Skip to content

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 .

License

Notifications You must be signed in to change notification settings

ashwin-phadke/Real-Time-Object-Detection-Recognition

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

14 Commits
 
 
 
 
 
 
 
 

Repository files navigation

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.

About

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 .

Topics

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages