EITN35 - ML Object Detector

This is a project for training a data object detector

Training and testing an algorithm which will be used to detect persons and dogs in a tunnel.

Prerequisites

• Anaconda
• CUDA-enabled GPU

Installation

Create an Anaconda environment with the packages listed in requirements.txt

conda create --name <NAME> --file requirements.txt

Setup

Organize input frames into two separate folders, one for the training set and one for the test set. Update train_dir and test_dir in CNN_baseline.py accordingly.

Usage

CNN_baseline.py is the main file which trains a model from scratch given frames of a tunnel with objects: person, bike, dog and empty tunnel

Run the command:

python CNN_baseline.py

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 tests as appropriate.

License

MIT