FloraFy

WINNER: Best Use of Google Cloud by MLH

What it does:

FloraFy employs AI and image recognition, trained on a diverse dataset, to instantly identify flowers from user-submitted images. Users can mark the flower's location on a global map using the Google Maps API, creating a valuable biodiversity database accessible to all.

How we built it:

We built FloraFy by training our image recognition model using a comprehensive dataset. The integration with Google Maps API enabled seamless mapping functionalities, allowing users to geotag their flower discoveries.

Challenges we ran into:

A significant challenge was testing the model during its training phase, leading to extended waiting times. Balancing accuracy and efficiency was crucial to delivering a seamless user experience.

Accomplishments that we're proud of:

We're proud of creating FloraFy, a tool that bridges technology and environmental conservation. Building a functional system integrating AI and geolocation services was a significant achievement, fostering community engagement in preserving biodiversity.

Built With

CSS Firebase Flask Google Cloud Google Maps API HTML JavaScript Keras Matplotlib NumPy Pandas Pickle Python Scikit-learn TensorFlow tqdm