Öffentliches RegisterGut
Software-GesundheitsberichtSchema 0.26.0 · Metriken 1.13.0 · 2026-07-22 20:17 UTC
huggingface / pytorch-image-models
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
huggingface/pytorch-image-models erreicht einen Gesundheitsindex von 77 von 100 und liegt damit im Bereich Gut. Am stärksten schneidet es bei Vitality (98/100) ab, am schwächsten bei Security (51/100). Zuletzt vor 5 Tagen aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.
77
gesamt / 100Software-Gesundheitsindex
Metriken werden auf einer Skala von 1–100 in gewichtete Kategorien gruppiert. Der Gesamtwert beginnt als ihr Mittel; sobald öffentliche Evidenz die Richtlinie für Hochrisikojurisdiktionen auslöst, wird die Bewertung angepasst und erhält die Obergrenze 49 (Gefährdet). AI Readiness liegt außerhalb.
77
Exzellent85-100Vorbildlich; erfüllt im Wesentlichen alle geprüften Kriterien
Gut70-84Gesund; geringfügige Lücken
Mittel50-69Akzeptabel mit deutlichen Lücken; Überprüfung empfohlen
Gefährdet30-49Erhebliche Schwächen; eine Übernahme erfordert Vorsicht
Kritisch1-29Schwerwiegende Probleme (aufgegeben, nur ein Maintainer, keine Hygiene)
Bewertungsprofil
Jede Achse ist eine Kategorie. Die Form zählt mehr als der Durchschnitt — ein gesundes Projekt füllt die gesamte Fläche, während ein Profil aus Spitzen und Kratern bedeutet, dass Stärke in einer Dimension Risiken in einer anderen verdeckt.
Eigentümerschaft
Hugging FaceOrganisation
66.034 Follower458 öffentliche Reposseit Feb. 2017
Dieses Repository wird von einer Organisation getragen — geteilte, rechenschaftspflichtige Trägerschaft, die jeden einzelnen Maintainer überdauern kann.
Paket-Ökosysteme
| Registry | Paket | Version | Downloads / Monat | Versionen | Zuletzt veröffentlicht | Tags |
|---|---|---|---|---|---|---|
| PyPI | timm | 1.0.28 | 14.501.427 | 79 | vor 11 Tagen | pytorchimage-classification |
Metriken nach Kategorie
Vitalität
Lebt das Projekt — wird Code geschrieben und werden Releases ausgeliefert?
98
Entwicklungsaktivität
96Exzellent
Wie die Bewertung erfolgt
| 36/36 | Push-Aktualität — letzter Push vor 5 Tagen |
| 31.8/36 | Commit-Rhythmus — 46/52 Wochen mit Commits |
| 18/18 | Commit-Volumen — 241 Commits im letzten Jahr |
| 10/10 | OpenSSF Scorecard: Maintained — 30 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10 |
Verwendete Eingangsdaten
| commits_last_year | 241 |
| human_commit_share | 1 |
| days_since_last_push | 5 |
| active_weeks_last_year | 46 |
Release-Disziplin
100Exzellent
Wie die Bewertung erfolgt
| 27/27 | Liefert Releases aus — 78 Releases veröffentlicht |
| 36/36 | Release-Aktualität — letztes Release vor 11 Tagen |
| 27/27 | Release-Rhythmus — ein Release etwa alle 39,2 Tage |
| 0/10 | OpenSSF Scorecard: Signed-Releases — keine Daten |
Verwendete Eingangsdaten
| releases_count | 78 |
| latest_release_tag | v1.0.28 |
| releases_from_tags | nein |
| days_since_latest_release | 11 |
| mean_days_between_releases | 39,2 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): OpenSSF Scorecard: Signed-Releases. Die verbleibenden Gewichte wurden renormalisiert.
Community & Verbreitung
Hat das Projekt Nutzer, Downloads, Aufmerksamkeit und ein einladendes Umfeld für Beitragende?
94
Popularität & Verbreitung
99Exzellent
Wie die Bewertung erfolgt
| 60/60 | Stars — 37.003 Stars |
| 25/25 | Forks — 5.173 Forks |
| 13.9/15 | Watcher — 320 Watcher |
Verwendete Eingangsdaten
| forks | 5.173 |
| stars | 37.003 |
| watchers | 320 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Community-Gesundheit
85Exzellent
Wie die Bewertung erfolgt
| 22.5/22.5 | README |
| 22.5/22.5 | Lizenz — anerkannte Lizenz (Apache-2.0) |
| 18/18 | CONTRIBUTING-Leitfaden |
| 13.5/13.5 | Verhaltenskodex |
| 0/7.2 | Issue-Vorlage |
| 0/6.3 | PR-Vorlage |
Verwendete Eingangsdaten
| has_readme | ja |
| has_license | ja |
| has_contributing | ja |
| has_issue_template | nein |
| has_code_of_conduct | ja |
| has_pull_request_template | nein |
Ökosystem-Verbreitung (Downloads)
100Exzellent
Wie die Bewertung erfolgt
| 80/80 | Downloads pro Monat — 14.501.427 Downloads/Monat über pypi |
| 0/20 | Abhängige in der Registry — von diesem Ökosystem nicht ausgewiesen |
Verwendete Eingangsdaten
| packages | timm |
| dependents | — |
| ecosystems | pypi |
| total_downloads | — |
| monthly_downloads | 14.501.427 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Abhängige in der Registry. Die verbleibenden Gewichte wurden renormalisiert.
Nachhaltigkeit & Governance
Überdauert das Projekt die Menschen, die es tragen — Bus-Faktor, Reaktionsfähigkeit, Trägerschaft und Paketpflege?
70
Maintainer-Resilienz (Bus-Faktor)
36Gefährdet
Wie die Bewertung erfolgt
| 9/54 | Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab |
| 3.3/22.5 | Commit-Verteilung — wichtigste beitragende Person verfasste 86 % der Commits |
| 13.5/13.5 | Breite der Beitragenden — 100 Beitragende |
| 10/10 | OpenSSF Scorecard: Contributors — project has 15 contributing companies or organizations |
Verwendete Eingangsdaten
| bus_factor | 1 |
| contributors_sampled | 100 |
| top_contributor_share | 0,855 |
Wie die Bewertung erfolgt
| 44.8/46.8 | Issue-Lösungsquote — 96 % der Issues geschlossen |
| 28.8/38.3 | PR-Annahme — 552/733 entschiedene PRs gemergt |
| 4.5/15 | OpenSSF Scorecard: Code-Review — Found 6/20 approved changesets -- score normalized to 3 |
Verwendete Eingangsdaten
| merged_prs | 552 |
| open_issues | 43 |
| closed_issues | 992 |
| issue_closed_ratio | 0,958 |
| closed_unmerged_prs | 181 |
Wie die Bewertung erfolgt
| 30/30 | Organisatorische Trägerschaft — im Besitz einer Organisation |
| 0/20 | Verifizierte Domain |
| 25/25 | Reichweite des Inhabers — 66.034 Follower von huggingface |
| 25/25 | Kontohistorie — 458 öffentliche Repos, Kontoalter ca. 9 Jahre |
Verwendete Eingangsdaten
| followers | 66.034 |
| owner_type | Organization |
| is_verified | — |
| owner_login | huggingface |
| public_repos | 458 |
| account_age_days | 3.447 |
Paketpflege
100Exzellent
Wie die Bewertung erfolgt
| 25/25 | Veröffentlicht & auflösbar — 1 Paket(e) auf pypi |
| 35/35 | Veröffentlichungsaktualität — letzte Veröffentlichung vor 11 Tagen |
| 20/20 | Versionshistorie — 79 veröffentlichte Versionen |
| 20/20 | Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen |
Verwendete Eingangsdaten
| packages | timm |
| ecosystems | pypi |
| any_deprecated | nein |
| min_days_since_publish | 11 |
Engineering-Qualität
Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?
68
Engineering-Praktiken
64Mittel
Wie die Bewertung erfolgt
| 24/24 | CI-Workflows — 5 Workflow(s) |
| 24/24 | Tests vorhanden |
| 0/16 | Linter-Konfiguration |
| 0/9.6 | Pre-Commit-Hooks |
| 0/6.4 | .editorconfig |
| 16/20 | OpenSSF Scorecard: CI-Tests — 14 out of 16 merged PRs checked by a CI test -- score normalized to 8 |
Verwendete Eingangsdaten
| has_ci | ja |
| has_tests | ja |
| has_editorconfig | nein |
| has_linter_config | nein |
| has_precommit_config | nein |
Dokumentation
75Gut
Wie die Bewertung erfolgt
| 30/30 | README |
| 0/25 | Dokumentationsverzeichnis |
| 15/15 | Dokumentations-/Homepage-Site — https://huggingface.co/docs/timm |
| 10/10 | Repository-Beschreibung |
| 10/10 | Topics — 20 Topics |
| 10/10 | Wiki |
Verwendete Eingangsdaten
| topics | pytorch, resnet, pretrained-models, pretrained-weights, distributed-training, mobile-deep-learning, mobilenet-v2, mobilenetv3, efficientnet, augmix, randaugment, mixnet, vision-transformer-models, nfnets, normalization-free-training, maxvit, convnext, image-classification, imagenet, optimizer |
| has_wiki | ja |
| homepage | https://huggingface.co/docs/timm |
| has_readme | ja |
| has_docs_dir | nein |
| has_description | ja |
Sicherheit
Sind die sichtbaren Sicherheits- und Lieferkettenpraktiken belastbar, ohne ungeklärte Exposition gegenüber Hochrisikojurisdiktionen?
51
Sicherheitslage
51Mittel
Wie die Bewertung erfolgt
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 0/7.5 | Branch-Protection — keine Daten |
| 2/2.5 | CI-Tests — 14 out of 16 merged PRs checked by a CI test -- score normalized to 8 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 2.2/7.5 | Code-Review — Found 6/20 approved changesets -- score normalized to 3 |
| 2.5/2.5 | Contributors — project has 15 contributing companies or organizations |
| 10/10 | Dangerous-Workflow — no dangerous workflow patterns detected |
| 7.5/7.5 | Dependency-Update-Tool — update tool detected |
| 0/5 | Fuzzing — project is not fuzzed |
| 2.5/2.5 | Lizenz — license file detected |
| 7.5/7.5 | Maintained — 30 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10 |
| 0/5 | Packaging — keine Daten |
| 1.5/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 3 |
| 0/5 | SAST — SAST tool is not run on all commits -- score normalized to 0 |
| 0/5 | Security-Policy — security policy file not detected |
| 0/7.5 | Signed-Releases — keine Daten |
| 0/7.5 | Token-Permissions — detected GitHub workflow tokens with excessive permissions |
| 0/7.5 | Vulnerabilities — 24 existing vulnerabilities detected |
Verwendete Eingangsdaten
| source | openssf_scorecard |
| checks_evaluated | 15 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 3 |
| scorecard_aggregate | 5,1 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): branch_protection, packaging, signed_releases. Die verbleibenden Gewichte wurden renormalisiert.
AI Readiness
Wie gut ist das Repository dafür ausgestattet, mit KI-Coding-Agenten entwickelt und gepflegt zu werden? Ein unabhängiges, experimentelles Badge — Gewicht 0,0, es wird eigenständig ausgewiesen und verändert den Gesamt-Gesundheitswert nicht.
56
AI-Agentenkontext & Leitlinien
59Mittel
Wie die Bewertung erfolgt
| 45/45 | Agentenanweisungen — CLAUDE.md |
| 0/15 | Maschinenlesbare Doku (llms.txt) |
| 14.4/40 | Lesbare Commit-Historie — 27 von 100 menschlichen Commits benennen ihre Absicht (strukturierter Betreff oder erläuternder Text) |
Verwendete Eingangsdaten
| has_llms_txt | nein |
| legible_history_share | 0,27 |
| agent_instruction_files | CLAUDE.md |
| agent_instruction_max_bytes | 901 |
AI-Verify-Loop (Build / Test / Typprüfung)
44Gefährdet
Wie die Bewertung erfolgt
| 0/18 | Bootstrap mit einem Befehl |
| 22/22 | Automatisierte Tests |
| 0/11 | Lint-/Format-Konfiguration |
| 11/11 | Statische Typprüfung — timm/py.typed |
| 0/10 | Reproduzierbare Umgebung |
| 8/10 | Belegte Agentenpraxis — 4 der letzten 100 Commits von Agenten verfasst oder ihnen zugeschrieben |
| 0/8 | Automatisierte Wartung — keine automatisierten Abhängigkeits-Updates beobachtet |
| 3/10 | OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 3 |
Verwendete Eingangsdaten
| has_nix | nein |
| has_tests | ja |
| lockfiles | — |
| has_dockerfile | nein |
| typed_language | nein |
| bootstrap_files | — |
| has_devcontainer | nein |
| has_linter_config | nein |
| typecheck_configs | timm/py.typed |
| agent_commit_share | 0,04 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
Wie die Bewertung erfolgt
| 27/45 | Typprüfbarer Code — Python mit Typprüfungs-Konfiguration (timm/py.typed) |
| 52.7/55 | Handhabbare Dateigrößen — 13/311 Quelldateien über 60 KB |
Verwendete Eingangsdaten
| primary_language | Python |
| largest_source_bytes | 211.911 |
| source_files_sampled | 311 |
| oversized_source_files | 13 |
Eckdaten
37.003GitHub-Sterne
100Mitwirkende
241Commits, letzte 12 Monate
5Tage seit letztem Push
78Releases
1Bus-Faktor
43offene Issues
PyPIPaket-Ökosysteme
Warnungen zur Datenerhebung
- Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
- deps.dev does not index pypi:timm@1.0.28; advisories assessed against the repository dependency graph instead
- No resolved dependencies carried a version and a supported ecosystem
Weitere Details
Stern- und Fork-Verlauf 0 ★ / 5.173 ⇿
0Sterne
5.173Forks
24Releases
Wann jeder Stern und Fork hinzugefügt wurde, von GitHub erfasst und nach Tagen gruppiert. Das kumulierte Wachstum steht direkt über den täglichen Zugängen, aus denen es besteht, sodass beide gegeneinander lesbar sind: stetiger organischer Zuwachs sieht ganz anders aus als ein abrupter, kurzlebiger Ausschlag. Wo dieser Unterschied messbar ist, wird er als Wachstumsauthentizität ausgewiesen.
Es wird nur die jüngste Historie angezeigt — dieses Repository überschreitet das Erfassungsfenster, sodass die früheste Historie nicht erfasst wird.
Major 0Minor 0Patch 24
Jeder Punkt umfasst 3 Tage.
OpenSSF Scorecard 5.1 / 10
5.1Gesamtwert
Unabhängige, werkzeugneutrale Sicherheitsbewertung durch das quelloffene OpenSSF Scorecard. Jede Prüfung honoriert eine Sicherheits-Praxis, nicht das Werkzeug eines bestimmten Anbieters. Prüfungen, die Scorecard nicht ermitteln konnte, sind mit k. A. markiert und vom Sicherheitswert ausgeschlossen (nie als null gezählt).
| 10 | Binary-Artifacts | no binaries found in the repo |
| k. A. | Branch-Protection | internal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md |
| 8 | CI-Tests | 14 out of 16 merged PRs checked by a CI test -- score normalized to 8 |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 3 | Code-Review | Found 6/20 approved changesets -- score normalized to 3 |
| 10 | Contributors | project has 15 contributing companies or organizations |
| 10 | Dangerous-Workflow | no dangerous workflow patterns detected |
| 10 | Dependency-Update-Tool | update tool detected |
| 0 | Fuzzing | project is not fuzzed |
| 10 | License | license file detected |
| 10 | Maintained | 30 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10 |
| k. A. | Packaging | packaging workflow not detected |
| 3 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 3 |
| 0 | SAST | SAST tool is not run on all commits -- score normalized to 0 |
| 0 | Security-Policy | security policy file not detected |
| k. A. | Signed-Releases | no releases found |
| 0 | Token-Permissions | detected GitHub workflow tokens with excessive permissions |
| 0 | Vulnerabilities | 24 existing vulnerabilities detected |
Direkte Abhängigkeiten 5
| Registry | Paket | Versionsvorgabe | Manifest |
|---|---|---|---|
| PyPI | torch | — | pyproject.toml |
| PyPI | torchvision | — | pyproject.toml |
| PyPI | pyyaml | — | pyproject.toml |
| PyPI | huggingface_hub | — | pyproject.toml |
| PyPI | safetensors | — | pyproject.toml |
Alle Abhängigkeiten 11
Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 5 direkte und 6 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.
| Registry | Paket | Version | Beziehung |
|---|---|---|---|
| PyPI | huggingface-hub | — | direkt |
| PyPI | pyyaml | — | direkt |
| PyPI | safetensors | — | direkt |
| PyPI | torch | — | direkt |
| PyPI | torchvision | — | direkt |
| PyPI | expecttest | — | indirekt |
| PyPI | numpy | — | indirekt |
| PyPI | pytest | — | indirekt |
| PyPI | pytest-forked | — | indirekt |
| PyPI | pytest-timeout | — | indirekt |
| PyPI | pytest-xdist | — | indirekt |
Abhängigkeits-Advisories nicht bewertet
Der Advisory-Abgleich konnte für diesen Bericht nicht ausgeführt werden: No resolved dependencies carried a version and a supported ecosystem
JSON-Rohbericht maschinenlesbar
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"status": "partial",
"details": [],
"max_points": 7.5
},
{
"key": "contributors",
"name": "Contributors",
"detail": "project has 15 contributing companies or organizations",
"points": 2.5,
"status": "met",
"details": [],
"max_points": 2.5
},
{
"key": "dangerous_workflow",
"name": "Dangerous-Workflow",
"detail": "no dangerous workflow patterns detected",
"points": 10,
"status": "met",
"details": [],
"max_points": 10
},
{
"key": "dependency_update_tool",
"name": "Dependency-Update-Tool",
"detail": "update tool detected",
"points": 7.5,
"status": "met",
"details": [],
"max_points": 7.5
},
{
"key": "fuzzing",
"name": "Fuzzing",
"detail": "project is not fuzzed",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "license",
"name": "License",
"detail": "license file detected",
"points": 2.5,
"status": "met",
"details": [],
"max_points": 2.5
},
{
"key": "maintained",
"name": "Maintained",
"detail": "30 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10",
"points": 7.5,
"status": "met",
"details": [],
"max_points": 7.5
},
{
"key": "packaging",
"name": "Packaging",
"detail": "packaging workflow not detected",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 5
},
{
"key": "pinned_dependencies",
"name": "Pinned-Dependencies",
"detail": "dependency not pinned by hash detected -- score normalized to 3",
"points": 1.5,
"status": "partial",
"details": [],
"max_points": 5
},
{
"key": "sast",
"name": "SAST",
"detail": "SAST tool is not run on all commits -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "security_policy",
"name": "Security-Policy",
"detail": "security policy file not detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "signed_releases",
"name": "Signed-Releases",
"detail": "no releases found",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 7.5
},
{
"key": "token_permissions",
"name": "Token-Permissions",
"detail": "detected GitHub workflow tokens with excessive permissions",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "vulnerabilities",
"name": "Vulnerabilities",
"detail": "24 existing vulnerabilities detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
}
]
},
{
"key": "high_risk_jurisdiction_exposure",
"band": "excellent",
"name": "High-Risk Jurisdiction Exposure",
"note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
"notes": [
{
"code": "jurisdiction_evidence_limits",
"params": {}
}
],
"value": 100,
"inputs": {
"meaning": "self-published location evidence; not nationality or citizenship",
"red_flag": false,
"exposures": [],
"policy_countries": [
"Russia",
"Iran",
"North Korea"
],
"review_only_matches": 0,
"assessed_self_published_locations": 12
},
"components": [
{
"key": "policy_exposure_multiplier",
"name": "Policy exposure multiplier",
"detail": "no confirmed policy-scope location match",
"points": 100,
"status": "met",
"details": [
{
"code": "jurisdiction_no_match",
"params": {}
}
],
"max_points": 100
}
]
}
],
"description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
},
{
"key": "ai_readiness",
"band": "moderate",
"name": "AI Readiness",
"value": 56,
"weight": 0,
"metrics": [
{
"key": "ai_agent_context",
"band": "moderate",
"name": "Agent context & guidance",
"note": null,
"notes": [],
"value": 59,
"inputs": {
"has_llms_txt": false,
"legible_history_share": 0.27,
"agent_instruction_files": [
"CLAUDE.md"
],
"agent_instruction_max_bytes": 901
},
"components": [
{
"key": "agent_instructions",
"name": "Agent instructions",
"detail": "CLAUDE.md",
"points": 45,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "CLAUDE.md"
}
}
],
"max_points": 45
},
{
"key": "machine_readable_docs_llms_txt",
"name": "Machine-readable docs (llms.txt)",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 15
},
{
"key": "legible_commit_history",
"name": "Legible commit history",
"detail": "27 of 100 human commits state their intent (structured subject or explanatory body)",
"points": 14.4,
"status": "partial",
"details": [
{
"code": "legible_history",
"params": {
"legible": 27,
"sampled": 100
}
}
],
"max_points": 40
}
]
},
{
"key": "ai_verify_loop",
"band": "at_risk",
"name": "Verify loop (build / test / typecheck)",
"note": null,
"notes": [],
"value": 44,
"inputs": {
"has_nix": false,
"has_tests": true,
"lockfiles": [],
"has_dockerfile": false,
"typed_language": false,
"bootstrap_files": [],
"has_devcontainer": false,
"has_linter_config": false,
"typecheck_configs": [
"timm/py.typed"
],
"agent_commit_share": 0.04,
"toolchain_manifests": [],
"dependency_bot_commit_share": 0
},
"components": [
{
"key": "one_command_bootstrap",
"name": "One-command bootstrap",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 18
},
{
"key": "automated_tests",
"name": "Automated tests",
"detail": null,
"points": 22,
"status": "met",
"details": [],
"max_points": 22
},
{
"key": "lint_format_config",
"name": "Lint / format config",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "static_type_checking",
"name": "Static type checking",
"detail": "timm/py.typed",
"points": 11,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "timm/py.typed"
}
}
],
"max_points": 11
},
{
"key": "reproducible_environment",
"name": "Reproducible environment",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
},
{
"key": "demonstrated_agent_practice",
"name": "Demonstrated agent practice",
"detail": "4 of the last 100 commits agent-authored or agent-credited",
"points": 8,
"status": "partial",
"details": [
{
"code": "agent_authored_commits",
"params": {
"count": 4,
"sampled": 100
}
}
],
"max_points": 10
},
{
"key": "automated_maintenance",
"name": "Automated maintenance",
"detail": "no automated dependency updates observed",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_dependency_automation",
"params": {}
}
],
"max_points": 8
},
{
"key": "openssf_scorecard_pinned_dependencies",
"name": "OpenSSF Scorecard: Pinned-Dependencies",
"detail": "dependency not pinned by hash detected -- score normalized to 3",
"points": 3,
"status": "partial",
"details": [],
"max_points": 10
}
]
},
{
"key": "ai_code_legibility",
"band": "good",
"name": "Code legibility for models",
"note": null,
"notes": [],
"value": 80,
"inputs": {
"primary_language": "Python",
"largest_source_bytes": 211911,
"source_files_sampled": 311,
"oversized_source_files": 13
},
"components": [
{
"key": "type_checkable_code",
"name": "Type-checkable code",
"detail": "Python with type-check config (timm/py.typed)",
"points": 27,
"status": "partial",
"details": [
{
"code": "typecheck_config_language",
"params": {
"files": "timm/py.typed",
"language": "Python"
}
}
],
"max_points": 45
},
{
"key": "manageable_file_sizes",
"name": "Manageable file sizes",
"detail": "13/311 source files over 60KB",
"points": 52.7,
"status": "partial",
"details": [
{
"code": "oversized_source_files",
"params": {
"kb": 60,
"sampled": 311,
"oversized": 13
}
}
],
"max_points": 55
}
]
}
],
"description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
}
],
"metrics_version": "1.13.0"
},
"warnings": [
"Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token",
"deps.dev does not index pypi:timm@1.0.28; advisories assessed against the repository dependency graph instead",
"No resolved dependencies carried a version and a supported ecosystem"
],
"report_type": "repository",
"generated_at": "2026-07-22T20:17:23.429210Z",
"schema_version": "0.26.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/h/huggingface/pytorch-image-models.svg",
"full_name": "huggingface/pytorch-image-models",
"license_state": "standard",
"license_spdx": "Apache-2.0"
}Bewertungen sind Signale, keine Garantien. Sie spiegeln öffentlich sichtbare Praxis auf GitHub wider — kein Code-Audit und keine Sicherheitsgarantie.
Fehlende Daten werden ausgeschlossen und die Gewichte neu normiert, nie als null bewertet. Die Methodik ist versioniert und offen: Metriken v1.13.0, Schema v0.26.0 — vollständige Methodik · Metriken-Wiki.
Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte Statistiken — PyPI.