# soumith/dcgan.torch

A torch implementation of http://arxiv.org/abs/1511.06434

Repository: https://github.com/soumith/dcgan.torch
Canonical: https://ross.abutalabs.com/products/dcgantorch
Language: Lua
License: NOASSERTION
License Family: other
Last push: 2021-08-02T01:46:39+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3927, "days_push": 1858, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1488, forks 410 (observed 2026-08-28T04:04:52.130183+00:00)

## What it is
A Torch (Lua) implementation of the DCGAN paper for training deep convolutional generative adversarial networks that generate images. It supports training on datasets like Celeb-A, LSUN, and ImageNet, plus generating samples and latent-space vector arithmetic with pre-trained models.

## Use cases
- train a GAN to generate faces from the Celeb-A dataset
- generate images of bedrooms or churches with DCGAN on LSUN
- generate large artsy images from a pre-trained generator
- interpolate between samples by walking the latent space
- do vector arithmetic on images in latent space
- train an image generator on my own image dataset

## When to choose
- you specifically need the classic DCGAN architecture in Torch7
- you want to reproduce the DCGAN paper experiments
- you have legacy Torch7 infrastructure and an NVIDIA GPU

## When to avoid
- you want a maintained framework - Torch7 is deprecated
- you prefer PyTorch or TensorFlow implementations of GANs
- you only have a CPU and need fast training

## Facets
- artifact type: library
- maturity: abandoned
- function: deep-learning, machine-learning, image-processing, gpu-computing
- domain: deep-learning, machine-learning, image-processing, artificial-intelligence
- platform: lua
- tags: dcgan, gan, torch7, image-generation, generative-models, celeba, lsun, linux, macos, gpu

## Member repositories
- soumith/dcgan.torch (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:52.130183+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:33:46.117203+00:00, confidence not recorded.
  - readme: https://github.com/soumith/dcgan.torch (fetched 2026-08-28T04:04:52.130183+00:00, sha b83c2481f6f2)
- Data as of 2026-08-30T08:39:29.467469+00:00.