mmpose VS openpose

RTMPose-m achieves 75.8% AP on COCO with 90+ FPS on an Intel i7-11700 CPU and 430+ FPS on an NVIDIA GTX 1660 Ti GPU, and RTMPose-l achieves 67.0% AP on COCO-WholeBody with 130+ FPS.

MMPose: OpenMMLab pose estimation toolbox and benchmark.

I downloaded pytorch2onnx.py from mmPose tools. It's big, but the top half is imports and input arguments. Line 125, I hard-coded my (image) input size. I ran it on my .pth model file, and out pop'd an onnx file.

They have a specific repo called mmpose: https://github.com/open-mmlab/mmpose

I would start with mmpose. It's basically a curated list of the best models ready to go.

The [MMLab key point detection](https://github.com/open-mmlab/mmpose) is in a separate repo from detection.

One option is mmPose. They have a bunch of 2D/3D models implemented and support different skeleton structures.

This library is pretty good. It has implementations for a number of pose estimators. I think Darkpose is the best one from memory

Check out https://github.com/open-mmlab/mmpose I think they have guides for new datasets

Open Pose, a multi-person keypoint detection library for body, face, hands, and foot estimation [10], is used for posing generated characters;

OpenPose

Perhaps something like OpenPose for pose estimation?

OpenPose looks like what you're looking for, it seems to have plugins for Unity. I can't say I've used it though.

You are correct. Open Pose has two keypoints for the eyes and two more for the ears. By saying were the ears are you automatically influence the angle of the head. You can see more about it on this github page. Just scroll a tiny bit and you can see a gif of the nodes overlapped on humans

FROM nvidia/cuda:10.0-cudnn7-devel-ubuntu18.04 # https://hub.docker.com/r/nvidia/cuda ENV DEBIAN_FRONTEND=noninteractive # install the dependencies for building OpenPose RUN apt-get update && # The rest is ignored for brevity. RUN pip3 install --no-cache-dir # The rest is ignored for brevity. # install cmake, clone OpenPose and download models RUN wget https://cmake.org/files/v3.20/cmake-3.20.2-linux-x86_64.tar.gz && \ # The rest is ignored for brevity. WORKDIR /openpose/build RUN alias python=python3 && cmake -DBUILD_PYTHON=OFF -DWITH_GTK=OFF -DUSE_CUDNN=ON .. # Build OpenPose. Cudnn 8 causes memory issues this is why we are using base with CUDA 10 and Cudnn 7 # Fix for CUDA 10.0 and Cudnn 7 based on the post below. # https://github.com/CMU-Perceptual-Computing-Lab/openpose/issues/1753#issuecomment-792431838 RUN sed -ie 's/set(AMPERE "80 86")/#&/g' ../cmake/Cuda.cmake && \ sed -ie 's/set(AMPERE "80 86")/#&/g' ../3rdparty/caffe/cmake/Cuda.cmake && \ make -j`nproc` && \ make install WORKDIR /openpose

One of the best cam only libraries (no depth sensor) I've seen is openpose, I ran it through a 360 camera and it was able to track body, face, and fingers really well even with spherical distortion from the 360 cam. example 360