# bamos/dcgan-completion.tensorflow

Image Completion with Deep Learning in TensorFlow

Repository: https://github.com/bamos/dcgan-completion.tensorflow
Canonical: https://ross.abutalabs.com/products/dcgan-completiontensorflow
Language: Python
License: NOASSERTION
License Family: other
Topics: tensorflow, deep-learning
Last push: 2017-07-18T11:08:45+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3676, "days_push": 3333, "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 1316, forks 382 (observed 2026-08-28T04:04:20.817279+00:00)

## What it is
A TensorFlow implementation of semantic image inpainting using DCGANs, based on the paper 'Semantic Image Inpainting with Perceptual and Contextual Losses'. It includes a pre-trained face completion model trained on CelebA.

## Use cases
- fill in missing parts of face images with deep learning
- run semantic image inpainting with a DCGAN
- reproduce the perceptual and contextual loss inpainting paper
- complete partially occluded CelebA face images
- learn how GAN-based image completion works in TensorFlow

## When to choose
- you want a reference implementation of DCGAN-based image inpainting for research or learning
- you need to complete face images using the included pre-trained CelebA model

## When to avoid
- you need a maintained, production-ready inpainting tool for modern TensorFlow or PyTorch
- you need inpainting for general images rather than faces
- you require a permissive, clearly defined license

## Facets
- artifact type: library
- maturity: abandoned
- function: image-processing, machine-learning, deep-learning
- domain: deep-learning, computer-vision, image-processing
- platform: python
- tags: dcgan, inpainting, tensorflow, celeba, research-code, face-completion, gpu

## Member repositories
- bamos/dcgan-completion.tensorflow (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:20.817279+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 2026-08-30T04:48:27.314666+00:00, confidence not recorded.
  - readme: https://github.com/bamos/dcgan-completion.tensorflow (fetched 2026-08-28T04:04:20.817279+00:00, sha 91b31e78b29e)
- Data as of 2026-08-30T08:39:29.467469+00:00.