GitHub - open-mmlab/mmpose: OpenMMLab Pose Estimation Toolbox and Benchmark.
github.com
GitHub - open-mmlab/mmpose: OpenMMLab Pose Estimation Toolbox and Benchmark.
OpenMMLab Pose Estimation Toolbox and Benchmark. Contribute to open-mmlab/mmpose development by creating an account on GitHub.
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Atsushi Iida | AI Motion Analysis on Instagram: "強傾斜だと腰と壁の距離が空きがちになって、次のホールドに移動する時に長い距離を移動できない場合が多発してる。 下半身の筋肉を強化する必要がある。 グラフで原因が分かりやすくなって良かった！ #bouldering #boulder #climb #climbing #climber #training #trainingday #sport #climbingtraining #climbingcoach #rocklands #computervision #sportstech #sportsscience #python #AI #poseestimation #mmpose #pytorch #opencv #rtmw3d #3dpose #groundingdino #zeroshot #radarchart #performanceanalysis"
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Atsushi Iida | AI Motion Analysis on Instagram: "強傾斜だと腰と壁の距離が空きがちになって、次のホールドに移動する時に長い距離を移動できない場合が多発してる。 下半身の筋肉を強化する必要がある。 グラフで原因が分かりやすくなって良かった！ #bouldering #boulder #climb #climbing #climber #training #trainingday #sport #climbingtraining #climbingcoach #rocklands #computervision #sportstech #sportsscience #python #AI #poseestimation #mmpose #pytorch #opencv #rtmw3d #3dpose #groundingdino #zeroshot #radarchart #performanceanalysis"
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Atsushi Iida | AI Motion Analysis on Instagram: "3Dビュー機能・3D平滑化・コーチング機能追加版 Pose Estimation: RTMPose / RTMW3D (OpenMMLab/MMPose) Person Detection: RTMDet (OpenMMLab/MMDetection) Framework: PyTorch + OpenCV Climbing Analysis: —keypoint-mode climbing - Climbing-specific mode (127 keypoints, including fingertips) —show-grip-type - Display grip type (crimp, open hand, etc.) —detect-holds - Auto-detect holds on the wall —highlight-route-holds - Highlight holds matching the route color —hide-hold-boxes
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Atsushi Iida | AI Motion Analysis on Instagram: "3Dビュー機能・3D平滑化・コーチング機能追加版 Pose Estimation: RTMPose / RTMW3D (OpenMMLab/MMPose) Person Detection: RTMDet (OpenMMLab/MMDetection) Framework: PyTorch + OpenCV Climbing Analysis: —keypoint-mode climbing - Climbing-specific mode (127 keypoints, including fingertips) —show-grip-type - Display grip type (crimp, open hand, etc.) —detect-holds - Auto-detect holds on the wall —highlight-route-holds - Highlight holds matching the route color —hide-hold-boxes
Instagramoreshihon.atsushi.iida
1.1K views4 months ago
飯田 篤 on Instagram: "Pose Estimation: RTMPose (OpenMMLab/MMPose) Person Detection: RTMDet (OpenMMLab/MMDetection) Framework: PyTorch + OpenCV Climbing Analysis: —keypoint-mode climbing - Climbing-specific mode (127 keypoints, including fingertips)—show-grip-type - Display grip type (crimp, open hand, etc.)—detect-holds - Auto-detect holds on the wall—highlight-route-holds - Highlight holds matching the route color—hide-hold-boxes - Hide detection boxes (show circles only) Motion Analysis: —show-r
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飯田 篤 on Instagram: "Pose Estimation: RTMPose (OpenMMLab/MMPose) Person Detection: RTMDet (OpenMMLab/MMDetection) Framework: PyTorch + OpenCV Climbing Analysis: —keypoint-mode climbing - Climbing-specific mode (127 keypoints, including fingertips)—show-grip-type - Display grip type (crimp, open hand, etc.)—detect-holds - Auto-detect holds on the wall—highlight-route-holds - Highlight holds matching the route color—hide-hold-boxes - Hide detection boxes (show circles only) Motion Analysis: —show-r
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Instagramoreshihon.atsushi.iida
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