People movement type classifier with YOLOv4 detection and SORT tracking.

Overview

Movement classification

The goal of this project would be movement classification of people, in other words, walking (normal and fast) and running.

Yolov4 will be used for detection.

Yolov4 detection

Yolo: Real-Time object detection

You only look once (YOLO) is a state-of-the-art, real-time object detection system.

Currently the most advanced YOLO version is YOLOv4 which provides optimal speed and accuracy for object detection, therefore it will be used.

Modules

Before starting, usage of a virtual environment is advised via the venv module:

$ python3 -m venv envname # to create the virtual env
$ source envname/bin/activate # activate it
$ deactivate # when done

For ease of use, the yolov4 Python module was used, which is a YOLOv4 implementation in TensorFlow 2. For further documentation refer to the project wiki

To install yolov4:

Dependencies:

$ python3 -m pip install opencv-python tensorflow

Note: If TensorFlow Lite needs to be used, refer to the project wiki for further instructions.

TensorFlow YOLOv4:

$ python3 -m pip install yolov4

Download the yolov4-tiny and yolov4 weights to the weights/ directory from the project wiki weights download section.

Test yolov4 with the provided default test image. Change model config, weights based on the one used (default is yolov4-tiny).

$ python3 test.py

Test results

KACAVIS runaway_walk_1.mp4 frame 1471 was used:

YOLOv4 YOLOv4-tiny
Yolov4 Yolov4-tiny

Help

>>> from yolov4.tf import YOLOv4
>>> help(YOLOv4)

Dataset

FER's dataset: KACAVIS.`

Download the dataset:

wget -O dataset/crowd_simulation_dataset.zip  http://kacavis.zemris.fer.hr/datasets/Crowd_simulation_dataset_videos.zip

Pip freeze

To get the used module versions, in other words $ python3 -m pip freeze, take a look at:

./pip_freeze.txt

Tested on Archlinux 5.12.x-arch1-1, python version Python 3.9.5

If working on Arch change python3 to python everywhere.

Owner
sladoled
Deep learning image registration library for PyTorch

TorchIR: Pytorch Image Registration TorchIR is a image registration library for deep learning image registration (DLIR). I have integrated several ide

Bob de Vos 40 Dec 16, 2022
Code for WSDM 2022 paper, Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation.

DuoRec Code for WSDM 2022 paper, Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation. Usage Download datasets fr

Qrh 46 Dec 19, 2022
Official implementation of ACTION-Net: Multipath Excitation for Action Recognition (CVPR'21).

ACTION-Net Official implementation of ACTION-Net: Multipath Excitation for Action Recognition (CVPR'21). Getting Started EgoGesture data folder struct

V-Sense 171 Dec 26, 2022
MediaPipeで姿勢推定を行い、Tokyo2020オリンピック風のピクトグラムを表示するデモ

Tokyo2020-Pictogram-using-MediaPipe MediaPipeで姿勢推定を行い、Tokyo2020オリンピック風のピクトグラムを表示するデモです。 Tokyo2020Pictgram02.mp4 Requirement mediapipe 0.8.6 or later O

KazuhitoTakahashi 295 Dec 26, 2022
A Python package for time series augmentation

tsaug tsaug is a Python package for time series augmentation. It offers a set of augmentation methods for time series, as well as a simple API to conn

Arundo Analytics 278 Jan 01, 2023
Multi-View Consistent Generative Adversarial Networks for 3D-aware Image Synthesis (CVPR2022)

Multi-View Consistent Generative Adversarial Networks for 3D-aware Image Synthesis Multi-View Consistent Generative Adversarial Networks for 3D-aware

Xuanmeng Zhang 78 Dec 10, 2022
implement of SwiftNet:Real-time Video Object Segmentation

SwiftNet The official PyTorch implementation of SwiftNet:Real-time Video Object Segmentation, which has been accepted by CVPR2021. Requirements Python

haochen wang 64 Dec 14, 2022
HMLLDB is a collection of LLDB commands to assist in the debugging of iOS apps.

HMLLDB is a collection of LLDB commands to assist in the debugging of iOS apps. 中文介绍 Features Non-intrusive. Your iOS project does not need to be modi

mao2020 47 Oct 22, 2022
Code for CVPR 2018 paper --- Texture Mapping for 3D Reconstruction with RGB-D Sensor

G2LTex This repository contains the implementation of "Texture Mapping for 3D Reconstruction with RGB-D Sensor (CVPR2018)" based on mvs-texturing. Due

Fu Yanping(付燕平) 129 Dec 30, 2022
Latte: Cross-framework Python Package for Evaluation of Latent-based Generative Models

Cross-framework Python Package for Evaluation of Latent-based Generative Models Latte Latte (for LATent Tensor Evaluation) is a cross-framework Python

Karn Watcharasupat 30 Sep 08, 2022
The implementation of ICASSP 2020 paper "Pixel-level self-paced learning for super-resolution"

Pixel-level Self-Paced Learning for Super-Resolution This is an official implementaion of the paper Pixel-level Self-Paced Learning for Super-Resoluti

Elon Lin 41 Dec 15, 2022
Bayesian optimisation library developped by Huawei Noah's Ark Library

Bayesian Optimisation Research This directory contains official implementations for Bayesian optimisation works developped by Huawei R&D, Noah's Ark L

HUAWEI Noah's Ark Lab 395 Dec 30, 2022
The materials used in the SaxonJS tutorial presented at Declarative Amsterdam, 2021

SaxonJS-Tutorial-2021, version 1.0.4 Last updated on 4 November, 2021. Table of contents Background Prerequisites Starting a web server Running a Java

Saxonica 11 Oct 23, 2022
Implementation of the ALPHAMEPOL algorithm, presented in Unsupervised Reinforcement Learning in Multiple Environments.

ALPHAMEPOL This repository contains the implementation of the ALPHAMEPOL algorithm, presented in Unsupervised Reinforcement Learning in Multiple Envir

3 Dec 23, 2021
Using a Seq2Seq RNN architecture via TensorFlow to predict future Bitcoin prices

Recurrent Bitcoin Network A Data Science Thesis Project About This repository contains the source code for implementing Bitcoin price prediciton using

Frizu 6 Sep 08, 2022
Training vision models with full-batch gradient descent and regularization

Stochastic Training is Not Necessary for Generalization -- Training competitive vision models without stochasticity This repository implements trainin

Jonas Geiping 32 Jan 06, 2023
Keras implementation of AdaBound

AdaBound for Keras Keras port of AdaBound Optimizer for PyTorch, from the paper Adaptive Gradient Methods with Dynamic Bound of Learning Rate. Usage A

Somshubra Majumdar 132 Sep 23, 2022
Code for testing various M1 Chip benchmarks with TensorFlow.

M1, M1 Pro, M1 Max Machine Learning Speed Test Comparison This repo contains some sample code to benchmark the new M1 MacBooks (M1 Pro and M1 Max) aga

Daniel Bourke 348 Jan 04, 2023
This repository contains source code for the Situated Interactive Language Grounding (SILG) benchmark

SILG This repository contains source code for the Situated Interactive Language Grounding (SILG) benchmark. If you find this work helpful, please cons

Victor Zhong 17 Nov 27, 2022
Unofficial pytorch implementation of the paper "Dynamic High-Pass Filtering and Multi-Spectral Attention for Image Super-Resolution"

DFSA Unofficial pytorch implementation of the ICCV 2021 paper "Dynamic High-Pass Filtering and Multi-Spectral Attention for Image Super-Resolution" (p

2 Nov 15, 2021