Real-time 3D multi-person detection made easy with OpenPose and the ZED

Overview

OpenPose ZED

What to expect

This sample show how to simply use the ZED with OpenPose, the deep learning framework that detects the skeleton from a single 2D image. The 3D information provided by the ZED is used to place the joints in space. The output is a 3D view of the skeletons.

Installation

Openpose

This sample can be put in the folder examples/user_code/ OR preferably, compile and install openpose with the cmake and compile this anywhere

The installation process is very easy using cmake.

Clone the repository :

    git clone https://github.com/CMU-Perceptual-Computing-Lab/openpose/

Build and install it :

    cd openpose
    mkdir build
    cmake .. # This can take a while
    make -j8
    sudo make install

ZED SDK

The ZED SDK is also a requirement for this sample, download the ZED SDK and follows the instructions.

It requires ZED SDK 2.4 for the floor plane detection but can be easily disabled to use an older ZED SDK version.

Build the program

Open a terminal in the sample directory and execute the following command:

    mkdir build
    cd build
    cmake ..
    make -j8

We then need to make a symbolic link to the models folder to be able to loads it

    ln -s ~/path/to/openpose/models "$(pwd)"

A models folder should now be in the build folder

Run the program

  • Navigate to the build directory and launch the executable

  • Or open a terminal in the build directory and run the sample :

      ./zed_openpose
    

Options

Beyond the openpose option, several more were added, mainly:

Option Description
svo_path SVO file path to load instead of opening the ZED
ogl_ptcloud Boolean to show the point cloud in the OpenGL window
estimate_floor_plane Boolean to align the point cloud on the floor plane
opencv_display Enable the 2D View of OpenPose output
depth_display Display the depth map with OpenCV

Example :

    ./zed_openpose -net_resolution 320x240 -ogl_ptcloud true -svo_path ~/foo/bar.svo

Notes

  • This sample is a proof of concept and might not be robust to every situation, especially to detect the floor plane if the environment is cluttered.
  • This sample was only tested on Linux but should be easy to run on Windows.
  • This sample requires both Openpose and the ZED SDK which are heavily relying on the GPU.
  • Only the body keypoints are currently used, however we could imagine doing the same for hand and facial keypoints, though the precision required might be a limiting factor.
Owner
blanktec
blanktec
Pyramid Grafting Network for One-Stage High Resolution Saliency Detection. CVPR 2022

PGNet Pyramid Grafting Network for One-Stage High Resolution Saliency Detection. CVPR 2022, CVPR 2022 (arXiv 2204.05041) Abstract Recent salient objec

CVTEAM 109 Dec 05, 2022
PyTorch implementation of the Quasi-Recurrent Neural Network - up to 16 times faster than NVIDIA's cuDNN LSTM

Quasi-Recurrent Neural Network (QRNN) for PyTorch Updated to support multi-GPU environments via DataParallel - see the the multigpu_dataparallel.py ex

Salesforce 1.3k Dec 28, 2022
Pytorch implementation of Hinton's Dynamic Routing Between Capsules

pytorch-capsule A Pytorch implementation of Hinton's "Dynamic Routing Between Capsules". https://arxiv.org/pdf/1710.09829.pdf Thanks to @naturomics fo

Tim Omernick 625 Oct 27, 2022
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

Adversarial Robustness Toolbox (ART) is a Python library for Machine Learning Security. ART provides tools that enable developers and researchers to defend and evaluate Machine Learning models and ap

3.4k Jan 04, 2023
Codes for TIM2021 paper "Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences"

Codes for TIM2021 paper "Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences"

Intelligent Robotics and Machine Vision Lab 4 Jul 19, 2022
LF-YOLO (Lighter and Faster YOLO) is used to detect defect of X-ray weld image.

This project is based on ultralytics/yolov3. LF-YOLO (Lighter and Faster YOLO) is used to detect defect of X-ray weld image. Download $ git clone http

26 Dec 13, 2022
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms

CARLA - Counterfactual And Recourse Library CARLA is a python library to benchmark counterfactual explanation and recourse models. It comes out-of-the

Carla Recourse 200 Dec 28, 2022
🤖 Project template for your next awesome AI project. 🦾

🤖 AI Awesome Project Template 👋 Template author You may want to adjust badge links in a README.md file. 💎 Installation with pip Installation is as

Wiktor Łazarski 18 Nov 23, 2022
Learning Generative Models of Textured 3D Meshes from Real-World Images, ICCV 2021

Learning Generative Models of Textured 3D Meshes from Real-World Images This is the reference implementation of "Learning Generative Models of Texture

Dario Pavllo 115 Jan 07, 2023
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

Apache MXNet (incubating) for Deep Learning Master Docs License Apache MXNet (incubating) is a deep learning framework designed for both efficiency an

ROCm Software Platform 29 Nov 16, 2022
Dynamical movement primitives (DMPs), probabilistic movement primitives (ProMPs), spatially coupled bimanual DMPs.

Movement Primitives Movement primitives are a common group of policy representations in robotics. There are many different types and variations. This

DFKI Robotics Innovation Center 63 Jan 06, 2023
A tiny, friendly, strong baseline code for Person-reID (based on pytorch).

Pytorch ReID Strong, Small, Friendly A tiny, friendly, strong baseline code for Person-reID (based on pytorch). Strong. It is consistent with the new

Zhedong Zheng 3.5k Jan 08, 2023
A Weakly Supervised Amodal Segmenter with Boundary Uncertainty Estimation

Paper Khoi Nguyen, Sinisa Todorovic "A Weakly Supervised Amodal Segmenter with Boundary Uncertainty Estimation", accepted to ICCV 2021 Our code is mai

Khoi Nguyen 5 Aug 14, 2022
BarcodeRattler - A Raspberry Pi Powered Barcode Reader to load a game on the Mister FPGA using MBC

Barcode Rattler A Raspberry Pi Powered Barcode Reader to load a game on the Mist

Chrissy 29 Oct 31, 2022
Driller: augmenting AFL with symbolic execution!

Driller Driller is an implementation of the driller paper. This implementation was built on top of AFL with angr being used as a symbolic tracer. Dril

Shellphish 791 Jan 06, 2023
an implementation of softmax splatting for differentiable forward warping using PyTorch

softmax-splatting This is a reference implementation of the softmax splatting operator, which has been proposed in Softmax Splatting for Video Frame I

Simon Niklaus 338 Dec 28, 2022
Implementation of 'X-Linear Attention Networks for Image Captioning' [CVPR 2020]

Introduction This repository is for X-Linear Attention Networks for Image Captioning (CVPR 2020). The original paper can be found here. Please cite wi

JDAI-CV 240 Dec 17, 2022
KAPAO is an efficient multi-person human pose estimation model that detects keypoints and poses as objects and fuses the detections to predict human poses.

KAPAO (Keypoints and Poses as Objects) KAPAO is an efficient single-stage multi-person human pose estimation model that models keypoints and poses as

Will McNally 664 Dec 30, 2022
DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation

DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation By Qing Xu, Wenting Duan and Na He Requirements pytorch==1.1

Qing Xu 20 Dec 09, 2022