Inspiration
Only 9% of plastic waste is recycled in Canada and similarly only 1/10th of solid waste is recycled in the United States.
What it does
Using machine learning and computer vision we are able to accurately classify waste into 7 different categories (cardboard, paper, metal, glass, plastic, organic, and trash). The machine learning algorithm I trained was able to achieve 90% correct classification of waste.
How I built it
Cross Platform Mobile App
The mobile app was built using React Native in the front end and using a Flask server for the backend.
Machine Learning Algorithm
This algorithm was built using the TensorFlow and Keras frameworks.
Accomplishments that I'm proud of
I am proud of the accuracy that I was able to achieve in the machine learning algorithm. I am also proud of the smooth user interface that I was able to develop in React Native.
What I learned
Multiclass image classification.
Computer vision
React Native
What's next for ReGreen
Built With
- docker
- javascript
- jupyter
- keras
- maps-api
- python
- react-native
- tensorflow
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