AI for Food Detection

16 Feb. 20
769 VIEWS

“Four simple ways to fight diabetes/Obesity: Go for regular medical check-ups; Exercise more; Watch your diet, and Cut down on soft drinks.” – Singapore PM Lee Hsien Loong (Nvidia Research paper)

Increase in obesity rates associated with poor nutrition in countries worldwide has encouraged numerous researchers to develop mobile applications or online tools that promote a healthier lifestyle.

NutriChecker, an AI driven mobile app developed by Let’s Nurture, is an easy to use wellness tracker for individuals and families. When a user points his smartphone camera to a plate containing his/her meal, the app instantly recognizes the meal along with different Ingredients.

What is the primary requirement to start working on Image classification problems?

The answer is “Data”. In the world of Big Data, you can find thousands of images online which can be useful for us as labelled Data. We’ve used Food101 Datasets from Kaggle.

In the paper, Food-101 – Mining Discriminative Components with Random Forests, they introduce the Food-101 dataset. There are 101 different classes of food, with 1000 labelled images per class available for supervised training.

How CNN actually see the images?

A CNN (convolutional neural network or ConvNet) is one of the most used and effective algorithms for deep learning, in which a model learns to perform classification tasks directly from images, video, text, or sound.

In the past couple of years, cutting edge technology has started to become available to the software development community. Industrial strength packages such as Tensorflow have given us the same building blocks that Google uses to write deep learning applications for embedded/mobile devices to scalable clusters in the cloud and stochastic optimizers that make efficient applications possible.

 
On top of all of this, user-friendly APIs such as Keras that abstract away some of the lower-level details and allow us to focus on rapidly prototyping a deep learning computation graph.

Images with their true classes

 

Our Artificial intelligence has been trained on diets from the global and accuracy constantly improves as new cuisine images are added to the database.

Why choose Let’s Nurture for Image classification?

Let’s Nurture is an ISO 9001:2015 affirmed site improvement organization in India, USA, Canada, Australia, UK, and Singapore. We have been offering Python development services for over 10+ years. We have a separate team of seasoned AI engineers,with experience in working for 15+ Diverse industry projects.

If you want to know more about our skills and our ideas behind, then why wait? Get in touch with us. Reach us at info@letsnurture.com. We would be glad to stroll with you.

Author

Lets Nurture
Posted by Lets Nurture

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