akash2021 / face-generation

Using GAN on Celeberity faces to generate new faces

Face-Generation

In this project, we will use pytorch to create generative adversarial networks to generate new images of faces. We will be using the CelebFaces Attributes Dataset (CelebA) to train your adversarial network. To download the dataset click here. This is a zip file that you'll need to extract in the home directory of this notebook for further loading and processing. After extracting the data, you should be left with a directory of data processed_celeba_small/.

How training happens

#Dependencies Download the latest version of miniconda that matches your system. Install miniconda on your machine. Detailed instructions:

• Linux: http://conda.pydata.org/docs/install/quick.html#linux-miniconda-install
• Mac: http://conda.pydata.org/docs/install/quick.html#os-x-miniconda-install
• Windows: http://conda.pydata.org/docs/install/quick.html#windows-miniconda-install

For Windows users, these following commands need to be executed from the Anaconda prompt as opposed to a Windows terminal window. For Mac, a normal terminal window will work.

Git and version control These instructions also assume you have git installed for working with Github from a terminal window, but if you do not, you can download that first with the command: conda install git

Create (and activate) a new environment, named deep-learning with Python 3.6. If prompted to proceed with the install (Proceed [y]/n) type y.

Linux or Mac:

conda create -n deep-learning python=3.6
source activate deep-learning

Windows:

conda create --name deep-learning python=3.6
activate deep-learning

To install all the requirements copy the requirements in a blank text document name it as requirement.txt

Requirements to run the project

• opencv-python
• jupyter
• matplotlib
• pandas
• numpy
• pillow
• scipy
• tqdm
• scikit-learn
• scikit-image
• seaborn
• h5py
• ipykernel
• bokeh
• pickleshare
• torch

Install a few required pip packages, which are specified in the requirements text file .

pip install -r requirements.txt

Now you can start working on the project use jupyter to either load a notebook or create a new untitled norebook

Final Result