tensorflow_Realtime_Multi-Person_Pose_Estimation
evopose2d
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| tensorflow_Realtime_Multi-Person_Pose_Estimation | evopose2d | |
|---|---|---|
| 1 | 1 | |
| 212 | 82 | |
| - | - | |
| 0.0 | 0.0 | |
| over 1 year ago | over 2 years ago | |
| Jupyter Notebook | Python | |
| GNU General Public License v3.0 or later | MIT License |
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tensorflow_Realtime_Multi-Person_Pose_Estimation
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[Help] Multiple Keypoints Estimation
I've seen this kind of repo too : https://github.com/michalfaber/tensorflow_Realtime_Multi-Person_Pose_Estimation
evopose2d
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Is there an easy way to add pose estimation into a sequential tensorflow model?
You could try EvoPose2D. It uses the TF2 Keras API. It outputs heatmaps, though, so your second network could either work with the heatmaps directly or you could try converting the heatmaps to x,y coordinates by implementing a soft argmax.
What are some alternatives?
openpifpaf - Official implementation of "OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association" in PyTorch.
posenet-python - A Python port of Google TensorFlow.js PoseNet (Real-time Human Pose Estimation)
LoFTR - Code for "LoFTR: Detector-Free Local Feature Matching with Transformers", CVPR 2021, T-PAMI 2022
metrabs - Estimate absolute 3D human poses from RGB images.
PeekingDuck - A modular framework built to simplify Computer Vision inference workloads.
lightweight-human-pose-estimation.pytorch - Fast and accurate human pose estimation in PyTorch. Contains implementation of "Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose" paper.
PoseEstimationForMobile - :dancer: Real-time single person pose estimation for Android and iOS.
DECIMER-Image_Transformer - DECIMER: Deep Learning for Chemical Image Recognition using Efficient-Net V2 + Transformer
Single-Stage-Multi-person-Pose-Machines - A tensorlfow implementation about arxiv paper "Single-Stage Multi-Person Pose Machines" (SPM)
pytorch-openpose - pytorch implementation of openpose including Hand and Body Pose Estimation.
Human-pose-estimation - A quick tutorial on multi-pose estimation with OpenCV, Tensorflow and MoveNet lightning.