Real-Time-Object-Detection-Recognition

Code for realtime object detection and recognition . The model is trained on caffe and uses OpenCV. The code and it's testing was done on a CPU .

Getting Started

• Download MobileNetSSD_deploy.caffemodel and MobileNetSSD_deploy.prototxt.txt for real time object detection.
• Host all the files on the same directory
• It is always a good practice to create a virtual environment for every project , not compuslory but ensures that dependencies are not hampered elsewhere.
• It contains more than around 40+ objects trained model.

Installing

pip install -r requirements.txt

Deployment

• Tested on
  • Intel i3 6006U CPU
  • OS : Linux Fedora 28
  • 4GB RAM

Best Results based on number of objects detected

To Run : python objdet.py -p [PATH TO PROTOTXT FILE] -m [PATH TO CAFFEMODEL DEPLOY] -c [CONFIDENCE]

Contributing

If you have any :

• Pull Requests : make one, work is always appreciated.
• Issues : they are what help us improve, do create if any.
• Idea : feature requests etc.
• Suggestions : The world of Open Source

Authors

• Ashwin Phadke

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Acknowledgments

• Amazing Ad.
• Open Source Community.
• Last mile contributors.