The inspiration behind this project is to find an automatic method for segregating by classifying the waste into a different type of waste by Machine Learning.
What it does
The web app inputs an image from the user and then classifies the image into a category out of 6 for which we have trained the model.
How we built it
We built it using TensorFlow, python, streamlit. The model we are using is VGG16 and the dataset is a Kaggle dataset.
Challenges we ran into
The first challenge we ran into was streamlit. It was our first time using streamlit and also we were only 2 members in the team.
Accomplishments that we're proud of
We are proud of the fact that we completed the project, and were able to run it.
What we learned
We learned Streamlit which has a very good feature of markdown and minimalizes the website code.
What's next for WASCA
The next step for WASCA is to add more waste categories and also improve the model used for classifying the waste.