# tylin/coco-caption

Repository: https://github.com/tylin/coco-caption
Canonical: https://ross.abutalabs.com/products/coco-caption
Language: Jupyter Notebook
License: NOASSERTION
License Family: other
Last push: 2024-05-13T12:04:29+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": 4187, "days_push": 842, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1224, forks 544 (observed 2026-08-28T04:04:02.792241+00:00)

## What it is
The official evaluation code for the Microsoft COCO image captioning benchmark, implementing metrics such as BLEU, METEOR, ROUGE-L, CIDEr, and SPICE. It includes annotation files, demo scripts, and a Python package (pycocoevalcap) for scoring generated captions against reference captions.

## Use cases
- evaluate image captioning model outputs on COCO
- compute BLEU, METEOR, ROUGE-L, CIDEr, and SPICE scores for captions
- benchmark caption generation against MS COCO 2014 validation set
- score machine-generated captions against human references
- run caption evaluation in a research pipeline

## When to choose
- you need standard COCO caption metrics for a paper or benchmark
- you are evaluating image captioning or multimodal generation models
- you want the official reference implementation of CIDEr and SPICE

## When to avoid
- you need Python 3 support out of the box (code targets Python 2.7 and Java 1.8)
- you are evaluating tasks other than image captioning
- you want a maintained library with active development

## Facets
- artifact type: library
- maturity: maintenance
- function: nlp, machine-learning, benchmarking
- domain: computer-vision, machine-learning
- platform: python
- tags: image-captioning, evaluation-metrics, coco-dataset, bleu, cider, spice, meteor, rouge, natural-language-processing, linux, macos

## Member repositories
- tylin/coco-caption (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:02.792241+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 2026-08-30T06:15:30.000408+00:00, confidence not recorded.
  - readme: https://github.com/tylin/coco-caption (fetched 2026-08-28T04:04:02.792241+00:00, sha 12e026ef8dca)
- Data as of 2026-08-30T08:39:29.467469+00:00.