# google/deepdream

Repository: https://github.com/google/deepdream
Canonical: https://ross.abutalabs.com/products/deepdream
License: NOASSERTION
License Family: other
Archived: true
Last push: 2022-10-19T06:43:24+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4081, "days_push": 1414, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, archived, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 13231, forks 3150 (observed 2026-08-28T04:11:02.670896+00:00)

## What it is
Google Research's DeepDream repository containing an IPython Notebook with sample code for generating neural network art via the Inceptionism technique. It complements the 2015 Google Research blog post and serves as a reference implementation and educational resource.

## Use cases
- generate psychedelic deepdream images from photos
- learn how neural network feature visualization works
- reproduce the inceptionism technique from the Google blog post
- experiment with convolutional network activations for art
- create trippy AI-generated artwork from my pictures

## When to choose
- you want the original reference implementation of DeepDream
- you are learning how deep neural networks visualize features
- you want a notebook-based, easy-to-follow example of neural art

## When to avoid
- you need a maintained production image-generation pipeline
- you want modern generative models like diffusion or GANs
- you need a supported library with active development

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: image-processing, machine-learning, deep-learning
- domain: artificial-intelligence, image-processing, deep-learning
- platform: python, cross-platform
- tags: deepdream, neural-network-art, ipython-notebook, inceptionism, google-research, generative-art

## Member repositories
- google/deepdream (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:02.670896+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 2026-08-29T17:13:25.394649+00:00, confidence not recorded.
  - readme: https://github.com/google/deepdream (fetched 2026-08-28T04:11:02.670896+00:00, sha a46496225fa5)
- Data as of 2026-08-30T08:39:29.467469+00:00.