YolandaAlvarez / Face-Generation

Project for the module Generative Adversarial Networks for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

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Face-Generation

In this project, a DCGAN (Deep Convolutional Generative Adversarial Network) is defined and trained on a dataset of faces. The goal is to get a generator network to generate new images of faces that look as realistic as possible!

Example

Project Instructions

  1. Clone the repository and navigate to the downloaded folder.

  2. Download the CelebFaces Attributes Dataset (CelebA). Unzip the folder and place it in the repo, at location path/to/face-generation/data processed_celeba_small.

  3. Make sure you have already installed the necessary Python packages according to the requirements.txt in the repository.

  4. Open a terminal window and navigate to the project folder. Open the notebook using:

	jupyter notebook dlnd_face_generation.ipynb

NOTE: If the code is taking too long to run switch to running the code on a GPU.

About

Project for the module Generative Adversarial Networks for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

License:GNU General Public License v3.0


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