In this repository, I am going to generate realistic looking faces with Machine Learning. In order to do so, we are going to leverage Generative Adversarial Networks (GANs), and more specifically Deep Convolutional Generative Adversarial Networks (DCGANs). By using this repository, you will be able to successfully train a GAN to sample an infinite amount of images based on a given dataset, which in our case will be human faces.
For running this project you should install some requirements such as Anaconda.
Conda is an open source package management system and environment management system for installing multiple versions of software packages and their dependencies and switching easily between them. It works on Linux, OS X and Windows, and was created for Python programs but can package and distribute any software.
Download the latest version of miniconda that matches your system.
| Linux | Mac | Windows | |
|---|---|---|---|
| 64-bit | 64-bit (bash installer) | 64-bit (bash installer) | 64-bit (exe installer) |
| 32-bit | 32-bit (bash installer) | 32-bit (exe installer) |
Before start to work you should define an Environment on the Anaconda. You can put this command either on the terminal window such CMD or in the Anaconda Console Application.
- Linux or Mac:
conda create -n FaceGeneration python=3.6 source activate FaceGeneration - Windows:
conda create --name FaceGeneration python=3.6 activate FaceGeneration
Next step is installing PyTorch and torchvision.
- Linux or Mac:
conda install pytorch torchvision -c pytorch - Windows:
conda install pytorch -c pytorch pip install torchvision
Now it is time to clone the repositort and run it.
git clone https://github.com/PooyaAlamirpour/FaceGeneration.git
cd FaceGeneration
jupyter notebook
The below image indicates the result
