Inspiration
What it does
Snap or upload a picture of a plastic code Install the PWA on your phone for easy access Search for specific item to know how to dispose of it Learn how to recycle effectively using AI Keep track of how many plastic items you've recycled Change your location for specific advice and much more to come - all for free & no sign in needed!
How we built it
The model was trained on image examples of the 7 different resin codes, the data for this can be found in ml/seven_plastics. It is a combination of the following Kaggle Dataset and images collected by the authors and contributors. The final model was trained using TensorFlow's EfficientNet implementation, the model weights were frozen for transfer learning, so the model could learn the resin codes faster! The model was trained in Python on a GPU-powered machine, for faster training! You can find the training script in ml/train.py and try it for yourself, there you will see that different meta architectures and parameters were experimented with before arriving at the final model.
Challenges we ran into
Faced issues for managing a large dataset and how to efficiently use that
Accomplishments that we're proud of
Worked on a real world project and successfully completed it
What we learned
Learned how to work on real world data
What's next for EcoSnap
Can increase Scalability and Robustness
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