Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-05 05:53 UTC

wkentaro / labelme

Image annotation with Python. Supports polygon, rectangle, circle, line, point, and AI-assisted annotation.

PythonGPL-3.0★ 16,081 stars⑂ 3,693 forkssince May 2016View on GitHub ↗
KindCommand-line toolLibraryDesktop applicationhow this is determined
#image-annotation#python#computer-vision#annotations#deep-learning#semantic-segmentation#instance-segmentation#video-annotation#classification

wkentaro/labelme holds a health index of 90 out of 100, placing it in the Excellent band. It scores highest on Vitality (98/100) and lowest on Security (62/100). It was last updated today. A single contributor accounts for most of its recent work.

90
overall / 100
Excellent

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

90
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 76 is calibrated to 90 on the published index scale (record calibration 2026-08-02).

Ownership

Kentaro WadaPersonal account
2,544 followers355 public repossince May 2013Self-employed

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIlabelme7.0.449,05723223 days ago

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

98Exceptional · 21% of overall

Development activity

96Exceptional
How it's scored
36/36Push recency — last push 0 days ago
32.5/36Commit cadence — 47/52 weeks with commits
18/18Commit volume — 1,675 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 30 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year1,675
human_commit_share1
days_since_last_push0
active_weeks_last_year47

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 100 releases published
36/36Release recency — latest release 23 days ago
27/27Release cadence — a release every ~9.1 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count100
latest_release_tagv7.0.4
releases_from_tagsno
days_since_latest_release23
mean_days_between_releases9.1
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Signed-Releases. Remaining weights renormalized.

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

75Good · 17% of overall

Popularity & adoption

97Exceptional
How it's scored
60/60Stars — 16,081 stars
25/25Forks — 3,693 forks
12/15Watchers — 146 watchers
Inputs used
forks3,693
stars16,081
watchers146
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

50Moderate
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (GPL-3.0)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges3
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateno

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

67Good · 23% of overall

Maintainer resilience (bus factor)

35Weak
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
2.5/22.5Commit distribution — top contributor authored 89% of commits
13.5/13.5Contributor breadth — 64 contributors
10/10OpenSSF Scorecard: Contributors — project has 22 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled64
top_contributor_share0.891

Issue & PR responsiveness

71Good
How it's scored
35.2/42Issue resolution — 84% of issues closed
23.2/30PR acceptance — 945/1,222 decided PRs merged
13/13Newcomer PR acceptance — 2/2 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/17 approved changesets -- score normalized to 0
Inputs used
merged_prs945
open_issues148
closed_issues772
prs_merged_7d44
prs_decided_7d46
prs_merged_30d56
prs_decided_30d58
issue_closed_ratio0.839
closed_unmerged_prs277
first_time_authors_30d1
first_time_prs_merged_30d2
first_time_prs_decided_30d2

Ownership & stewardship

74Good
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
24.5/25Owner reach — 2,544 followers of wkentaro
25/25Track record — 355 public repos, account ~13 yr old
Inputs used
followers2,544
owner_typeUser
is_verified—
owner_loginwkentaro
public_repos355
account_age_days4,843
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 23 days ago
20/20Version history — 232 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packageslabelme
ecosystemspypi
any_deprecatedno
min_days_since_publish23

Engineering Quality

Are baseline engineering and documentation practices in place?

77Good · 19% of overall

Engineering practices

68Good
How it's scored
24/24CI workflows — 5 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 17 out of 17 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://labelme.io
10/10Repository description
10/10Topics — 9 topics
0/10Wiki
Inputs used
topicsimage-annotation, python, computer-vision, annotations, deep-learning, semantic-segmentation, instance-segmentation, video-annotation, classification
has_wikino
homepagehttps://labelme.io
docs_sitehttps://labelme.io
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

62Moderate · 16% of overall

Security posture

53Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
2.2/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 17 out of 17 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/17 approved changesets -- score normalized to 0
2.5/2.5Contributors — project has 22 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 30 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
4.5/7.5Vulnerabilities — 4 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5.3
Excluded from scoring (no data or not applicable): Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages44
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:labelme@7.0.4 runtime dependency closure — what installing the published package pulls in — 44 packages. Reachability is not analyzed.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

69Good · 4% of overall

Agent context & guidance

85Excellent
How it's scored
45/45Agent instructions — AGENTS.md, CLAUDE.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 99 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.99
agent_instruction_filesAGENTS.md, CLAUDE.md
agent_instruction_max_bytes888

Verify loop (build / test / typecheck)

50Moderate
How it's scored
18/18One-command bootstrap — Makefile
22/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

54Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
54.3/55Manageable file sizes — 2/160 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes117,396
source_files_sampled160
oversized_source_files2

Machine-readable interfaces

100Exceptional
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — examples
Inputs used
example_dirsexamples
has_mcp_signalno
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

16,081GitHub stars
64contributors
1,675commits, last 12 months
0days since last push
100releases
1bus factor
148open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 3,693 ⇿
0Stars
3,693Forks
43Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

Only the most recent history is shown — this repository exceeds the collection window, so the earliest history is not captured.

2,5002,7503,0003,2503,5003,7503,693102023-012024-102026-08
Major 2Minor 13Patch 23

Each point covers 4 days.

OpenSSF Scorecard 5.3 / 10
5.3aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-08-05 05:53 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests17 out of 17 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/17 approved changesets -- score normalized to 0
10Contributorsproject has 22 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 30 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
6Vulnerabilities4 existing vulnerabilities detected
Direct dependencies 13
RegistryPackageVersion constraintManifest
PyPIimgviz>=2.0.0pyproject.toml
PyPIloguru>=0.7pyproject.toml
PyPImatplotlib>=3.7pyproject.toml
PyPInatsort>=7.1.0pyproject.toml
PyPInumpy>=1.24pyproject.toml
PyPIonnxruntime>=1.23.2pyproject.toml
PyPIosam>=0.4.0pyproject.toml
PyPIpillow>=2.8pyproject.toml
PyPIpyside6>=6.8pyproject.toml
PyPIscipy>=1.8pyproject.toml
PyPIscikit-image>=0.21pyproject.toml
PyPItifffile>=2024.1.30pyproject.toml
PyPIruamel-yaml>=0.18pyproject.toml
All dependencies 114

Full resolved dependency set from the GitHub dependency graph: 13 direct and 101 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIimgviz2.0.0direct
PyPIloguru0.7.3direct
PyPImatplotlib3.10.8direct
PyPInatsort8.4.0direct
PyPInumpy2.4.4direct
PyPIonnxruntime1.24.4direct
PyPIosam0.4.0direct
PyPIpillow12.3.0direct
PyPIpyside66.11.1direct
PyPIruamel-yaml0.19.1direct
PyPIscikit-image0.26.0direct
PyPIscipy1.17.1direct
PyPItifffile2026.4.11direct
PyPIannotated-doc0.0.4indirect
PyPIannotated-types0.7.0indirect
PyPIasttokens3.0.1indirect
PyPIbeautifulsoup44.14.3indirect
PyPIcertifi2026.2.25indirect
PyPIcffi2.0.0indirect
PyPIcharset-normalizer3.4.7indirect
PyPIclick8.3.2indirect
PyPIcmap0.7.2indirect
PyPIcolorama0.4.6indirect
PyPIcontourpy1.3.3indirect
PyPIcoverage7.13.5indirect
PyPIcryptography48.0.1indirect
PyPIcycler0.12.1indirect
PyPIdecorator5.2.1indirect
PyPIdistro1.9.0indirect
PyPIdocutils0.22.4indirect
PyPIexecnet2.1.2indirect
PyPIexecuting2.2.1indirect
PyPIfilelock3.28.0indirect
PyPIflatbuffers25.12.19indirect
PyPIfonttools4.62.1indirect
PyPIgdown6.0.0indirect
PyPIid1.6.1indirect
PyPIidna3.15indirect
PyPIimageio2.37.3indirect
PyPIiniconfig2.3.0indirect
PyPIipython9.12.0indirect
PyPIipython-pygments-lexers1.1.1indirect
PyPIjaraco-classes3.4.0indirect
PyPIjaraco-context6.1.2indirect
PyPIjaraco-functools4.4.0indirect
PyPIjedi0.19.2indirect
PyPIjeepney0.9.0indirect
PyPIkeyring25.7.0indirect
PyPIkiwisolver1.5.0indirect
PyPIlazy-loader0.5indirect
PyPImaison2.0.2indirect
PyPImarkdown-it-py4.0.0indirect
PyPImatplotlib-inline0.2.1indirect
PyPImdformat1.0.0indirect
PyPImdformat-frontmatter2.0.10indirect
PyPImdformat-gfm1.0.0indirect
PyPImdit-py-plugins0.5.0indirect
PyPImdurl0.1.2indirect
PyPImore-itertools11.0.2indirect
PyPImpmath1.3.0indirect
PyPInetworkx3.6.1indirect
PyPInh30.3.4indirect
PyPIpackaging26.1indirect
PyPIparso0.8.6indirect
PyPIpexpect4.9.0indirect
PyPIplatformdirs4.9.6indirect
PyPIpluggy1.6.0indirect
PyPIprompt-toolkit3.0.52indirect
PyPIprotobuf7.34.1indirect
PyPIptyprocess0.7.0indirect
PyPIpure-eval0.2.3indirect
PyPIpycparser3.0indirect
PyPIpydantic2.13.2indirect
PyPIpydantic-core2.46.2indirect
PyPIpygments2.20.0indirect
PyPIpyparsing3.3.2indirect
PyPIpyside6-addons6.11.1indirect
PyPIpyside6-essentials6.11.1indirect
PyPIpysocks1.7.1indirect
PyPIpytest9.0.3indirect
PyPIpytest-cov7.1.0indirect
PyPIpytest-qt4.5.0indirect
PyPIpytest-xdist3.8.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpywin32-ctypes0.2.3indirect
PyPIreadme-renderer44.0indirect
PyPIrequests2.33.1indirect
PyPIrequests-toolbelt1.0.0indirect
PyPIrfc39862.0.0indirect
PyPIrich15.0.0indirect
PyPIruff0.12.12indirect
PyPIruyaml0.91.0indirect
PyPIsecretstorage3.5.0indirect
PyPIsetuptools83.0.0indirect
PyPIshellingham1.5.4indirect
PyPIshiboken66.11.1indirect
PyPIsix1.17.0indirect
PyPIsoupsieve2.8.4indirect
PyPIstack-data0.6.3indirect
PyPIsympy1.14.0indirect
PyPItaplo0.9.3indirect
PyPItqdm4.67.3indirect
PyPItraitlets5.14.3indirect
PyPItwine6.2.0indirect
PyPIty0.0.31indirect
PyPItyper0.24.1indirect
PyPItypes-pillow10.2.0.20240822indirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspection0.4.2indirect
PyPItypos1.45.1indirect
PyPIurllib32.7.0indirect
PyPIwcwidth0.6.0indirect
PyPIwin32-setctime1.2.0indirect
PyPIyamlfix1.19.1indirect
Dependency advisories 0

Installing pypi:labelme@7.0.4 pulls in 44 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

No known advisories affect the assessed dependencies.

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

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Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.31.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.