# awentzonline/image-analogies

Generate image analogies using neural matching and blending.

Repository: https://github.com/awentzonline/image-analogies
Canonical: https://ross.abutalabs.com/products/image-analogies
Language: Python
License: MIT
License Family: permissive
Last push: 2022-11-22T01:02:52+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3839, "days_push": 1381, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3502, forks 280 (observed 2026-08-28T04:08:07.578239+00:00)

## What it is
A Python library implementing neural image analogies using VGG16 feature maps with PatchMatch-based matching and blending, based on the 'Image Analogies' paper. It generates image transformations by learning the relationship between a pair of images and applying it to a new image.

## Use cases
- transfer a texture or style from one image pair to a new image
- apply a seasonal color transformation to photos
- generate stylized skull or artistic effects on portraits
- perform neural style transfer with patch-based blending
- experiment with Markov Random Field image synthesis

## When to choose
- you want image analogy or style transfer effects using VGG16 features
- you need a Python/Keras implementation with GPU or CPU support
- you want PatchMatch-accelerated patch matching for image synthesis

## When to avoid
- you need actively maintained software with recent framework compatibility
- you want modern style transfer models like diffusion-based approaches
- you need a plug-and-play tool without downloading VGG16 weights and configuring Keras backends

## Facets
- artifact type: library
- maturity: maintenance
- function: image-processing, deep-learning, machine-learning
- domain: image-processing, deep-learning, computer-vision
- platform: python, cross-platform
- tags: neural-style-transfer, image-analogies, vgg16, patchmatch, keras, texture-synthesis, gpu

## Member repositories
- awentzonline/image-analogies (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:07.578239+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 2026-08-29T18:35:47.526924+00:00, confidence not recorded.
  - readme: https://github.com/awentzonline/image-analogies (fetched 2026-08-28T04:08:07.578239+00:00, sha 55820ecfb98e)
- Data as of 2026-08-30T08:39:29.467469+00:00.