Use OpenCV to count the number of occurrences of an object such faces or bananas

Search for recipes by image recognition of food ingredients using food2fork recipe api and CoreML. App built using MVP and Clean architecture. Unit tests with Quick, Nimble and Mockingjay.

SeeFood - Imagine a world where your food is so visible, even Erlich Bachman would say, 'Whoa, that's some next-level transparency!' It's like having a front-row seat to a culinary show where your meals are always in plain sight. No more sneaky food—just pure, unfiltered deliciousness!

Cloud computing miniproject

Seefood Android application

its like Shazam for Food!!! Model trained using tensorflow and deployed as tfjs model with reactjs.

NotHotDog using Convolutional Neural Network.It achieved about 79% accuracy with only 800 images.

Shazam for Food

Remember silicon valley's seefood app? I trained a neural network binary classifier using tensorflow to recognize hot dog. Because.., why not?

It's shazam for food but only hotdogs (from HBO's Silicon Valley) , made using transfer learning ( Densenet121)

Identify food item present in an image

Repo for the ML model that classifies whether an image is a hotdog or not.

An Image Recognition using Vision and CoreML from Silicon Valley

Silicon Valley copy app that detects if an object is a hotdog or not