공공장소에서 눈만 돌리면 CCTV가 보인다는 말이 과언이 아닐 정도로 CCTV가 우리 생활에 깊숙이 자리 잡았습니다.

Overview

ObsCare_Main

소개

공공장소에서 눈만 돌리면 CCTV가 보인다는 말이 과언이 아닐 정도로 CCTV가 우리 생활에 깊숙이 자리 잡았습니다.

CCTV의 대수가 급격히 늘어나면서 관리와 효율성 문제와 더불어, 곳곳에 설치된 CCTV를 개별 관제하는 것으로는 응급 상황 대처 등에

실효성이 떨어질 수 있다는 지적이 대두되고 있습니다.

이런 문제점을 해결할 수 있는 방안으로 영상을 자동으로 분석하여

문제 상황을 즉시 알리는 지능형 영상관제 시스템(ObsCare)을 제시하고자 합니다.

시스템 구성도

image

시연 화면

상황 감지 시 log 발생

image

이전 영상 확인 위한 정보 입력

image

이전 영상 확인

image

설치 및 실행

Ubuntu 20.04 터미널에서 설치한다고 가정하였습니다.

clone repository

git clone https://github.com/SSU-DC-DCWZ/ObsCare_Main.git

가상환경 생성 및 활성화

python -m venv venv
source venv/bin/activate

의존성 패키지 설치

cd ObsCare_Main
pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 -f https://download.pytorch.org/whl/torch_stable.html
pip install -r requirements.txt

실행

python3 ObsCare.py

시연 시스템 사양

1. UVC 카메라

국제에이브이 에이스원 X PRO2

2. GPU 및 cuda 버전

NVIDIA GeForce RTX 3080 10GB, CUDA 11.4

3. CPU

Intel(R) Core(TM) i9-10900K CPU @ 3.70GHz

4. 메모리

16GB

5. Python version

Python 3.8.10

개발 환경

Ubuntu 20.04.3 LTS (GNU/Linux 5.11.0-25-generic x86_64)

PyCharm 2021.1.13 (Professional Edition) @11.0.11

Visual Studio Code 1.60.0

기여자

강병휘(essentialhrdy) : 모델 학습 및 Object Detection 처리

이찬서(Lfollow-CS) : DB,Stream 관리 및 개별 프로젝트 통합

박세진(pseeej) : UI 생성 및 Model 스레딩 관리

라이선스

이 프로젝트는 GNU General Public License v3.0을 사용합니다.

PyTorch implementations of the beta divergence loss.

Beta Divergence Loss - PyTorch Implementation This repository contains code for a PyTorch implementation of the beta divergence loss. Dependencies Thi

Billy Carson 7 Nov 09, 2022
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •

Pytorch Lightning 21.1k Jan 08, 2023
Over9000 optimizer

Optimizers and tests Every result is avg of 20 runs. Dataset LR Schedule Imagenette size 128, 5 epoch Imagewoof size 128, 5 epoch Adam - baseline OneC

Mikhail Grankin 405 Nov 27, 2022
Cross-modal Retrieval using Transformer Encoder Reasoning Networks (TERN). With use of Metric Learning and FAISS for fast similarity search on GPU

Cross-modal Retrieval using Transformer Encoder Reasoning Networks This project reimplements the idea from "Transformer Reasoning Network for Image-Te

Minh-Khoi Pham 5 Nov 05, 2022
Geometric Deep Learning Extension Library for PyTorch

Documentation | Paper | Colab Notebooks | External Resources | OGB Examples PyTorch Geometric (PyG) is a geometric deep learning extension library for

Matthias Fey 16.5k Jan 08, 2023
Repository for the COLING 2020 paper "Explainable Automated Fact-Checking: A Survey."

Explainable Fact Checking: A Survey This repository and the accompanying webpage contain resources for the paper "Explainable Fact Checking: A Survey"

Neema Kotonya 42 Nov 17, 2022
A Number Recognition algorithm

Paddle-VisualAttention Results_Compared SVHN Dataset Methods Steps GPU Batch Size Learning Rate Patience Decay Step Decay Rate Training Speed (FPS) Ac

1 Nov 12, 2021
Official code for 'Robust Siamese Object Tracking for Unmanned Aerial Manipulator' and offical introduction to UAMT100 benchmark

SiamSA: Robust Siamese Object Tracking for Unmanned Aerial Manipulator Demo video 📹 Our video on Youtube and bilibili demonstrates the evaluation of

Intelligent Vision for Robotics in Complex Environment 12 Dec 18, 2022
Source code of "Hold me tight! Influence of discriminative features on deep network boundaries"

Hold me tight! Influence of discriminative features on deep network boundaries This is the source code to reproduce the experiments of the NeurIPS 202

EPFL LTS4 19 Dec 10, 2021
Code for all the Advent of Code'21 challenges mostly written in python

Advent of Code 21 Code for all the Advent of Code'21 challenges mostly written in python. They are not necessarily the best or fastest solutions but j

4 May 26, 2022
Research on controller area network Intrusion Detection Systems

Group members information Member 1: Lixue Liang Member 2: Yuet Lee Chan Member 3: Xinruo Zhang Member 4: Yifei Han User Manual Generate Attack Packets

Roche 4 Aug 30, 2022
Source code for our Paper "Learning in High-Dimensional Feature Spaces Using ANOVA-Based Matrix-Vector Multiplication"

NFFT4ANOVA Source code for our Paper "Learning in High-Dimensional Feature Spaces Using ANOVA-Based Matrix-Vector Multiplication" This package uses th

Theresa Wagner 1 Aug 10, 2022
Neural-fractal - Create Fractals Using Complex-Valued Neural Networks!

Neural Fractal Create Fractals Using Complex-Valued Neural Networks! Home Page Features Define Dynamical Systems Using Complex-Valued Neural Networks

Amirabbas Asadi 10 Dec 17, 2022
AdaFocus (ICCV 2021) Adaptive Focus for Efficient Video Recognition

AdaFocus (ICCV 2021) This repo contains the official code and pre-trained models for AdaFocus. Adaptive Focus for Efficient Video Recognition Referenc

Rainforest Wang 115 Dec 21, 2022
Multi Agent Path Finding Algorithms

MATP-solver Simulator collision check path step random initial states or given states Traditional method Seperate A* algorithem Confict-based Search S

30 Dec 12, 2022
This solves the autonomous driving issue which is supported by deep learning technology. Given a video, it splits into images and predicts the angle of turning for each frame.

Self Driving Car An autonomous car (also known as a driverless car, self-driving car, and robotic car) is a vehicle that is capable of sensing its env

Sagor Saha 4 Sep 04, 2021
High-performance moving least squares material point method (MLS-MPM) solver.

High-Performance MLS-MPM Solver with Cutting and Coupling (CPIC) (MIT License) A Moving Least Squares Material Point Method with Displacement Disconti

Yuanming Hu 2.2k Dec 31, 2022
Code for IntraQ, PyTorch implementation of our paper under review

IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization paper Requirements Python = 3.7.10 Pytorch == 1.7

1 Nov 19, 2021
PyTorch implementation of "Learn to Dance with AIST++: Music Conditioned 3D Dance Generation."

Learn to Dance with AIST++: Music Conditioned 3D Dance Generation. Installation pip install -r requirements.txt Prepare Dataset bash data/scripts/pre

Zj Li 8 Sep 07, 2021
3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans.

3DMV 3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans. This work is based on our ECCV'18 p

Владислав Молодцов 0 Feb 06, 2022