The goal of this project is to create an algorithm to classify 5 types of flowers.
Dataset to be trained contains 3670 images, that shall be used for training and testing the model.
Transfer learning is a technique that allows the use of some state-of-the-art CNN classifiers such as VGG, to create our own model.
In this study, I have used VGG, a model created with over 10 thousand images as features abstractor for the classification.
In this project we shall find, besides the datasets, the following documents:
- Data Visualization & Preparation
- Model โ Transfer Learning VGG
This project has been undertaken complying with a code of ethics
I provide the environment used to run this code.
This project is done thanks to what I learnt at Udacity
This project is under Copyright ยฉ 2019 Josep Maria Niubo. It is free software, and may be redistributed under the terms specified in the LICENSE file