-hm_res101_8xb64-210e_zebra-160x160.py
+  In Collection: SimpleBaseline2D
+  Metadata:
+    Architecture: *id001
+    Training Data: "Gr\xE9vy\u2019s Zebra"
+  Name: td-hm_res101_8xb64-210e_zebra-160x160
+  Results:
+  - Dataset: "Gr\xE9vy\u2019s Zebra"
+    Metrics:
+      AUC: 0.915
+      EPE: 1.83
+      PCK@0.2: 1.0
+    Task: Animal 2D Keypoint
+  Weights: https://download.openmmlab.com/mmpose/animal/resnet/res101_zebra_160x160-e8cb2010_20210407.pth
+- Config: configs/animal_2d_keypoint/topdown_heatmap/zebra/td-hm_res152_8xb32-210e_zebra-160x160.py
+  In Collection: SimpleBaseline2D
+  Metadata:
+    Architecture: *id001
+    Training Data: "Gr\xE9vy\u2019s Zebra"
+  Name: td-hm_res152_8xb32-210e_zebra-160x160
+  Results:
+  - Dataset: "Gr\xE9vy\u2019s Zebra"
+    Metrics:
+      AUC: 0.921
+      EPE: 1.67
+      PCK@0.2: 1.0
+    Task: Animal 2D Keypoint
+  Weights: https://download.openmmlab.com/mmpose/animal/resnet/res152_zebra_160x160-05de71dd_20210407.pth
diff --git a/configs/body_2d_keypoint/cid/coco/hrnet_coco.yml b/configs/body_2d_keypoint/cid/coco/hrnet_coco.yml
@@ -0,0 +1,41 @@
+Collections:
+- Name: CID
+  Paper:
+    Title: Contextual Instance Decoupling for Robust Multi-Person Pose Estimation
+    URL: https://openaccess.thecvf.com/content/CVPR2022/html/Wang_Contextual_Instance_Decoupling_for_Robust_Multi-Person_Pose_Estimation_CVPR_2022_paper.html
+  README: https://github.com/open-mmlab/mmpose/blob/main/docs/src/papers/algorithms/cid.md
+Models:
+- Config: configs/body_2d_keypoint/cid/coco/cid_hrnet-w32_8xb20-140e_coco-512x512.py
+  In Collection: CID
+  Metadata:
+    Architecture: &id001
+    - CID
+    - HRNet
+    Training Data: COCO
+  Name: cid_hrnet-w32_8xb20-140e_coco-512x512
+  Results:
+  - Dataset: COCO
+    Metrics:
+      AP: 0.704
+      AP@0.5: 0.894
+      AP@0.75: 0.775
+      AR: 0.753
+      AR@0.5: 0.928
+    Task: Body 2D Keypoint
+  Weights: https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/cid/coco/cid_hrnet-w32_8xb20-140e_coco-512x512_42b7e6e6-20230207.pth
+- Config: configs/body_2d_keypoint/cid/coco/cid_hrnet-w48_8xb20-140e_coco-512x512.py
+  In Collection: CID
+  Metadata:
+    Architecture: *id001
+    Training Data: COCO
+  Name: cid_hrnet-w48_8xb20-140e_coco-512x512
+  Results:
+  - Dataset: COCO
+    Metrics:
+      AP: 0.715
+      AP@0.5: 0.9
+      AP@0.75: 0.782
+      AR: 0.765
+      AR@0.5: 0.935
+    Task: Body 2D Keypoint
+  Weights: https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/cid/coco/cid_hrnet-w48_8xb20-140e_coco-512x512_a36c3ecf-20230207.pth
diff --git a/configs/body_2d_keypoint/dekr/coco/hrnet_coco.yml b/configs/body_2d_keypoint/dekr/coco/hrnet_coco.yml
@@ -0,0 +1,41 @@
+Collections:
+- Name: DEKR
+  Paper:
+    Title: Bottom-up human pose estimation via disentangled keypoint regression
+    URL: https://arxiv.org/abs/2104.02300
+  README: https://github.com/open-mmlab/mmpose/blob/main/docs/src/papers/algorithms/dekr.md
+Models:
+- Config: configs/body_2d_keypoint/dekr/coco/dekr_hrnet-w32_8xb10-140e_coco-512x512.py
+  In Collection: DEKR
+  Metadata:
+    Architecture: &id001
+    - DEKR
+    - HRNet
+    Training Data: COCO
+  Name: dekr_hrnet-w32_8xb10-140e_coco-512x512
+  Results:
+  - Dataset: COCO
+    Metrics:
+      AP: 0.686
+      AP@0.5: 0.868
+      AP@0.75: 0.750
+      AR: 0.735
+      AR@0.5: 0.898
+    Task: Body 2D Keypoint
+  Weights: https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/dekr/coco/dekr_hrnet-w32_8xb10-140e_coco-512x512_ac7c17bf-20221228.pth
+- Config: configs/body_2d_keypoint/dekr/coco/dekr_hrnet-w48_8xb10-140e_coco-640x640.py
+  In Collection: DEKR
+  Metadata:
+    Architecture: *id001
+    Training Data: COCO
+  Name: dekr_hrnet-w48_8xb10-140e_coco-640x640
+  Results:
+  - Dataset: COCO
+    Metrics:
+      AP: 0.714
+      AP@0.5: 0.883
+      AP@0.75: 0.777
+      AR: 0.762
+      AR@0.5: 0.915
+    Task: Body 2D Keypoint
+  Weights: https://download.openmmlab.com/mmpose/v1/body_2d_keypoint/dekr/coco/dekr_hrnet-w48_8xb10-140e_coco-640x640_74796c32-20230124.pth