# happynear/caffe-windows

Configure Caffe in one hour for Windows users.

Repository: https://github.com/happynear/caffe-windows
Canonical: https://ross.abutalabs.com/products/caffe-windows
Language: C++
License: NOASSERTION
License Family: other
Last push: 2018-07-15T03:09:52+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 4173, "days_push": 2971, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1309, forks 637 (observed 2026-08-28T04:04:19.475239+00:00)

## What it is
A Windows-specific fork of the Caffe deep learning framework with preconfigured Visual Studio project files, enabling users to build Caffe on Windows in about an hour. It supports CPU-only and CUDA/cuDNN builds, plus optional Python bindings.

## Use cases
- build caffe on windows with visual studio
- train convolutional neural networks on windows with cuda
- set up deep learning framework without linux
- use caffe python bindings on windows
- cpu-only deep learning build for windows

## When to choose
- you must use Windows and specifically need Caffe
- you have legacy Caffe models or prototxt files to run on Windows
- you need a Visual Studio-based deep learning build with CUDA/cuDNN

## When to avoid
- starting a new deep learning project - use PyTorch or TensorFlow instead
- you need recent CUDA versions or modern GPUs
- you need active maintenance, security updates, or community support

## Facets
- artifact type: framework
- maturity: abandoned
- function: deep-learning, machine-learning, gpu-computing
- domain: deep-learning, machine-learning, computer-vision, windows
- platform: windows, cpp, python
- tags: caffe, cuda, cudnn, windows-build, neural-networks, visual-studio, gpu

## Member repositories
- happynear/caffe-windows (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:19.475239+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 2026-08-30T04:49:59.455891+00:00, confidence not recorded.
  - readme: https://github.com/happynear/caffe-windows (fetched 2026-08-28T04:04:19.475239+00:00, sha fde98fe7f2df)
- Data as of 2026-08-30T08:39:29.467469+00:00.