DCGAN.torch

DCGAN.torch is an open-source implementation of Deep Convolutional Generative Adversarial Networks using the Torch7 machine learning framework. It allows developers to train image generators that create synthetic pictures from random latent vectors. The project follows the architecture introduced in the DCGAN research paper and includes configurable generator and discriminator networks. Users can train models with CelebA, LSUN, ImageNet, or custom image datasets. Pretrained generators support synthetic image creation and exploration of learned visual representations. Additional scripts enable latent space interpolation and vector arithmetic between generated images. The software supports NVIDIA GPU acceleration through CUDA and cuDNN, with optional browser-based training visualization. It serves as a historical research implementation of convolutional generative modeling.