Projet Name:

Flower Recognition

Description:

For several years, flower recognition in the wildlife has been an area of great interest among biologists. Recognition of flower in environments such as forests and mountains is necessary to know whether they are extinct or not. While search engines assist in searching for a flower, it lacks robustness because of the intra-class variation among millions of flower species.

The application of deep learning is rapidly growing in the field of computer vision and is helping in building powerful classification and identification models. We can leverage this power of deep learning to build models that can classify and differentiate between different species of flower as well

Given a large class of flowers, 102 to be precise. Build a flower classification model which is discriminative between classes but can correctly classify all flower images belonging to the same class. There are a total of 20549 (train + test) images of flowers. Predict the category of the flowers present in the test folder with good accuracy.

Data Source and Project Idea:

Took the dataset from a online data science challenge in this URL https://www.hackerearth.com/challenges/competitive/garden-nerd-data-science-competition/machine-learning/flower-recognition/