Welcome to the Face Generator project! This project utilizes the Deep Convolutional Generative Adversarial Networks (DCGAN) algorithm to generate realistic human faces.
The Face Generator is an artificial intelligence project that creates realistic face images using the power of Deep Convolutional Generative Adversarial Networks (DCGAN). The project provides an interactive web interface where users can explore and generate unique face images.
DCGAN, or Deep Convolutional Generative Adversarial Networks, is a class of artificial intelligence algorithms used in unsupervised machine learning. In the context of the Face Generator project, DCGAN consists of two main neural networks: the Generator (G) and the Discriminator (D). These networks work together in an adversarial manner, with the generator attempting to create realistic faces and the discriminator trying to distinguish between real and generated images. This adversarial process leads to the generation of high-quality and realistic face images.
To run this project on your local machine, follow these steps:
-
Clone the repository to your local machine:
git clone https://github.com/Mandy10k/Face-Generator.git
-
Navigate to the project directory:
cd Face-Generator -
Open the
index.htmlfile in your web browser to interact with the Face Generator. -
Explore the various sections, such as image generation, algorithm details, results, and the classification challenge.
Feel free to experiment with the Face Generator and generate unique face images!
The project is also deployed as a website. You can access it here.
Read more about the DCGAN algorithm in this blog post.