Recent development in computer vision has enabled exciting new technologies like self-driving cars, gesture recognition, and machine vision. The processing power required to create computer vision models was a barrier of entry for those interested in exploring this technology. However, this is no longer the case with pre-trained models today.
Instead of training your own model from scratch, you can build on existing models and fine-tune them for your own purpose without requiring as much computing power.
In this tutorial, we’re going to get our hands dirty and train our own corgi detector using a pre-trained SSD MobileNet V2 model.
This tutorial is based on Anaconda virtual environment with Python 3.6.
Install Tensorflow using the following command:
If you have a GPU that you can use with Tensorflow:
$ pip install tensorflow-gpu