Gods Eye - For Image processing and storing in database. (for admins and owners) Steps :-
- Extract the zip file.
- Install the following packages:- python==3.6.2 pytorch>=0.4.0 numpy==1.14.0 scikit-image==0.13.1 scipy==1.0.0 pandas==0.22.0
- The images are already present in the test data folder. You can change it if required.
- Finally, run it and enter the location and you are all set for real time prediction of the crowd. The system automatically sends a picture after regular intervals of time. It also sends the alert messages to the local authorities.
Godseye.apk - App for Android users to interact with our system to analyse real time data and predict it. Steps:
- Install the apk in your mobile and you are all set for a complete experience of our system.
Godseye website - Web interface for users to analyse real time data and predict.
- Go to website folder and run the index.html in your favourite browser.
- You are all set to experience the enhanced UI.
Godseye Admin.apk - Admin App for local authorities to set the limit for each location. Steps:
- Install the apk in your mobile and you are all set for a complete experience of our system.
Godseye_GUI.py - For users and customers Steps:
- Install firebase-admin package and import the db connectivity file shared with you.
- You can now run it and interact with real time data and also predict future data at a particular location for a particular date and time.
In recent years, the human population is growing in extreme rate and hence the growth has indirectly increased the incidence of the crowd. There is a lot of interest in many scientific research in public service, security, safety and computer vision for the analysis of mobility and behavior of the crowd. Due to a crowded crisis, there are large crowds of confusion, consequence in pushing, mass-panic, stampede or crowd crushes and causing control loss.People visiting various malls and students studying in universities face a lot of difficulty because of the rush. Our project aims to tackle this issue by providing a system for collecting, processing and visualizing the crowd behaviour. The end result of our system is a web and app user interface where users can browse through a range of information related to the crowd distribution and crowd movement within a campus and a city. The objectives of this project are: Develop an automated system for collecting and processing input data. Develop algorithms for observing the crowd size in various places and predicting the crowd. Raise alarms in the case of over crowdedness. Design and build database for data storage. Build an intrusive app and web user interface for visualizing the crowd distribution and crowd movement information.