eswar3/face-generation-using-gan

Project from Deep Learning Nanodegree of Udacity

Face Generation

Project Overview

In this project, I have built and trained a DCGAN on a dataset of human faces. The goal of this project is to get a generator network to generate new images of faces that look as realistic as possble. Check the images at the end of the notebook to see the final results

Project Instruction

Instruction

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

   	git clone https://github.com/eswar3/face-generation-using-GAN.git
   	cd face-generation-using-GAN
   

2. Open the face_generation.ipynb file. Of course, you can find HTML version of the file.

   	jupyter notebook face_generation.ipynb
   

3. Read and follow the instructions in the jupyter notebook.

4. This repository does not include the dataset. You can find the instruction in notebook on how to downlaod it.

Project Information

Contents

• Pre-processed Data
• Define the Model
  • Discriminator
  • Generator
  • Build complete network
• Discriminator and Generator Losses
• Optimizers
• Training
• Generator samples from training

Libraries

• tensorflow (Generator and Discriminator)

Accelerating the Training Process

For training the model I recommend you to use a GPU.

Amazon Web Services

You can use Amazon Web Services to launch an EC2 GPU instance. (This costs money!)