Making a Custom Object Detector using Pre-trained Model in Tensorflow

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.

1. Installation

This tutorial is based on Anaconda virtual environment with Python 3.6.

1.1 Tensorflow

Install Tensorflow using the following command:

$ pip install tensorflow

If you have a GPU that you can use with Tensorflow:

$ pip install tensorflow-gpu

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