Mask_RCNN VS openpose

The most widely used algorithms for classical feature detection today are "whatever opencv implements"

In terms of tech that's advancing at the moment? https://co-tracker.github.io/ if you want to track individual points, https://github.com/matterport/Mask_RCNN and its descendents if you want to detect, say, the cover of a book.

Mask R-CNN

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- Mask RCNN https://github.com/matterport/Mask_RCNN (open source, so also not Palantir's)

pip install git+https://github.com/matterport/Mask_RCNN

It is important to realize that to do its masking procedures, Hent-AI uses the Mask RCNN (MRCNN) package from Matterport. The problem with this version of MRCNN is that it is not compatible with Tensorflow 2.X versions, essentially limiting Hent-AI compatibility to strict Tensorflow 1.X versions. Since Tensorflow 1.15 is the last of the Tensorflow 1.X versions and uses CUDA 10.0, which supports a maximum compute capability of 7.5, this means that the last NVIDIA GPU series that is compatible with the original Hent-AI implementation is the RTX 2000 series. This is, of course, not optimal since it means that RTX 3000 series and later GPUs cannot be used despite their significant computing power and high VRAM.

I read that it could bethe problem with scipy version (https://github.com/matterport/Mask_RCNN/issues/2122) so I downgraded it, I also tried to modify shift = np.array([0, 0, 1., 1.]) in utils.py but nothing helped.

I am assuming you did a pip install of this github repository, or did you run pip install mrcnn. The mrcnn package on pypi is just an example package and doesn't have any useful functionality. In addition, where did you get the code from that you are trying to run, from someone else or did you write it yourself? Reason I am asking is because the import error is to be expected since there indeed is no InferenceConfig class defined in mrcnn.visualize.

Hello AI learners, check out my own development of Mask-RCNN supporting Tensorflow2.7.0 and Keras2.8.0. This is an edit of MRCNN which supports Tensoflow1.0, only.

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