Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-17 16:18 UTC

roboflow / rf-detr

RF-DETR is a real-time object detection and segmentation model architecture developed by Roboflow, SOTA on COCO, designed for fine-tuning. [ICLR 2026]

PythonApache-2.0★ 9,507 stars⑂ 1,200 forkssince Mar 2025View on GitHub ↗

KindCommand-line toolLibraryhow this is determined

#computer-vision #detr #machine-learning #object-detection #rf-detr #instance-segmentation #sota

roboflow/rf-detr holds a health index of 97 out of 100, placing it in the Exceptional band. It scores highest on Vitality (92/100) and lowest on Security (66/100). It was last updated today. 2 contributors account for most of its recent work.

overall / 100

Exceptional

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.

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)

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 85 is calibrated to 97 on the published index scale (record calibration 2026-08-02).

Ownership

RoboflowOrganization · verified domain

5,350 followers170 public repossince Jul 2019

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

Registry	Package	Version	Downloads / mo	Versions	Last publish	Tags
PyPI	rfdetr	1.10.1	497,646	59	10 days ago	machine-learning deep-learning vision ml dl ai detr rf-detr roboflow

Metrics by category

Vitality

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

92Excellent · 21% of overall

Development activity

93Exceptional

How it's scored

36/36	Push recency — last push 0 days ago
29.1/36	Commit cadence — 42/52 weeks with commits
18/18	Commit volume — 853 commits in the last year
10/10	OpenSSF Scorecard: Maintained — 30 commit(s) and 13 issue activity found in the last 90 days -- score normalized to 10

Inputs used

commits_last_year	853
human_commit_share	0.99
days_since_last_push	0
active_weeks_last_year	42

Release discipline

90Excellent

How it's scored

27/27	Ships releases — 30 releases published
36/36	Release recency — latest release 10 days ago
27/27	Release cadence — a release every ~8.9 days
0/10	OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.

Inputs used

releases_count	30
latest_release_tag	1.10.1
releases_from_tags	no
days_since_latest_release	10
mean_days_between_releases	8.9

Community & Adoption

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

89Excellent · 17% of overall

Popularity & adoption

96Exceptional

How it's scored

60/60	Stars — 9,507 stars
25/25	Forks — 1,200 forks
10.6/15	Watchers — 81 watchers

Inputs used

forks	1,200
stars	9,507
watchers	81
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

77Good

How it's scored

22.5/22.5	README
22.5/22.5	License — recognized license (Apache-2.0)
18/18	CONTRIBUTING guide
0/13.5	Code of conduct
0/7.2	Issue template
6.3/6.3	PR template

Inputs used

has_readme	yes
has_license	yes
readme_badges	8
has_contributing	yes
has_issue_template	no
has_code_of_conduct	no
readme_badge_services	badge.fury.io, codecov.io, shields.io
has_pull_request_template	yes

Ecosystem adoption (downloads)

95Exceptional

How it's scored

76/80	Monthly downloads — 497,646 downloads/month across pypi
0/20	Registry dependents — not reported by this ecosystem

Inputs used

packages	rfdetr
dependents	—
ecosystems	pypi
total_downloads	—
monthly_downloads	497,646
unverified_packages_excluded	—

Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

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

84Excellent · 23% of overall

Maintainer resilience (bus factor)

62Moderate

How it's scored

25.2/54	Bus factor — 2 contributor(s) cover half of all commits
12.9/22.5	Commit distribution — top contributor authored 43% of commits
13.5/13.5	Contributor breadth — 98 contributors
10/10	OpenSSF Scorecard: Contributors — project has 22 contributing companies or organizations

Inputs used

bus_factor	2
contributors_sampled	98
top_contributor_share	0.426

Issue & PR responsiveness

80Excellent

How it's scored

37.5/42	Issue resolution — 89% of issues closed
26.2/30	PR acceptance — 692/793 decided PRs merged
9.8/13	Newcomer PR acceptance — 6/8 first-time contributors' PRs merged in 30d
6/15	OpenSSF Scorecard: Code-Review — Found 14/29 approved changesets -- score normalized to 4

Inputs used

merged_prs	692
open_issues	71
closed_issues	601
prs_merged_7d	27
prs_decided_7d	30
prs_merged_30d	52
prs_decided_30d	55
issue_closed_ratio	0.894
closed_unmerged_prs	101
first_time_authors_30d	7
first_time_prs_merged_30d	6
first_time_prs_decided_30d	8

Ownership & stewardship

100Exceptional

How it's scored

30/30	Ownership backing — organization-owned
20/20	Verified domain
25/25	Owner reach — 5,350 followers of roboflow
25/25	Track record — 170 public repos, account ~7 yr old

Inputs used

followers	5,350
owner_type	Organization
is_verified	yes
owner_login	roboflow
public_repos	170
account_age_days	2,616

Package maintenance

100Exceptional

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
35/35	Publish recency — latest publish 10 days ago
20/20	Version history — 59 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	rfdetr
ecosystems	pypi
any_deprecated	no
min_days_since_publish	10

Engineering Quality

Are baseline engineering and documentation practices in place?

92Excellent · 19% of overall

Engineering practices

94Exceptional

How it's scored

24/24	CI workflows — 16 workflow(s)
24/24	Tests present
16/16	Linter config — pyproject.toml ([tool.ruff])
9.6/9.6	Pre-commit hooks
0/6.4	.editorconfig
20/20	OpenSSF Scorecard: CI-Tests — 27 out of 27 merged PRs checked by a CI test -- score normalized to 10

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	no
has_linter_config	yes
has_precommit_config	yes

Documentation

90Excellent

How it's scored

30/30	README
25/25	Documentation directory
15/15	Documentation / homepage site — https://rfdetr.roboflow.com
10/10	Repository description
10/10	Topics — 7 topics
0/10	Wiki

Inputs used

topics	computer-vision, detr, machine-learning, object-detection, rf-detr, instance-segmentation, sota
has_wiki	no
homepage	https://rfdetr.roboflow.com
docs_site	https://rfdetr.roboflow.com
has_readme	yes
has_docs_dir	yes
has_description	yes

Security

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

66Good · 16% of overall

Security posture

58Moderate

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
3.8/7.5	Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5	CI-Tests — 27 out of 27 merged PRs checked by a CI test -- score normalized to 10
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
3/7.5	Code-Review — Found 14/29 approved changesets -- score normalized to 4
2.5/2.5	Contributors — project has 22 contributing companies or organizations
10/10	Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5	Dependency-Update-Tool — no update tool detected
0/5	Fuzzing — project is not fuzzed
2.5/2.5	License — license file detected
7.5/7.5	Maintained — 30 commit(s) and 13 issue activity found in the last 90 days -- score normalized to 10
5/5	Packaging — packaging workflow detected
4.5/5	Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 9
0/5	SAST — SAST tool is not run on all commits -- score normalized to 0
5/5	Security-Policy — security policy file detected
0/7.5	Signed-Releases — Project has not signed or included provenance with any releases.
0/7.5	Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5	Vulnerabilities — 0 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	18
scorecard_version	v5.5.0
checks_inconclusive	0
scorecard_aggregate	5.8

Dependency advisories

100Exceptional

How it's scored

35/35	Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25	Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40	No advisories left outstanding — no advisory carries a publication date

Inputs used

source	osv
advisories	0
affected_packages	0
assessed_packages	75
unassessed_packages	0
affected_by_severity	none
direct_affected_packages	0

Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:rfdetr@1.10.1 runtime dependency closure — what installing the published package pulls in — 75 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.

82Excellent · 4% of overall

Agent context & guidance

100Exceptional

How it's scored

45/45	Agent instructions — .github/copilot-instructions.md, AGENTS.md, CLAUDE.md
15/15	Machine-readable docs (llms.txt) — llms.txt present
40/40	Legible commit history — 99 of 99 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	yes
llms_txt_url	—
legible_history_share	1
agent_instruction_files	.github/copilot-instructions.md, AGENTS.md, CLAUDE.md
agent_instruction_max_bytes	18,403

Verify loop (build / test / typecheck)

63Moderate

How it's scored

0/18	One-command bootstrap
22/22	Automated tests
11/11	Lint / format config — pyproject.toml ([tool.ruff])
11/11	Static type checking — src/rfdetr/py.typed
0/10	Reproducible environment
10/10	Demonstrated agent practice — 46 of the last 100 commits agent-authored or agent-credited
0/8	Automated maintenance — no automated dependency updates observed
9/10	OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 9

Inputs used

has_nix	no
has_tests	yes
lockfiles	—
has_dockerfile	no
typed_language	no
bootstrap_files	—
has_devcontainer	no
has_linter_config	yes
typecheck_configs	src/rfdetr/py.typed
agent_commit_share	0.46
toolchain_manifests	—
dependency_bot_commit_share	0

Code legibility for models

77Good

How it's scored

27/45	Type-checkable code — Python with type-check config (src/rfdetr/py.typed)
50/55	Manageable file sizes — 27/298 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	176,284
source_files_sampled	298
oversized_source_files	27

Machine-readable interfaces

100Exceptional

How it's scored

0/40	API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20	MCP server — not applicable to this kind of software
40/40	Runnable examples — notebooks

Inputs used

example_dirs	notebooks
has_mcp_signal	no
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

9,507GitHub stars

98contributors

853commits, last 12 months

0days since last push

30releases

2bus factor

71open issues

PyPIpackage ecosystems

Data collection warnings

Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
pypi download statistics for 'rfdetr' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced
pypi download figures for rfdetr carried forward from the previous scan (stats endpoint unavailable this scan)

More detail

Star and fork history 0 ★ / 1,200 ⇿

0Stars

1,200Forks

29Releases

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.

Major 0Minor 9Patch 19

Each point covers 2 days.

OpenSSF Scorecard 5.8 / 10

5.8aggregate

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 · 2026-09-17 16:17 UTC

10	Binary-Artifacts	no binaries found in the repo
5	Branch-Protection	branch protection is not maximal on development and all release branches
10	CI-Tests	27 out of 27 merged PRs checked by a CI test -- score normalized to 10
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
4	Code-Review	Found 14/29 approved changesets -- score normalized to 4
10	Contributors	project has 22 contributing companies or organizations
10	Dangerous-Workflow	no dangerous workflow patterns detected
0	Dependency-Update-Tool	no update tool detected
0	Fuzzing	project is not fuzzed
10	License	license file detected
10	Maintained	30 commit(s) and 13 issue activity found in the last 90 days -- score normalized to 10
10	Packaging	packaging workflow detected
9	Pinned-Dependencies	dependency not pinned by hash detected -- score normalized to 9
0	SAST	SAST tool is not run on all commits -- score normalized to 0
10	Security-Policy	security policy file detected
0	Signed-Releases	Project has not signed or included provenance with any releases.
0	Token-Permissions	detected GitHub workflow tokens with excessive permissions
10	Vulnerabilities	0 existing vulnerabilities detected

Direct dependencies 9

Registry	Package	Version constraint	Manifest
PyPI	requests	`—`	pyproject.toml
PyPI	numpy	`—`	pyproject.toml
PyPI	torch	`>=2.2.0`	pyproject.toml
PyPI	torchvision	`>=0.17.0`	pyproject.toml
PyPI	tqdm	`—`	pyproject.toml
PyPI	transformers	`>=5.1.0,<6.0.0`	pyproject.toml
PyPI	pydantic	`>=2.0,<3`	pyproject.toml
PyPI	supervision	`>=0.29.0`	pyproject.toml
PyPI	pyDeprecate	`>=0.9,<0.10`	pyproject.toml

All dependencies 49

Full resolved dependency set from the GitHub dependency graph: 7 direct and 42 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	numpy	`—`	direct
PyPI	pydantic	`—`	direct
PyPI	pydeprecate	`—`	direct
PyPI	supervision	`—`	direct
PyPI	torch	`2.14.0`	direct
PyPI	torchvision	`0.29.0`	direct
PyPI	transformers	`—`	direct
PyPI	albumentations	`—`	indirect
PyPI	build	`—`	indirect
PyPI	coremltools	`—`	indirect
PyPI	executorch	`—`	indirect
PyPI	faster-coco-eval	`—`	indirect
PyPI	fuse-augmentations	`0.10.0.dev0`	indirect
PyPI	hotcoco	`1.0.1`	indirect
PyPI	jsonargparse	`—`	indirect
PyPI	kornia	`—`	indirect
PyPI	litert-torch	`—`	indirect
PyPI	mike	`—`	indirect
PyPI	mkdocs-git-committers-plugin-2	`—`	indirect
PyPI	mkdocs-git-revision-date-localized-plugin	`—`	indirect
PyPI	mkdocs-jupyter	`—`	indirect
PyPI	mkdocs-material	`—`	indirect
PyPI	mkdocstrings	`—`	indirect
PyPI	mkdocstrings-python	`—`	indirect
PyPI	mypy	`1.19.1`	indirect
PyPI	onnx	`—`	indirect
PyPI	onnxsim	`—`	indirect
PyPI	openvino	`—`	indirect
PyPI	protobuf	`—`	indirect
PyPI	pycuda	`—`	indirect
PyPI	pytest	`—`	indirect
PyPI	pytest-cov	`—`	indirect
PyPI	pytest-doctestplus	`—`	indirect
PyPI	pytest-rerunfailures	`—`	indirect
PyPI	pytest-timeout	`—`	indirect
PyPI	pytest-xdist	`—`	indirect
PyPI	pytorch-lightning	`—`	indirect
PyPI	rfdetr-plus	`—`	indirect
PyPI	setuptools	`—`	indirect
PyPI	tensorboard	`—`	indirect
PyPI	tensorrt	`—`	indirect
PyPI	torch-hungarian	`0.1.0rc0`	indirect
PyPI	torch-xla	`—`	indirect
PyPI	torchmetrics	`—`	indirect
PyPI	transformer-engine	`—`	indirect
PyPI	twine	`—`	indirect
PyPI	ultrafast-pycocotools	`—`	indirect
PyPI	webdataset	`—`	indirect
PyPI	wheel	`—`	indirect

Dependency advisories 0

Installing pypi:rfdetr@1.10.1 pulls in 75 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.

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 — PyPI.

Software health index

Score profile

Ownership

Package ecosystems

Metrics by category

Key facts

Data collection warnings

More detail

Feedback

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