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Action Detection in Smart Surveillance Systems - Web Application

Logo

Table of Contents

  1. Introduction
  2. System Block Diagram
  3. Features
  4. Demo
  5. Screenshots
  6. How to Run the Code
  7. Authors
  8. 🚀 About Us
  9. Contact

Introduction

In this project, AI-based smart surveillance system capable of automatically detecting different actions was implemented on the Zewail City video surveillance system. The system reached a recall of 80% and a precision of 70% without fine-tuning using custom data. The system provided different features for the end-user through its graphical interface allowing for easy and convenient data retrieval.

System Block Diagram

block diagram

Features

Logs page:

1- The user can view the history of actions along with some metadata:

- The *id* of the *camera* that captured that action.
- The *timestamp* indicating the start and end of the action.
- The *Building* and *location* where the action happened.
- The *confidence* of the predicted action.

2- The user can filter by:

- Actions
- Building
- Location 
- Camera 
- Start, end date and time.

Visualizations page:

It provides different visualizations that deliver key insights to the user.

Demo

smart.surveillance.demo.mp4

Screenshots

login2

logs (1)

photo_2022-06-19_12-21-10

How to Run the Code

1- Clone the project

  git clone https://github.com/mo-shaffei/action-detection-app

2- Go to the project directory

  cd action-detection-app

3- Install dependencies

  • if you have CUDA
    pip install moviepy
    conda install -c pytorch torchvision cudatoolkit=10.2
    conda install -c conda-forge -c fvcore -c iopath fvcore=0.1.4 iopath
    pip install pytorchvideo
    conda install -c anaconda flask
    conda install -c anaconda pymongo
    conda install -c anaconda pandas
    python -m pip install 'git+https://github.com/facebookresearch/detectron2.git'
    pip install scikit-video
    pip install opencv-python
  • if you don't have CUDA
    pip install moviepy
    conda install -c pytorch torchvision cpuonly
    conda install -c conda-forge -c fvcore -c iopath fvcore=0.1.4 iopath
    pip install pytorchvideo
    conda install -c anaconda flask
    conda install -c anaconda pymongo
    conda install -c anaconda pandas
    python -m pip install 'git+https://github.com/facebookresearch/detectron2.git'
    pip install scikit-video
    pip install opencv-python

4- Start the server

    flask run

Authors

🚀 About Us

We are a group of students studying Communications and Information Engineering at Zewail City of Science and Technology in the final year. This project is our Graduation Project.

Contact

To contact us:

fmoanesnoureldin@gmail.com

s-mohamed_chaffei@zewailcity.edu.eg

hassouna97.ma@gmail.com

s-touka99-mohamed@zewailcity.edu.eg