# graphific/DeepDreamVideo

implementing deep dream on video

Repository: https://github.com/graphific/DeepDreamVideo
Canonical: https://ross.abutalabs.com/products/deepdreamvideo
Language: Python
License: GPL-2.0
License Family: copyleft
Last push: 2022-07-20T21:13:54+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": 4077, "days_push": 1505, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2109, forks 277 (observed 2026-08-28T04:06:14.107554+00:00)

## What it is
A Python-based command-line tool that applies Google's DeepDream algorithm to videos by extracting frames, running a pretrained deep neural network on each frame with continuity blending, and reassembling them. It includes shell scripts for frame extraction via ffmpeg, avconv, or mplayer and GPU/CPU benchmarking guidance.

## Use cases
- apply deepdream hallucination effects to a movie clip
- create trippy deep dream videos from any video file
- process video frames with a pretrained neural network
- generate psychedelic video art with deep learning
- run deepdream on frames with temporal continuity
- benchmark deepdream processing on GPU vs CPU

## When to choose
- you want the classic DeepDream effect applied to an entire video with frame-to-frame continuity
- you have a GPU and are comfortable with older Python/Caffe-based deep learning setups
- you want a scriptable pipeline from raw video to dream-processed output

## When to avoid
- you need modern, maintained tooling with current framework support (PyTorch/TensorFlow)
- you only want to deepdream single images
- you need fast processing on CPU-only machines, as it can take days for short videos

## Facets
- artifact type: cli-tool
- maturity: maintenance
- function: image-processing, video-processing, deep-learning, cli
- domain: deep-learning, computer-vision, media, artificial-intelligence
- platform: python, cli
- tags: deepdream, neural-style, ffmpeg, caffe, video-effects, generative-art, video, linux, gpu

## Member repositories
- graphific/DeepDreamVideo (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:14.107554+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 2026-08-30T02:53:50.800487+00:00, confidence not recorded.
  - readme: https://github.com/graphific/DeepDreamVideo (fetched 2026-08-28T04:06:14.107554+00:00, sha cb39116bcab3)
- Data as of 2026-08-30T08:39:29.467469+00:00.