PoseViz – Multi-person, multi-camera 3D human pose visualization tool built using Mayavi.

Overview

PoseViz – 3D Human Pose Visualizer

Multi-person, multi-camera 3D human pose visualization tool built using Mayavi. As used in MeTRAbs visualizations.

This repo does not contain pose estimation code, only the visualization part.

Gist of usage

import poseviz

viz = poseviz.PoseViz(...)
camera = poseviz.Camera(...)
for frame in frames:
    bounding_boxes, poses3d = run_pose_estimation_model(frame)
    viz.update(frame=frame, boxes=bounding_boxes, poses=poses3d, camera=camera)

The main feature of this tool is that the graphical event loop is hidden from the library user. We want to write code in terms of the prediction loop of the human pose estimator, not from the point of view of the visualizer tool.

Behind the scenes, this is achieved through forking a dedicated visualization process and passing new scene information via multiprocessing queues.

Detailed docs TBA.

Installation

Install Mayavi via Conda (the Mayavi pip package has compilation problems), clone this repo and install PoseViz via pip.

conda install mayavi -c conda-forge
pip install .

Then run demo.py to test if installation was successful.

Owner
István Sárándi
PhD candidate at RWTH Aachen University, making robots and machines see people better
István Sárándi
A Convolutional Transformer for Keyword Spotting

☢️ Audiomer ☢️ Audiomer: A Convolutional Transformer for Keyword Spotting [ arXiv ] [ Previous SOTA ] [ Model Architecture ] Results on SpeechCommands

49 Jan 27, 2022
Minimisation of a negative log likelihood fit to extract the lifetime of the D^0 meson (MNLL2ELDM)

Minimisation of a negative log likelihood fit to extract the lifetime of the D^0 meson (MNLL2ELDM) Introduction The average lifetime of the $D^{0}$ me

Son Gyo Jung 1 Dec 17, 2021
This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model inference.

PyTorch Infer Utils This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model infer

Alex Gorodnitskiy 11 Mar 20, 2022
A large-scale benchmark for co-optimizing the design and control of soft robots, as seen in NeurIPS 2021.

Evolution Gym A large-scale benchmark for co-optimizing the design and control of soft robots. As seen in Evolution Gym: A Large-Scale Benchmark for E

121 Dec 14, 2022
Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language (NeurIPS 2021)

VRDP (NeurIPS 2021) Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language Mingyu Ding, Zhenfang Chen, Tao Du, Pin

Mingyu Ding 36 Sep 20, 2022
Differential fuzzing for the masses!

NEZHA NEZHA is an efficient and domain-independent differential fuzzer developed at Columbia University. NEZHA exploits the behavioral asymmetries bet

147 Dec 05, 2022
A privacy-focused, intelligent security camera system.

Self-Hosted Home Security Camera System A privacy-focused, intelligent security camera system. Features: Multi-camera support w/ minimal configuration

Scott Barnes 175 Jan 01, 2023
[ICCV'21] Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment

CKDN The official implementation of the ICCV2021 paper "Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment" O

Multimedia Research 50 Dec 13, 2022
AdelaiDepth is an open source toolbox for monocular depth prediction.

AdelaiDepth is an open source toolbox for monocular depth prediction.

Adelaide Intelligent Machines (AIM) Group 743 Jan 01, 2023
This is the face keypoint train code of project face-detection-project

face-key-point-pytorch 1. Data structure The structure of landmarks_jpg is like below: |--landmarks_jpg |----AFW |------AFW_134212_1_0.jpg |------AFW_

I‘m X 3 Nov 27, 2022
A large dataset of 100k Google Satellite and matching Map images, resembling pix2pix's Google Maps dataset.

Larger Google Sat2Map dataset This dataset extends the aerial ⟷ Maps dataset used in pix2pix (Isola et al., CVPR17). The provide script download_sat2m

34 Dec 28, 2022
A collection of implementations of deep domain adaptation algorithms

Deep Transfer Learning on PyTorch This is a PyTorch library for deep transfer learning. We divide the code into two aspects: Single-source Unsupervise

Yongchun Zhu 647 Jan 03, 2023
Dense Prediction Transformers

Vision Transformers for Dense Prediction This repository contains code and models for our paper: Vision Transformers for Dense Prediction René Ranftl,

Intelligent Systems Lab Org 1.3k Jan 02, 2023
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).

ClusterGCN ⠀⠀ A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019). A

Benedek Rozemberczki 697 Dec 27, 2022
A simple tutoral for error correction task, based on Pytorch

gramcorrector A simple tutoral for error correction task, based on Pytorch Grammatical Error Detection (sentence-level) a binary sequence-based classi

peiyuan_gong 8 Dec 03, 2022
Using this codebase as a tool for my own research. Making some modifications to the original repo for my own purposes.

For SwapNet Create a list.txt file containing all the images to process. This can be done with the GNU find command: find path/to/input/folder -name '

Andrew Jong 2 Nov 10, 2021
Incorporating Transformer and LSTM to Kalman Filter with EM algorithm

Deep learning based state estimation: incorporating Transformer and LSTM to Kalman Filter with EM algorithm Overview Kalman Filter requires the true p

zshicode 57 Dec 27, 2022
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 Apache MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to m

The Apache Software Foundation 20.2k Jan 08, 2023
Code for "Continuous-Time Meta-Learning with Forward Mode Differentiation" (ICLR 2022)

Continuous-Time Meta-Learning with Forward Mode Differentiation ICLR 2022 (Spotlight) - Installation - Example - Citation This repository contains the

Tristan Deleu 25 Oct 20, 2022
World Models with TensorFlow 2

World Models This repo reproduces the original implementation of World Models. This implementation uses TensorFlow 2.2. Docker The easiest way to hand

Zac Wellmer 234 Nov 30, 2022