MoveNetを用いたPythonでの姿勢推定のデモ

Overview

MoveNet-Python-Example

MoveNetのPythonでの動作サンプルです。
ONNXに変換したモデルも同梱しています。変換自体を試したい方はMoveNet_tf2onnx.ipynbを使用ください。

smjqx-4ndt8

2021/08/24時点でTensorFlow Hubで提供されている以下モデルを使用しています。

Requirement

  • TensorFlow 2.3.0 or later
  • tensorflow-hub 0.12.0 or later
  • OpenCV 3.4.2 or later
  • onnxruntime 1.5.2 or later ※ONNX推論を使用する場合のみ

Demo

デモの実行方法は以下です。

SignlePose

python demo_singlepose.py
  • --device
    カメラデバイス番号の指定
    デフォルト:0
  • --file
    動画ファイルの指定 ※指定時はカメラデバイスより優先
    デフォルト:指定なし
  • --width
    カメラキャプチャ時の横幅
    デフォルト:960
  • --height
    カメラキャプチャ時の縦幅
    デフォルト:540
  • --mirror
    VideoCapture()取り込みデータを左右反転するか否か
    デフォルト:指定なし
  • --model_select
    使用モデルの選択
    Saved Model, ONNX:0→Lightning 1→Thunder
    TFLite:0→Lightning(float16) 1→Thunder(float16) 2→Lightning(int8) 3→Thunder(int8)
    デフォルト:0
  • --keypoint_score
    キーポイント表示の閾値
    デフォルト:0.4

MultiPose

python demo_multipose.py
  • --device
    カメラデバイス番号の指定
    デフォルト:0
  • --file
    動画ファイルの指定 ※指定時はカメラデバイスより優先
    デフォルト:指定なし
  • --width
    カメラキャプチャ時の横幅
    デフォルト:960
  • --height
    カメラキャプチャ時の縦幅
    デフォルト:540
  • --mirror
    VideoCapture()取り込みデータを左右反転するか否か
    デフォルト:指定なし
  • --keypoint_score
    キーポイント表示の閾値
    デフォルト:0.4
  • --bbox_score
    バウンディングボックス表示の閾値
    デフォルト:0.2

Reference

Author

高橋かずひと(https://twitter.com/KzhtTkhs)

License

MoveNet-Python-Example is under Apache-2.0 License.

License(Movie)

サンプル動画はNHKクリエイティブ・ライブラリーストリートバスケットを使用しています。

Owner
KazuhitoTakahashi
KazuhitoTakahashi
Code for the paper 'A High Performance CRF Model for Clothes Parsing'.

Clothes Parsing Overview This code provides an implementation of the research paper: A High Performance CRF Model for Clothes Parsing Edgar Simo-S

Edgar Simo-Serra 119 Nov 21, 2022
High performance Cross-platform Inference-engine, you could run Anakin on x86-cpu,arm, nv-gpu, amd-gpu,bitmain and cambricon devices.

Anakin2.0 Welcome to the Anakin GitHub. Anakin is a cross-platform, high-performance inference engine, which is originally developed by Baidu engineer

514 Dec 28, 2022
A configurable, tunable, and reproducible library for CTR prediction

FuxiCTR This repo is the community dev version of the official release at huawei-noah/benchmark/FuxiCTR. Click-through rate (CTR) prediction is an cri

XUEPAI 397 Dec 30, 2022
An LSTM based GAN for Human motion synthesis

GAN-motion-Prediction An LSTM based GAN for motion synthesis has a few issues reading H3.6M data from A.Jain et al , will fix soon. Prediction of the

Amogh Adishesha 9 Jun 17, 2022
An easy way to build PyTorch datasets. Modularly build datasets and automatically cache processed results

EasyDatas An easy way to build PyTorch datasets. Modularly build datasets and automatically cache processed results Installation pip install git+https

Ximing Yang 4 Dec 14, 2021
cisip-FIRe - Fast Image Retrieval

Fast Image Retrieval (FIRe) is an open source image retrieval project release by Center of Image and Signal Processing Lab (CISiP Lab), Universiti Malaya. This project implements most of the major bi

CISiP Lab 39 Nov 25, 2022
Official pytorch code for "APP: Anytime Progressive Pruning"

APP: Anytime Progressive Pruning Diganta Misra1,2,3, Bharat Runwal2,4, Tianlong Chen5, Zhangyang Wang5, Irina Rish1,3 1 Mila - Quebec AI Institute,2 L

Landskape AI 12 Nov 22, 2022
Image Captioning using CNN and Transformers

Image-Captioning Keras/Tensorflow Image Captioning application using CNN and Transformer as encoder/decoder. In particulary, the architecture consists

24 Dec 28, 2022
PyTorch reimplementation of hand-biomechanical-constraints (ECCV2020)

Hand Biomechanical Constraints Pytorch Unofficial PyTorch reimplementation of Hand-Biomechanical-Constraints (ECCV2020). This project reimplement foll

Hao Meng 59 Dec 20, 2022
Cards Against Humanity AI

cah-ai This is a Cards Against Humanity AI implemented using a pre-trained Semantic Search model. How it works A player is described by a combination

Alex Nichol 2 Aug 22, 2022
Learning to Draw: Emergent Communication through Sketching

Learning to Draw: Emergent Communication through Sketching This is the official code for the paper "Learning to Draw: Emergent Communication through S

19 Jul 22, 2022
Privacy as Code for DSAR Orchestration: Privacy Request automation to fulfill GDPR, CCPA, and LGPD data subject requests.

Meet Fidesops: Privacy as Code for DSAR Orchestration A part of the greater Fides ecosystem. ⚡ Overview Fidesops (fee-dez-äps, combination of the Lati

Ethyca 44 Dec 06, 2022
A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis

A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis Figure: Shape-Accurate 3D-Aware Image Synthesis. A Shading-Guid

Xingang Pan 115 Dec 18, 2022
Use unsupervised and supervised learning to predict stocks

AIAlpha: Multilayer neural network architecture for stock return prediction This project is meant to be an advanced implementation of stacked neural n

Vivek Palaniappan 1.5k Dec 26, 2022
Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019

Class-Balanced Loss Based on Effective Number of Samples Tensorflow code for the paper: Class-Balanced Loss Based on Effective Number of Samples Yin C

Yin Cui 546 Jan 08, 2023
A library for Deep Learning Implementations and utils

deeply A Deep Learning library Table of Contents Features Quick Start Usage License Features Python 2.7+ and Python 3.4+ compatible. Quick Start $ pip

Achilles Rasquinha 1 Dec 12, 2022
[CVPR 2021] NormalFusion: Real-Time Acquisition of Surface Normals for High-Resolution RGB-D Scanning

NormalFusion: Real-Time Acquisition of Surface Normals for High-Resolution RGB-D Scanning Project Page | Paper | Supplemental material #1 | Supplement

KAIST VCLAB 49 Nov 24, 2022
Commonality in Natural Images Rescues GANs: Pretraining GANs with Generic and Privacy-free Synthetic Data - Official PyTorch Implementation (CVPR 2022)

Commonality in Natural Images Rescues GANs: Pretraining GANs with Generic and Privacy-free Synthetic Data (CVPR 2022) Potentials of primitive shapes f

31 Sep 27, 2022
UNAVOIDS: Unsupervised and Nonparametric Approach for Visualizing Outliers and Invariant Detection Scoring

UNAVOIDS: Unsupervised and Nonparametric Approach for Visualizing Outliers and Invariant Detection Scoring Code Summary aggregate.py: this script aggr

1 Dec 28, 2021
Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis

Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis. You write a high level configuration file specifying your in

Blue Collar Bioinformatics 917 Jan 03, 2023