whichFlower : a flower species recognition app using tensorflow/keras and React-Native
As a passionate person about computer vision (CV), I came to know that model deployment is also important in model development process because the usefulness of a model is measured by the satisfaction of end users. In a previous project I named DEmoClassi (Demographic (age, gender race) and Emotion (happy, neutral, angry, ...) Classification) I tried to turned my trained models in a standalone python module that can be run on windows/Linux using OpenCV. You can check it here.
In this new project I decided to give mobile technologies a try. Today the models are migrating more and more to the edge devices (mobile, sensors, ... IOT in general). So I started by learning React-Native, a cross-platform mobile development framework developed by Facebook. The course is available on youtube, it is a little bit long, but it worth learning it.
The end goal for me was to combine my 2 passions, CV and programming into another project : this time I opted for CV model training and deployment on mobile device of a flower species recognition app I called, with no suspens, WhichFlower.
Below is a short animated demo showing the prediction process using the app :
Here is the link describing my approach from exploratory data analysis to model deployment in the app.