Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-17 17:13 UTC

mindee / doctr

docTR (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning. Ongoing development and maintenance by t2k.

PythonApache-2.0★ 6,355 stars⑂ 678 forkssince Jan 2021View on GitHub ↗
KindCommand-line toolLibraryNetwork servicehow this is determined
#ocr#deep-learning#document-recognition#tensorflow2#text-detection-recognition#text-detection#text-recognition#optical-character-recognition#pytorch

mindee/doctr holds a health index of 94 out of 100, placing it in the Exceptional band. It scores highest on Engineering Quality (96/100) and lowest on Security (64/100). It was last updated 2 days ago. 2 contributors account for most of its recent work.

94
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.

94
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 81 is calibrated to 94 on the published index scale (record calibration 2026-08-02).

Ownership

MindeeOrganization
135 followers29 public repossince Jul 2020

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIpython-doctr1.1.0235,7232127 days agoocrdeep-learningcomputer-visionpytorchtext-detectiontext-recognition

Metrics by category

Vitality

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

80Excellent · 21% of overall

Development activity

78Good
How it's scored
36/36Push recency — last push 2 days ago
14.5/36Commit cadence — 21/52 weeks with commits
17/18Commit volume — 77 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 7 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year77
human_commit_share0.84
days_since_last_push2
active_weeks_last_year21

Release discipline

83Excellent
How it's scored
27/27Ships releases — 22 releases published
36/36Release recency — latest release 27 days ago
19.8/27Release cadence — a release every ~119.7 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count22
latest_release_tagv1.1.0
releases_from_tagsno
days_since_latest_release27
mean_days_between_releases119.7

Community & Adoption

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

89Excellent · 17% of overall

Popularity & adoption

93Exceptional
How it's scored
60/60Stars — 6,355 stars
23.6/25Forks — 678 forks
9.5/15Watchers — 52 watchers
Inputs used
forks678
stars6,355
watchers52
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

85Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges9
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicescodecov.io, github.com, shields.io
has_pull_request_templateno

Ecosystem adoption (downloads)

89Excellent
How it's scored
71.6/80Monthly downloads — 235,723 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagespython-doctr
dependents—
ecosystemspypi
total_downloads—
monthly_downloads235,723
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?

77Good · 23% of overall

Maintainer resilience (bus factor)

64Moderate
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
14.9/22.5Commit distribution — top contributor authored 34% of commits
13.5/13.5Contributor breadth — 75 contributors
10/10OpenSSF Scorecard: Contributors — project has 7 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled75
top_contributor_share0.338

Issue & PR responsiveness

82Excellent
How it's scored
40.3/42Issue resolution — 96% of issues closed
26.9/30PR acceptance — 1,065/1,189 decided PRs merged
13/13Newcomer PR acceptance — 2/2 first-time contributors' PRs merged in 30d
1.5/15OpenSSF Scorecard: Code-Review — Found 5/28 approved changesets -- score normalized to 1
Inputs used
merged_prs1,065
open_issues18
closed_issues431
prs_merged_7d1
prs_decided_7d1
prs_merged_30d10
prs_decided_30d11
issue_closed_ratio0.96
closed_unmerged_prs124
first_time_authors_30d2
first_time_prs_merged_30d2
first_time_prs_decided_30d2

Ownership & stewardship

68Good
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
15.3/25Owner reach — 135 followers of mindee
22.8/25Track record — 29 public repos, account ~6 yr old
Inputs used
followers135
owner_typeOrganization
is_verifiedno
owner_loginmindee
public_repos29
account_age_days2,257

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 27 days ago
20/20Version history — 21 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagespython-doctr
ecosystemspypi
any_deprecatedno
min_days_since_publish27

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall

Engineering practices

94Exceptional
How it's scored
24/24CI workflows — 14 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 29 out of 29 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://mindee.github.io/doctr/
10/10Repository description
10/10Topics — 9 topics
10/10Wiki
Inputs used
topicsocr, deep-learning, document-recognition, tensorflow2, text-detection-recognition, text-detection, text-recognition, optical-character-recognition, pytorch
has_wikiyes
homepagehttps://mindee.github.io/doctr/
docs_sitehttps://mindee.github.io/doctr/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

64Moderate · 16% of overall

Security posture

55Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2.5/2.5CI-Tests — 29 out of 29 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
0.8/7.5Code-Review — Found 5/28 approved changesets -- score normalized to 1
2.5/2.5Contributors — project has 7 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 7 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 — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5.5
Excluded from scoring (no data or not applicable): Branch-Protection. 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_packages57
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:python-doctr@1.1.0 runtime dependency closure — what installing the published package pulls in — 57 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.

72Good · 4% of overall

Agent context & guidance

55Moderate
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://docs.nvidia.com/llms.txt)
40/40Legible commit history — 77 of 84 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://docs.nvidia.com/llms.txt
legible_history_share0.917
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

82Excellent
How it's scored
18/18One-command bootstrap — Makefile, api/Makefile, docs/Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
11/11Static type checking — doctr/py.typed
10/10Reproducible environment — Dockerfile
2/10Demonstrated agent practice — 1 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 16 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile, api/Makefile, docs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configsdoctr/py.typed
agent_commit_share0.01
toolchain_manifests—
dependency_bot_commit_share0.16

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (doctr/py.typed)
54.8/55Manageable file sizes — 1/261 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes102,220
source_files_sampled261
oversized_source_files1

Key facts

6,355GitHub stars
75contributors
77commits, last 12 months
2days since last push
22releases
2bus factor
18open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Could not fetch pypi package 'doctr-api' from its registry

More detail

Star and fork history 0 ★ / 678 ⇿
0Stars
678Forks
19Releases

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.

0125250375500625750664172021-042024-012026-09
Major 1Minor 12Patch 6

Each point covers 5 days.

OpenSSF Scorecard 5.5 / 10
5.5aggregate

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 17:13 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal 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
10CI-Tests29 out of 29 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1Code-ReviewFound 5/28 approved changesets -- score normalized to 1
10Contributorsproject has 7 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 7 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
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 21
RegistryPackageVersion constraintManifest
PyPIpython-doctr—api/pyproject.toml
PyPIfastapi>=0.73.0api/pyproject.toml
PyPIuvicorn>=0.11.1api/pyproject.toml
PyPIpython-multipart>=0.0.5api/pyproject.toml
PyPItorch>=2.0.0,<3.0.0pyproject.toml
PyPItorchvision>=0.15.0pyproject.toml
PyPIonnx>=1.12.0,<3.0.0pyproject.toml
PyPInumpy>=1.16.0,<3.0.0pyproject.toml
PyPIscipy>=1.4.0,<2.0.0pyproject.toml
PyPIh5py>=3.1.0,<4.0.0pyproject.toml
PyPIopencv-python>=4.5.0,<6.0.0pyproject.toml
PyPIpypdfium2>=4.11.0,<6.0.0pyproject.toml
PyPIpyclipper>=1.2.0,<2.0.0pyproject.toml
PyPIshapely>=1.6.0,<3.0.0pyproject.toml
PyPIlangdetect>=1.0.9,<2.0.0pyproject.toml
PyPIrapidfuzz>=3.0.0,<4.0.0pyproject.toml
PyPIhuggingface-hub>=0.20.0,<2.0.0pyproject.toml
PyPIPillow>=10.1.0pyproject.toml
PyPIanyascii>=0.3.2pyproject.toml
PyPIvalidators>=0.18.0pyproject.toml
PyPItqdm>=4.30.0pyproject.toml
All dependencies 99

Full resolved dependency set from the GitHub dependency graph: 37 direct and 62 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIanyascii—direct
PyPIanyascii0.3.3direct
PyPIfastapi0.141.1direct
PyPIh5py—direct
PyPIh5py3.16.0direct
PyPIhuggingface-hub—direct
PyPIhuggingface-hub1.28.0direct
PyPIlangdetect—direct
PyPIlangdetect1.0.9direct
PyPInumpy—direct
PyPInumpy2.4.6direct
PyPIonnx—direct
PyPIonnx1.22.0direct
PyPIopencv-python—direct
PyPIopencv-python5.0.0.93direct
PyPIpillow—direct
PyPIpillow12.3.0direct
PyPIpyclipper—direct
PyPIpyclipper1.4.0direct
PyPIpypdfium2—direct
PyPIpypdfium25.13.0direct
PyPIpython-multipart0.0.32direct
PyPIrapidfuzz—direct
PyPIrapidfuzz3.14.5direct
PyPIscipy—direct
PyPIscipy1.17.1direct
PyPIshapely—direct
PyPIshapely2.1.2direct
PyPItorch—direct
PyPItorch2.13.0direct
PyPItorchvision—direct
PyPItorchvision0.28.0direct
PyPItqdm—direct
PyPItqdm4.70.0direct
PyPIuvicorn0.52.4direct
PyPIvalidators—direct
PyPIvalidators0.35.0direct
PyPIannotated-doc0.0.5indirect
PyPIannotated-types0.8.0indirect
PyPIanyio4.14.2indirect
PyPIcertifi2026.7.22indirect
PyPIcharset-normalizer3.5.1indirect
PyPIclearml—indirect
PyPIclick8.4.2indirect
PyPIcolorama0.4.6indirect
PyPIcuda-bindings13.3.1indirect
PyPIcuda-pathfinder1.6.1indirect
PyPIcuda-toolkit13.0.3indirect
PyPIfilelock3.32.3indirect
PyPIfsspec2026.7.0indirect
PyPIh110.16.0indirect
PyPIhf-xet1.6.0indirect
PyPIhttpcore1.0.9indirect
PyPIhttpx0.28.1indirect
PyPIidna3.19indirect
PyPIiniconfig2.3.0indirect
PyPIjinja23.1.6indirect
PyPImarkupsafe3.0.3indirect
PyPImatplotlib—indirect
PyPIml-dtypes0.6.0indirect
PyPImpmath1.3.0indirect
PyPInetworkx3.6.1indirect
PyPInvidia-cublas13.1.1.3indirect
PyPInvidia-cuda-cupti13.0.85indirect
PyPInvidia-cuda-nvrtc13.0.88indirect
PyPInvidia-cuda-runtime13.0.96indirect
PyPInvidia-cudnn-cu139.20.0.48indirect
PyPInvidia-cufft12.0.0.61indirect
PyPInvidia-cufile1.15.1.6indirect
PyPInvidia-curand10.4.0.35indirect
PyPInvidia-cusolver12.0.4.66indirect
PyPInvidia-cusparse12.6.3.3indirect
PyPInvidia-cusparselt-cu130.8.1indirect
PyPInvidia-nccl-cu132.29.7indirect
PyPInvidia-nvjitlink13.3.33indirect
PyPInvidia-nvshmem-cu133.4.5indirect
PyPInvidia-nvtx13.0.85indirect
PyPIpackaging26.3indirect
PyPIpandas—indirect
PyPIpluggy1.6.0indirect
PyPIprotobuf7.36.0indirect
PyPIpydantic2.13.4indirect
PyPIpydantic-core2.46.4indirect
PyPIpygments2.21.0indirect
PyPIpytest9.1.1indirect
PyPIpytest-asyncio1.4.0indirect
PyPIpyyaml6.0.3indirect
PyPIrequests2.34.2indirect
PyPIsetuptools84.0.0indirect
PyPIsix1.17.0indirect
PyPIslack-sdk—indirect
PyPIstarlette1.6.0indirect
PyPIstreamlit—indirect
PyPIsympy1.14.0indirect
PyPItriton3.7.1indirect
PyPItyping-extensions4.16.0indirect
PyPItyping-inspection0.4.4indirect
PyPIurllib32.7.0indirect
PyPIwandb—indirect
Dependency advisories 0

Installing pypi:python-doctr@1.1.0 pulls in 57 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

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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 v0.34.0 — full methodology · metrics wiki.

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