Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-01 23:51 UTC

alessiosavi / PyRecognizer

"A neural network to rule them all, a neural network to find them, a neural network to bring them all and verify if is you !!" (Face recognition tool)

PythonMIT★ 37 stars⑂ 14 forkssince Nov 2019View on GitHub ↗

alessiosavi/PyRecognizer holds a health index of 23 out of 100, placing it in the At Risk band. It scores highest on Engineering Quality (53/100) and lowest on Vitality (22/100). It was last updated 228 days ago. A single contributor accounts for most of its recent work.

23
overall / 100
At Risk

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.

23
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 43 is calibrated to 39 on the published index scale (record calibration 2026-08-02).

Ownership

alessiosaviPersonal account
34 followers118 public repossince Sep 2017Stealth Startup

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

Metrics by category

Vitality

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

22At Risk · 21% of overall
How it's scored
3.6/36Push recencylast push 228 days ago
0/36Commit cadence0/52 weeks with commits
0/18Commit volume0 commits in the last year
0/10OpenSSF Scorecard: Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year0
human_commit_share0.59
days_since_last_push228
active_weeks_last_year0
How it's scored
16.2/27Ships releases2 version tags (no GitHub releases)
0/36Release recencylatest release 2,424 days ago
27/27Release cadencea release every ~0.6 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count2
latest_release_tagv0.3.4
releases_from_tagsyes
days_since_latest_release2,424
mean_days_between_releases0.6
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?

50Moderate · 17% of overall
How it's scored
25.2/60Stars37 stars
9.3/25Forks14 forks
1.7/15Watchers3 watchers
Inputs used
forks14
stars37
watchers3
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (MIT)
0/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges7
has_contributingno
has_issue_templateno
has_code_of_conductyes
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?

43Weak · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
0.1/22.5Commit distributiontop contributor authored 99% of commits
2.7/13.5Contributor breadth2 contributors
6/10OpenSSF Scorecard: Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.994
How it's scored
28/42Issue resolution67% of issues closed
8.2/30PR acceptance52/190 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
15/15OpenSSF Scorecard: Code-Reviewall changesets reviewed
Inputs used
merged_prs52
open_issues8
closed_issues16
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.667
closed_unmerged_prs138
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
11.1/25Owner reach34 followers of alessiosavi
25/25Track record118 public repos, account ~8 yr old
Inputs used
followers34
owner_typeUser
is_verified
owner_loginalessiosavi
public_repos118
account_age_days3,277
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Engineering Quality

Are baseline engineering and documentation practices in place?

53Moderate · 19% of overall
How it's scored
24/24CI workflows1 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests0 out of 15 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

60Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics12 topics
10/10Wiki
Inputs used
topicsfacial-recognition, face-recognition, face-detection, rest-api, cuda-support, gpu-support, neural-network, video-guide, celebrities, photos, mlp, mlp-networks
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

51Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
0/2.5CI-Tests0 out of 15 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
7.5/7.5Code-Reviewall changesets reviewed
1.5/2.5Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
0/7.5Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities43 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate3.9
Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
0/25Indirect dependencies free of known advisoriestransitive set not separable from development and test dependencies in this scope
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories80
affected_packages6
assessed_packages13
unassessed_packages1
affected_by_severitycritical 2, high 2, moderate 1, low 1
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 13 resolved dependencies against OSV. 1 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. 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.

43Weak · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history46 of 59 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.78
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environmentDockerfile
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance40 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileyes
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.4
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/11 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes17,503
source_files_sampled11
oversized_source_files0

Key facts

37GitHub stars
2contributors
0commits, last 12 months
228days since last push
2releases
1bus factor
8open 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 ★ / 14 ⇿
0Stars
14Forks
2Releases

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.

24681012141432019-122022-112025-11
Major 0Minor 0Patch 2

Each point covers 6 days.

OpenSSF Scorecard 3.9 / 10
3.9aggregate

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 · 2026-09-01 23:50 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
0CI-Tests0 out of 15 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/aPackagingpackaging workflow not 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
0Vulnerabilities43 existing vulnerabilities detected
All dependencies 14

Full resolved dependency set from the GitHub dependency graph: 0 direct and 14 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIcython0.29.27indirect
PyPIface-recognition1.3.0indirect
PyPIflask1.1.2indirect
PyPIflask-login0.5.0indirect
PyPIflask-monitoringdashboard3.1.1indirect
PyPInumpy1.19.4indirect
PyPIolefile0.46indirect
PyPIpillow8.3.2indirect
PyPIpy-bcrypt0.4indirect
PyPIredis4.1.2indirect
PyPIrequestsindirect
PyPIscikit-learn0.22.2.post1indirect
PyPItqdm4.62.3indirect
PyPIwerkzeug2.0.3indirect
Dependency advisories 6

This repository publishes no package the index resolves, so its own dependency graph was assessed — 13 packages, which also include development and test pins that never ship: 6 carry known advisories, of which 0 are direct. 1 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
pillow8.3.2indirectcritical4827.0.0-beta.2
scikit-learn0.22.2.post1indirectcritical51.5.0
flask1.1.2indirecthigh43.1.3
werkzeug2.0.3indirecthigh193.1.6
numpy1.19.4indirectmoderate21.22
tqdm4.62.3indirectlow24.66.3

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.

The message is kept through sign-in.

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 v0.34.0 — full methodology · metrics wiki.

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