Implementation of an object color classifier using machine learning and a small custom dataset. This was developed for the Little Helper 7+ at Aalborg University, however it can also be run as a stand-alone application.
This was developed using classifiers which support online learning in scikit-learn
. For feature description, histograms in different colour spaces are compared.
pip3 install -r requirements --user
The utils package here is also required:https://github.com/glhr/img-utils
├── classifier.py # main file, for classifying objects
├── classifierutils.py # for loading classifier parameters and models, loading/saving the dataset
├── dataset_img # contains the images used to train the original model
├── dataset_json # dataset for different colour spaces and histogram resolutions
├── dataset_plots # images generated for documentation
├── dataset.py # for generating a JSON dataset file from the training images
├── dataset_user # images gathered through incremental learning
├── eval.py # for comparing the performance of different classifiers and parameters
├── requirements.txt
├── test # images used and generated during testing
└── test.py # for testing incremental learning