# ufoym/deepo

Setup and customize deep learning environment in seconds.

Repository: https://github.com/ufoym/deepo
Canonical: https://ross.abutalabs.com/products/deepo
Homepage: http://ufoym.com/deepo
Language: Python
License: MIT
License Family: permissive
Topics: deep-learning, jupyter, lasagne, caffe, tensorflow, sonnet, keras, theano, chainer, torch, pytorch, mxnet, cntk, dockerfile-generator, docker-image, caffe2, onnx
Last push: 2026-03-25T15:09:36+00:00

## Health v2 (maintenance only)
Score: 56/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 74, release rhythm 8, longevity 100
- inputs: {"age_days": 3232, "days_push": 161, "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 6276, forks 737 (observed 2026-08-28T04:09:41.213479+00:00)

## What it is
Deepo is a Dockerfile generator and collection of pre-built Docker images for setting up deep learning research environments. It composes modular 'Lego-like' components (CUDA, cuDNN, PyTorch, TensorFlow, etc.) into custom images with automatic dependency resolution.

## Use cases
- set up a deep learning environment in seconds
- generate a custom dockerfile with pytorch and tensorflow
- run jupyter with gpu acceleration in docker
- create a reproducible cuda and cudnn container
- build an all-in-one machine learning docker image
- resolve compatible versions of cuda python and deep learning frameworks

## When to choose
- you want a ready-made or custom Docker image with multiple deep learning frameworks preinstalled
- you need GPU (CUDA/cuDNN) support in containers with minimal configuration
- you want automatic dependency and version compatibility resolution across frameworks

## When to avoid
- you only need a single framework and prefer official framework images or pip/conda installs
- you don't use Docker or can't install the NVIDIA Container Toolkit
- you need lightweight CPU-only environments where a full image is overkill

## Facets
- artifact type: infra-config
- maturity: active
- function: deep-learning, llm-training, machine-learning, container-runtime, infrastructure-as-code, gpu-computing
- domain: deep-learning, machine-learning, gpu-computing, developer-tools
- platform: windows, python
- tags: dockerfile-generator, docker-images, cuda, cudnn, jupyter, tensorflow, pytorch, environment-setup, containers, docker, linux, macos, gpu

## Member repositories
- ufoym/deepo (main) score 56

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:41.213479+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 2026-08-29T17:46:28.708309+00:00, confidence not recorded.
  - readme: https://github.com/ufoym/deepo (fetched 2026-08-28T04:09:41.213479+00:00, sha 02f2b5256983)
  - homepage: http://ufoym.com/deepo (fetched 2026-08-29T08:43:06.044418+00:00, sha 1e4f3d9e09d0)
- Data as of 2026-08-30T08:39:29.467469+00:00.