dariasil / image_tutorial

This is a tutorial for Chapter 14 - Image Analytics in Marketing in the Handbook of Marketing Research. Dzyabura D., El Kihal S., Peres R. (2021) Image Analytics in Marketing. In: Homburg C., Klarmann M., Vomberg A.E. (eds) Handbook of Market Research. Springer, Cham. https://doi.org/10.1007/978-3-319-05542-8_38-1 A PDF copy of the paper is also attached to the project

image_tutorial

Introduction

A tutorial for some of the methods described in Dzyabura, El Kihal and Peres (2021), "Image Analytics in Marketing", in The Handbook of Market Research, Ch 14, Editors: Christian Homburg, Martin Klarmann, Arnd Vomberg. Springer, 2021. March 2021. https://doi.org/10.1007/978-3-319-05542-8_38-1 We thank Efrat Naor for her great contribution to this tutorial.

Content

The project includes:

• a Python notebook (.ipynb) with the code called "Image Analytics in Marketing Code Examples-Book Chapter.ipynb”
• 3 images (“dog.jpeg”, “elephant.jpeg “, “azrieli.jpeg”) that are used in the first part of the code examples
• a folder named "convolutional_neural_network_data" containing thousands of images (.jpeg) used to train the neural network classifier in the second part of the code example.

The code is written in Python 3. We recommend running the code in Jupyter Notebook via Anaconda.

Downloading the project

The images in this project (*.jpeg), exist in the repository as Git Large File Storage (LFS). Hence, using the “Download as Zip” button will not download the images properly, so there is a need to download the repository through the command line.

First, download and install the Git command line extension from the git large file storage website {https://git-lfs.github.com/).

Once downloaded and installed, set up Git LFS for your user account by running in the Git Bash Terminal:

git lfs install

Once Git LFS is installed, you can clone a Git LFS repository as normal using:

git clone https://github.com/dariasil/image_tutorial.git