ByteTrack(Multi-Object Tracking by Associating Every Detection Box)のPythonでのONNX推論サンプル

Overview

ByteTrack-ONNX-Sample

ByteTrack(Multi-Object Tracking by Associating Every Detection Box)のPythonでのONNX推論サンプルです。
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ByteTrack_Convert2ONNX.ipynbを使用ください。
ByteTrack_Convert2ONNX.ipynbはColaboratory上での実行を想定しています。
書き動画はWindowsでの実行例です。

sample_.mp4

Requirement

opencv-python 4.5.3.56 or later
onnx 1.9.0 or later
onnxruntime-gpu 1.9.0 or later
Cython 0.29.24 or later
torch 1.8.1 or later
torchvision 0.9.1 or later
pycocotools 2.0.2 or later
scipy 1.6.3 or later
loguru 0.5.3 or later
thop 0.0.31.post2005241907 or later
lap 0.4.0 or later
cython_bbox 0.1.3 or later

※onnxruntime-gpuはonnxruntimeでも動作しますが、推論時間がかかるためGPUを推奨します
※Windowsでcython_bbox のインストールが失敗する場合は、GitHubからのインストールをお試しください(2021/11/19時点)
pip install -e git+https://github.com/samson-wang/cython_bbox.git#egg=cython-bbox

Demo

デモの実行方法は以下です。

動画:動画に対しByteTrackで追跡した結果を動画出力します

python demo_video_onnx.py
実行時オプション
  • --use_debug_window
    動画書き込み時に書き込みフレームをGUI表示するか否か
    デフォルト:指定なし
  • --model
    ByteTrackのONNXモデル格納パス
    デフォルト:byte_tracker/model/bytetrack_s.onnx
  • --video
    入力動画の格納パス
    デフォルト:sample.mp4
  • --output_dir
    動画出力パス
    デフォルト:output
  • --score_th
    人検出のスコア閾値
    デフォルト:0.1
  • --score_th
    人検出のNMS閾値
    デフォルト:0.7
  • --input_shape
    推論時入力サイズ
    デフォルト:608,1088
  • --with_p6
    YOLOXモデルのFPN/PANでp6を含むか否か
    デフォルト:指定なし
  • --track_thresh
    追跡時のスコア閾値
    デフォルト:0.5
  • --track_buffer
    見失い時に何フレームの間、追跡対象を保持するか
    デフォルト:30
  • --match_thresh
    追跡時のマッチングスコア閾値
    デフォルト:0.8
  • --min-box-area
    最小のバウンディングボックスのサイズ閾値
    デフォルト:10
  • --mot20
    MOT20を使用しているか否か
    デフォルト:指定なし

Webカメラ:Webカメラ画像に対しByteTrackで追跡した結果をGUI表示します

python demo_webcam_onnx.py
実行時オプション
  • --model
    ByteTrackのONNXモデル格納パス
    デフォルト:byte_tracker/model/bytetrack_s.onnx
  • --device
    カメラデバイス番号の指定
    デフォルト:0
  • --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
  • --score_th
    人検出のスコア閾値
    デフォルト:0.1
  • --score_th
    人検出のNMS閾値
    デフォルト:0.7
  • --input_shape
    推論時入力サイズ
    デフォルト:608,1088
  • --with_p6
    YOLOXモデルのFPN/PANでp6を含むか否か
    デフォルト:指定なし
  • --track_thresh
    追跡時のスコア閾値
    デフォルト:0.5
  • --track_buffer
    見失い時に何フレームの間、追跡対象を保持するか
    デフォルト:30
  • --match_thresh
    追跡時のマッチングスコア閾値
    デフォルト:0.8
  • --min-box-area
    最小のバウンディングボックスのサイズ閾値
    デフォルト:10
  • --mot20
    MOT20を使用しているか否か
    デフォルト:指定なし

Reference

Author

高橋かずひと(https://twitter.com/KzhtTkhs)

License

ByteTrack-ONNX-Sample is under MIT License.

License(Movie)

サンプル動画はNHKクリエイティブ・ライブラリーイギリス ウースターのエルガー像を使用しています。

Owner
KazuhitoTakahashi
KazuhitoTakahashi
Implementation of ICCV21 paper: PnP-DETR: Towards Efficient Visual Analysis with Transformers

Implementation of ICCV 2021 paper: PnP-DETR: Towards Efficient Visual Analysis with Transformers arxiv This repository is based on detr Recently, DETR

twang 113 Dec 27, 2022
The Implicit Bias of Gradient Descent on Generalized Gated Linear Networks

The Implicit Bias of Gradient Descent on Generalized Gated Linear Networks This folder contains the code to reproduce the data in "The Implicit Bias o

Samuel Lippl 0 Feb 05, 2022
Official MegEngine implementation of CREStereo(CVPR 2022 Oral).

[CVPR 2022] Practical Stereo Matching via Cascaded Recurrent Network with Adaptive Correlation This repository contains MegEngine implementation of ou

MEGVII Research 309 Dec 30, 2022
Official PaddlePaddle implementation of Paint Transformer

Paint Transformer: Feed Forward Neural Painting with Stroke Prediction [Paper] [Paddle Implementation] Update We have optimized the serial inference p

TianweiLin 284 Dec 31, 2022
Flax is a neural network ecosystem for JAX that is designed for flexibility.

Flax: A neural network library and ecosystem for JAX designed for flexibility Overview | Quick install | What does Flax look like? | Documentation See

Google 3.9k Jan 02, 2023
Planning from Pixels in Environments with Combinatorially Hard Search Spaces -- NeurIPS 2021

PPGS: Planning from Pixels in Environments with Combinatorially Hard Search Spaces Environment Setup We recommend pipenv for creating and managing vir

Autonomous Learning Group 11 Jun 26, 2022
Minecraft Hack Detection With Python

Minecraft Hack Detection An attempt to try and use crowd sourced replays to find

Kuleen Sasse 3 Mar 26, 2022
[CVPR 2021] Released code for Counterfactual Zero-Shot and Open-Set Visual Recognition

Counterfactual Zero-Shot and Open-Set Visual Recognition This project provides implementations for our CVPR 2021 paper Counterfactual Zero-S

144 Dec 24, 2022
thundernet ncnn

MMDetection_Lite 基于mmdetection 实现一些轻量级检测模型,安装方式和mmdeteciton相同 voc0712 voc 0712训练 voc2007测试 coco预训练 thundernet_voc_shufflenetv2_1.5 input shape mAP 320

DayBreak 39 Dec 05, 2022
Registration Loss Learning for Deep Probabilistic Point Set Registration

RLLReg This repository contains a Pytorch implementation of the point set registration method RLLReg. Details about the method can be found in the 3DV

Felix Järemo Lawin 35 Nov 02, 2022
Official implementation of VQ-Diffusion

Official implementation of VQ-Diffusion: Vector Quantized Diffusion Model for Text-to-Image Synthesis

Microsoft 592 Jan 03, 2023
Semantic Scholar's Author Disambiguation Algorithm & Evaluation Suite

S2AND This repository provides access to the S2AND dataset and S2AND reference model described in the paper S2AND: A Benchmark and Evaluation System f

AI2 54 Nov 28, 2022
Codes for realizing theories learned from Data Mining, Machine Learning, Deep Learning without using the present Python packages.

Codes-for-Algorithms Codes for realizing theories learned from Data Mining, Machine Learning, Deep Learning without using the present Python packages.

Tracy (Shengmin) Tao 1 Apr 12, 2022
Official code for paper "ISNet: Costless and Implicit Image Segmentation for Deep Classifiers, with Application in COVID-19 Detection"

Official code for paper "ISNet: Costless and Implicit Image Segmentation for Deep Classifiers, with Application in COVID-19 Detection". LRPDenseNet.py

Pedro Ricardo Ariel Salvador Bassi 2 Sep 21, 2022
CenterNet:Objects as Points目标检测模型在Pytorch当中的实现

CenterNet:Objects as Points目标检测模型在Pytorch当中的实现

Bubbliiiing 267 Dec 29, 2022
The official repository for "Revealing unforeseen diagnostic image features with deep learning by detecting cardiovascular diseases from apical four-chamber ultrasounds"

Revealing unforeseen diagnostic image features with deep learning by detecting cardiovascular diseases from apical four-chamber ultrasounds The why Im

3 Mar 29, 2022
PyTorch implementation of our ICCV2021 paper: StructDepth: Leveraging the structural regularities for self-supervised indoor depth estimation

StructDepth PyTorch implementation of our ICCV2021 paper: StructDepth: Leveraging the structural regularities for self-supervised indoor depth estimat

SJTU-ViSYS 112 Nov 28, 2022
Deep Learning for Human Part Discovery in Images - Chainer implementation

Deep Learning for Human Part Discovery in Images - Chainer implementation NOTE: This is not official implementation. Original paper is Deep Learning f

Shintaro Shiba 63 Sep 25, 2022
Implementations of orthogonal and semi-orthogonal convolutions in the Fourier domain with applications to adversarial robustness

Orthogonalizing Convolutional Layers with the Cayley Transform This repository contains implementations and source code to reproduce experiments for t

CMU Locus Lab 36 Dec 30, 2022
Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA)

Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA). Master's thesis documents. Bibliography, experiments and reports.

Erick Cobos 73 Dec 04, 2022