https://github.com/athari22/face-generation
In this project, I defined and train a DCGAN on a dataset of faces. This project is part of the deep learning nanodegree program at udacity. Overview The project is broken down into a series of tasks from loading in data to defining and training adversarial networks. And visualize the results of trained Generator generated samples that look like fairly realistic faces with small amounts of noise.
https://github.com/athari22/face-generation
dataset dcgan deep-learning face-recognition gan generative-adversarial-network jupyter-notebook python pytorch visualization
Last synced: 8 months ago
JSON representation
In this project, I defined and train a DCGAN on a dataset of faces. This project is part of the deep learning nanodegree program at udacity. Overview The project is broken down into a series of tasks from loading in data to defining and training adversarial networks. And visualize the results of trained Generator generated samples that look like fairly realistic faces with small amounts of noise.
- Host: GitHub
- URL: https://github.com/athari22/face-generation
- Owner: Athari22
- Created: 2022-02-05T18:50:33.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2023-01-02T11:39:53.000Z (almost 3 years ago)
- Last Synced: 2024-12-30T20:15:57.457Z (10 months ago)
- Topics: dataset, dcgan, deep-learning, face-recognition, gan, generative-adversarial-network, jupyter-notebook, python, pytorch, visualization
- Language: Jupyter Notebook
- Homepage:
- Size: 1.71 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Face-Generation
In this project, I defined and train a DCGAN on a dataset of faces. This project is part of the [deep learning nanodegree program at udacity](https://www.udacity.com/course/deep-learning-nanodegree--nd101).
# Overview
The project is broken down into a series of tasks from loading in data to defining and training adversarial networks. And visualize the results of trained Generator generated samples that look like fairly realistic faces with small amounts of noise.
# Dataset
I used the CelebFaces Attributes [Dataset (CelebA)](http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html) to train adversarial networks.