Submission the Climate Change AI Hackathon 2019, Montreal, see DevPost post. We have created an application that uses Deep Learning to detect objects and classifies the method for waste management (recycling, compost, trash, hazardous).
The more we recycle, the less garbage winds up in our landfills and incineration plants. By reusing aluminum, paper, glass, plastics, and other materials, we can save production and energy costs, and reduce the negative impacts that the extraction and processing of virgin materials has on the environment. New products can be made from your recyclable waste material. It all comes back to you. Recycling gets down to one person taking action.
Built with Flask. Following this tutorial.
Run the server:
FLASK_ENV=development FLASK_APP=app.py python3.5 -m flask run
And upload pictures to try out the garbage detection AI. Example test images are in test_images.
HTMLs in khaled/YOCCO
Our image recognition models are based on pre-trained models (DenseNet121 and MobileNet, trained on ImageNet) provided by Torch and Keras. We fine-tuned MobileNet to classify garbage material based on the TrashNet data collection.
Julia Kreutzer, Salma Elmahallawy, Khaled Matloub, Kene Nnodu, Reza Filsoof