Fruit Nutrition

Inspiration

We were inspired to create the Fruit Classification lens as we wanted to provide users with a quick and convenient way to learn about the nutritional values of their favorite fruits.

What it does

The Fruit Classification lens uses a custom machine learning model to identify various types of fruits and then displays the nutrient values such as protein, iron, and calcium in an easy-to-read format. By simply scanning the fruit with their camera, users can quickly learn about the health benefits of different types of fruits.

How we built it

We started by collecting and labeling a large dataset of fruit images. We then trained a custom machine learning model using this dataset and deployed it on Lens Studio. We utilized the model to identify various types of fruits and then used an API to fetch the nutritional information for each type of fruit.

Challenges we ran into

One of the biggest challenges we faced was collecting a diverse and high-quality dataset of fruit images. We also had to fine-tune the machine learning model to improve its accuracy and avoid misclassification of similar-looking fruits.

Accomplishments that we're proud of

We are proud of being able to build a lens that makes it easy for people to access important information about the foods they eat. We believe that this will help people make better choices and lead healthier lives.

What we learned

We learned about the importance of collecting a diverse and high-quality dataset when training machine learning models. We also gained experience in deploying custom machine learning models on Lens Studio and integrating them with APIs to fetch relevant information.

What's next for Fruit Nutrition

Currently it supports only some fruits only. In the future, we plan to expand the lens to include more types of fruits and nutritional information, as well as integrating it with a database of recipes for healthy fruit-based meals. We also plan to explore the possibility of integrating the lens with wearable devices and mobile apps to provide users with a more comprehensive health and nutrition tracking experience.

Built With

• javascript
• machine-learning