Monocular 3D pose estimation. OpenVINO. CPU inference or iGPU (OpenCL) inference.

Related tags

Deep Learningpythoncppopenclonnxopenvino
Overview

human-pose-estimation-3d-python-cpp

  • RealSenseD435 (RGB) 480x640 + CPU Corei9 45 FPS (Depth is not used)

ezgif com-gif-maker (16)

1. Run

1-1. RealSenseD435 (RGB) 480x640 + CPU Corei9 45 FPS (Depth is not used)

$ xhost +local: && \
docker run -it --rm \
-v `pwd`:/home/user/workdir \
-v /tmp/.X11-unix/:/tmp/.X11-unix:rw \
--device /dev/video0:/dev/video0:mwr \
--device /dev/video1:/dev/video1:mwr \
--device /dev/video2:/dev/video2:mwr \
--device /dev/video3:/dev/video3:mwr \
--device /dev/video4:/dev/video4:mwr \
--device /dev/video5:/dev/video5:mwr \
--net=host \
-e XDG_RUNTIME_DIR=$XDG_RUNTIME_DIR \
-e DISPLAY=$DISPLAY \
--privileged \
ghcr.io/pinto0309/openvino2tensorflow:latest
$ python3 human_pose_estimation_3d_demo.py \
--model models/openvino/FP16/human-pose-estimation-3d-0001_bgr_480x640.xml \
--device CPU \
--input 4

1-2. RealSenseD435 (RGB) 480x640 + iGPU (OpenCL)

$ xhost +local: && \
docker run -it --rm \
-v `pwd`:/home/user/workdir \
-v /tmp/.X11-unix/:/tmp/.X11-unix:rw \
--device /dev/video0:/dev/video0:mwr \
--device /dev/video1:/dev/video1:mwr \
--device /dev/video2:/dev/video2:mwr \
--device /dev/video3:/dev/video3:mwr \
--device /dev/video4:/dev/video4:mwr \
--device /dev/video5:/dev/video5:mwr \
--net=host \
-e LIBVA_DRIVER_NAME=iHD \
-e XDG_RUNTIME_DIR=$XDG_RUNTIME_DIR \
-e DISPLAY=$DISPLAY \
--privileged \
ghcr.io/pinto0309/openvino2tensorflow:latest
$ python3 human_pose_estimation_3d_demo.py \
--model models/openvino/FP16/human-pose-estimation-3d-0001_bgr_480x640.xml \
--device GPU \
--input 4

1-3. General USB Camera 480x640 + CPU

$ xhost +local: && \
docker run -it --rm \
-v `pwd`:/home/user/workdir \
-v /tmp/.X11-unix/:/tmp/.X11-unix:rw \
--device /dev/video0:/dev/video0:mwr \
--net=host \
-e XDG_RUNTIME_DIR=$XDG_RUNTIME_DIR \
-e DISPLAY=$DISPLAY \
--privileged \
ghcr.io/pinto0309/openvino2tensorflow:latest
$ python3 human_pose_estimation_3d_demo.py \
--model models/openvino/FP16/human-pose-estimation-3d-0001_bgr_480x640.xml \
--device CPU \
--input 0

2. Build

$ PYTHON_PREFIX=$(python3 -c "import sys; print(sys.prefix)") \
&& PYTHON_VERSION=$(python3 -c "import sys; print(f'{sys.version_info.major}.{sys.version_info.minor}')") \
&& PYTHON_INCLUDE_DIRS=${PYTHON_PREFIX}/include/python${PYTHON_VERSION}

$ NUMPY_INCLUDE_DIR=$(python3 -c "import numpy; print(numpy.get_include())")

$ mkdir -p pose_extractor/build && cd pose_extractor/build

$ cmake \
-DPYTHON_INCLUDE_DIRS=${PYTHON_INCLUDE_DIRS} \
-DNUMPY_INCLUDE_DIR=${NUMPY_INCLUDE_DIR} ..

$ make && cp pose_extractor.so ../.. && cd ../..

3. Reference

  1. https://github.com/openvinotoolkit/open_model_zoo/tree/2021.4.1/demos/human_pose_estimation_3d_demo/python
  2. https://docs.openvino.ai/2021.4/omz_models_model_human_pose_estimation_3d_0001.html
  3. https://github.com/PINTO0309/PINTO_model_zoo/tree/main/029_human-pose-estimation-3d-0001
Owner
Katsuya Hyodo
Hobby programmer. Intel Software Innovator Program member.
Katsuya Hyodo
GitHub Repository
Lightweight stereo matching network based on MobileNetV1 and MobileNetV2

MobileStereoNet: Towards Lightweight Deep Networks for Stereo Matching

Cognitive Systems Research Group 139 Nov 30, 2022
Confidence Propagation Cluster aims to replace NMS-based methods as a better box fusion framework in 2D/3D Object detection

CP-Cluster Confidence Propagation Cluster aims to replace NMS-based methods as a better box fusion framework in 2D/3D Object detection, Instance Segme

Yichun Shen 41 Dec 08, 2022
Official code for "Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer. ICCV2021".

Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer. ICCV2021. Introduction We proposed a novel model training paradi

Lucas 103 Dec 14, 2022
Multi-scale discriminator feature-wise loss function

Multi-Scale Discriminative Feature Loss This repository provides code for Multi-Scale Discriminative Feature (MDF) loss for image reconstruction algor

Graphics and Displays group - University of Cambridge 76 Dec 12, 2022
Code accompanying our paper Feature Learning in Infinite-Width Neural Networks

Empirical Experiments in "Feature Learning in Infinite-width Neural Networks" This repo contains code to replicate our experiments (Word2Vec, MAML) in

Edward Hu 37 Dec 14, 2022
Official implementation of "Implicit Neural Representations with Periodic Activation Functions"

Implicit Neural Representations with Periodic Activation Functions Project Page | Paper | Data Vincent Sitzmann*, Julien N. P. Martel*, Alexander W. B

Vincent Sitzmann 1.4k Jan 06, 2023
Generative Modelling of BRDF Textures from Flash Images [SIGGRAPH Asia, 2021]

Neural Material Official code repository for the paper: Generative Modelling of BRDF Textures from Flash Images [SIGGRAPH Asia, 2021] Henzler, Deschai

Philipp Henzler 80 Dec 20, 2022
GrabGpu_py: a scripts for grab gpu when gpu is free

GrabGpu_py a scripts for grab gpu when gpu is free. WaitCondition: gpu_memory

tianyuluan 3 Jun 18, 2022
一个多语言支持、易使用的 OCR 项目。An easy-to-use OCR project with multilingual support.

AgentOCR 简介 AgentOCR 是一个基于 PaddleOCR 和 ONNXRuntime 项目开发的一个使用简单、调用方便的 OCR 项目 本项目目前包含 Python Package 【AgentOCR】 和 OCR 标注软件 【AgentOCRLabeling】 使用指南 Pytho

AgentMaker 98 Nov 10, 2022
This porject is intented to build the most accurate model for predicting the porbability of loan default

Estimating-Loan-Default-Probability IBA ML2 Mid-project / Kaggle Competition This porject is intented to build the most accurate model for predicting

Adil Gahramanov 1 Jan 24, 2022
Official implementation of "OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association" in PyTorch.

openpifpaf Continuously tested on Linux, MacOS and Windows: New 2021 paper: OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Te

VITA lab at EPFL 50 Dec 29, 2022
DeLiGAN - This project is an implementation of the Generative Adversarial Network

This project is an implementation of the Generative Adversarial Network proposed in our CVPR 2017 paper - DeLiGAN : Generative Adversarial Net

Video Analytics Lab -- IISc 110 Sep 13, 2022
ICON: Implicit Clothed humans Obtained from Normals (CVPR 2022)

ICON: Implicit Clothed humans Obtained from Normals Yuliang Xiu · Jinlong Yang · Dimitrios Tzionas · Michael J. Black CVPR 2022 News 🚩 [2022/04/26] H

Yuliang Xiu 1.1k Jan 04, 2023
Code for "Multi-Time Attention Networks for Irregularly Sampled Time Series", ICLR 2021.

Multi-Time Attention Networks (mTANs) This repository contains the PyTorch implementation for the paper Multi-Time Attention Networks for Irregularly

The Laboratory for Robust and Efficient Machine Learning 68 Dec 17, 2022
PyTorch implementation of ECCV 2020 paper "Foley Music: Learning to Generate Music from Videos "

Foley Music: Learning to Generate Music from Videos This repo holds the code for the framework presented on ECCV 2020. Foley Music: Learning to Genera

Chuang Gan 30 Nov 03, 2022
Machine Learning Toolkit for Kubernetes

Kubeflow the cloud-native platform for machine learning operations - pipelines, training and deployment. Documentation Please refer to the official do

Kubeflow 12.1k Jan 03, 2023
Learning to Initialize Neural Networks for Stable and Efficient Training

GradInit This repository hosts the code for experiments in the paper, GradInit: Learning to Initialize Neural Networks for Stable and Efficient Traini

Chen Zhu 124 Dec 30, 2022
PyTorch implementation of CloudWalk's recent work DenseBody

densebody_pytorch PyTorch implementation of CloudWalk's recent paper DenseBody. Note: For most recent updates, please check out the dev branch. Update

Lingbo Yang 401 Nov 19, 2022
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear

Simon Blanke 422 Jan 04, 2023
This is the paddle code for SeBoW(Self-Born wiring for neural trees), a kind of neural tree born form a large search space

SeBoW: Self-Born Wiring for neural trees(PaddlePaddle version) This is the paddle code for SeBoW(Self-Born wiring for neural trees), a kind of neural

HollyLee 13 Dec 08, 2022