Not intented to be replicated. Please contact if you wish to use any part of this project.

Thanks to hamza372 for the image classification template via Udemy

In Singapore, the tropical location has led to the flourishing of a diverse variety of unique flora and fauna. With the increase in hobbyists as well as professional botanists, automatic identification of plant species has proven to be a useful tool to help bridge the botanical taxonomic divide. Plant recognition systems that currently exist cater to a global perspective and perform poorly on plant species native to Singapore. These systems also perform identification using preexisting manually labelled plant databases and perform poorly on plants in real-world conditions. Furthermore, these systems are limited in their features and lack user interactivity aspects. Thus, in this research, the focus is on creating a highly accurate and robust Image classification model capable of identifying various plant species using Machine Learning techniques. This is then implemented as a feature in an interactive, mobile application. The mobile application also provides other features such as information on the identified plant and information on nearest nature parks using the NParks dataset. Thus, this mobile application provides a rapid, accurate and precise tool for the identification of Singapore's rich plant life, that can be used easily for a wide range of audience.