♻️ Inspiring eco-consciousness in students through waste classification and educational resources
RecycleRight is split up into 3 seperate parts.
/notebook: the Jupyter Notebook which trains the ML model on the given dataset.
/server: the Python Flask API which classifies images using the ML model.
/client: the Next.js frontend that users interact with.
First, clone the github repository and unpack it to the working directory:
git clone https://github.com/joeymalvinni/RecycleRight.git
cd RecycleRightInstall all Next.js dependencies.
npm installFrom here, you can either run the developement server to test out the frontend or build for production using npm run build.
Install using the requirements file.
pip install -r requirements.txtRun the Jupyter Notebook to create the model.keras file. Here are some images taken from the notebook:
Results for training and validation loss/accuracy over time.
Final accuracy of the model.
MIT License
Copyright (c) 2023 Joey Malvinni
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.