Skip to content

The hardware-based simulation is based on EV3 Core set and Raspberry Pi along with Pixy 2 Camera for virtually image recognition by CNN with drag and drop functionality of virtual hardware.

License

Notifications You must be signed in to change notification settings

manishmanjul77/Simulated-system-for-automation

Repository files navigation

Simulated Environment For Automation

A team project by Manish Manjul, Aagam Jain and Vineet Goyal.
A web simulated environment/portal for users which is used for learning of artificial intelligence techniques using the virtual hardware set of sensors and actuators.
This projects includes the concept of Object detection, Deep learning and Web development along with cloud server operations.
The virtual environment deals the robotic processing in form of colour recognition, multi-class and binary object recognition, real-world results after sensor’s input calculation.
The hardware based simulation is based on EV3 Core set and Raspberry Pi along with Pixy 2 Camera for virtually image recognition.
Multiclass classification on object detection by CNN and drag and drop functionality of virtual hardware.

Installation

Basic pip commands for installing libraries. Python 3.8 and above is recommended.

Requirements

Numpy
Pandas
Keras(2.2)
OpenCV
Pillow
Tensorflow(2.0)
Sklearn

Screenhots

Screenshot (160) Screenshot (161) Screenshot (162)

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update the tests as appropriate.

License

MIT

About

The hardware-based simulation is based on EV3 Core set and Raspberry Pi along with Pixy 2 Camera for virtually image recognition by CNN with drag and drop functionality of virtual hardware.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published