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18 changes: 18 additions & 0 deletions configs/animal_2d_keypoint/rtmpose/ap10k/rtmpose_ap10k.yml
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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
[email protected]: 0.939
[email protected]: 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
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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
[email protected]: 0.959
[email protected]: 0.833
AR: 0.780
[email protected]: 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
[email protected]: 0.958
[email protected]: 0.831
AR: 0.778
[email protected]: 0.962
Task: Animal 2D Keypoint
Weights: https://download.openmmlab.com/mmpose/animal/hrnet/hrnet_w48_animalpose_256x256-34644726_20210426.pth
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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
[email protected]: 0.947
[email protected]: 0.770
AR: 0.736
[email protected]: 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
[email protected]: 0.948
[email protected]: 0.774
AR: 0.736
[email protected]: 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
[email protected]: 0.938
[email protected]: 0.786
AR: 0.748
[email protected]: 0.946
Task: Animal 2D Keypoint
Weights: https://download.openmmlab.com/mmpose/animal/resnet/res152_animalpose_256x256-a0a7506c_20210426.pth
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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
[email protected]: 0.944
[email protected]: 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
34 changes: 34 additions & 0 deletions configs/animal_2d_keypoint/topdown_heatmap/ap10k/hrnet_ap10k.yml
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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
[email protected]: 0.935
[email protected]: 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
[email protected]: 0.936
[email protected]: 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
15 changes: 5 additions & 10 deletions configs/animal_2d_keypoint/topdown_heatmap/ap10k/resnet_ap10k.yml
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@@ -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:
Expand All @@ -19,8 +14,8 @@ Models:
AP: 0.680
[email protected]: 0.926
[email protected]: 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
Expand All @@ -35,7 +30,7 @@ Models:
AP: 0.681
[email protected]: 0.921
[email protected]: 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
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@@ -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
[email protected]: 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
[email protected]: 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
[email protected]: 1.0
Task: Animal 2D Keypoint
Weights: https://download.openmmlab.com/mmpose/animal/resnet/res152_locust_160x160-4ea9b372_20210407.pth
45 changes: 45 additions & 0 deletions configs/animal_2d_keypoint/topdown_heatmap/zebra/resnet_zebra.yml
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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
[email protected]: 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
[email protected]: 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
[email protected]: 1.0
Task: Animal 2D Keypoint
Weights: https://download.openmmlab.com/mmpose/animal/resnet/res152_zebra_160x160-05de71dd_20210407.pth
41 changes: 41 additions & 0 deletions configs/body_2d_keypoint/cid/coco/hrnet_coco.yml
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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
[email protected]: 0.894
[email protected]: 0.775
AR: 0.753
[email protected]: 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
[email protected]: 0.9
[email protected]: 0.782
AR: 0.765
[email protected]: 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
41 changes: 41 additions & 0 deletions configs/body_2d_keypoint/dekr/coco/hrnet_coco.yml
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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
[email protected]: 0.868
[email protected]: 0.750
AR: 0.735
[email protected]: 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
[email protected]: 0.883
[email protected]: 0.777
AR: 0.762
[email protected]: 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
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