Public recordExcellent
Software health reportschema 0.27.0 · metrics 2.5.0 · 2026-07-31 00:22 UTC
BrainLesion / panoptica
panoptica -- instance-wise evaluation of 3D semantic and instance segmentation maps
BrainLesion/panoptica holds a health index of 84 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (92/100) and lowest on AI Readiness (49/100). It was last updated 1 day ago. 2 contributors account for most of its recent work.
84
overall / 100Software 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.
84
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 71 is calibrated to 84 on the published index scale (record calibration 2026-08-02).
Ownership
BrainLesion SuiteOrganization
26 followers17 public repossince Aug 2023
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 | panoptica | 2.1.4 | - | 82 | 10 days ago | panopticqualitysegmentationmedical-imaging |
Metrics by category
Vitality
Is the project alive — is code being written and are releases shipping?
86
Development activity
77Good
How it's scored
| 36/36 | Push recency — last push 1 days ago |
| 13.2/36 | Commit cadence — 19/52 weeks with commits |
| 18/18 | Commit volume — 315 commits in the last year |
| 10/10 | OpenSSF Scorecard: Maintained — 30 commit(s) and 8 issue activity found in the last 90 days -- score normalized to 10 |
Inputs used
| commits_last_year | 315 |
| human_commit_share | 0.94 |
| days_since_last_push | 1 |
| active_weeks_last_year | 19 |
Release discipline
100Exceptional
How it's scored
| 27/27 | Ships releases — 67 releases published |
| 36/36 | Release recency — latest release 10 days ago |
| 27/27 | Release cadence — a release every ~39.5 days |
| 0/10 | OpenSSF Scorecard: Signed-Releases — no data |
Inputs used
| releases_count | 67 |
| latest_release_tag | v2.1.4 |
| releases_from_tags | no |
| days_since_latest_release | 10 |
| mean_days_between_releases | 39.5 |
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?
50
Popularity & adoption
33At Risk
How it's scored
| 24.4/60 | Stars — 33 stars |
| 8.3/25 | Forks — 11 forks |
| 0/15 | Watchers — 1 watchers |
Inputs used
| forks | 11 |
| stars | 33 |
| watchers | 1 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Community health
70Good
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 |
| 0/6.3 | PR template |
Inputs used
| has_readme | yes |
| has_license | yes |
| readme_badges | — |
| has_contributing | yes |
| has_issue_template | no |
| has_code_of_conduct | no |
| readme_badge_services | — |
| has_pull_request_template | no |
Sustainability & Governance
Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?
72
Maintainer resilience (bus factor)
61Moderate
How it's scored
| 25.2/54 | Bus factor — 2 contributor(s) cover half of all commits |
| 13.5/22.5 | Commit distribution — top contributor authored 40% of commits |
| 12.2/13.5 | Contributor breadth — 9 contributors |
| 10/10 | OpenSSF Scorecard: Contributors — project has 5 contributing companies or organizations |
Inputs used
| bus_factor | 2 |
| contributors_sampled | 9 |
| top_contributor_share | 0.4 |
Issue & PR responsiveness
81Excellent
How it's scored
| 34.6/42 | Issue resolution — 82% of issues closed |
| 28.2/30 | PR acceptance — 161/171 decided PRs merged |
| 0/13 | Newcomer PR acceptance — no first-time contributor's PR decided in 30d |
| 7.5/15 | OpenSSF Scorecard: Code-Review — Found 2/4 approved changesets -- score normalized to 5 |
Inputs used
| merged_prs | 161 |
| open_issues | 20 |
| closed_issues | 93 |
| prs_merged_7d | — |
| prs_decided_7d | — |
| prs_merged_30d | — |
| prs_decided_30d | — |
| issue_closed_ratio | 0.823 |
| closed_unmerged_prs | 10 |
| first_time_authors_30d | — |
| first_time_prs_merged_30d | — |
| first_time_prs_decided_30d | — |
Excluded from scoring (no data or not applicable): newcomer_pr_acceptance. Remaining weights renormalized.
Ownership & stewardship
55Moderate
How it's scored
| 30/30 | Ownership backing — organization-owned |
| 0/20 | Verified domain |
| 10.3/25 | Owner reach — 26 followers of BrainLesion |
| 15/25 | Track record — 17 public repos, account ~2 yr old |
Inputs used
| followers | 26 |
| owner_type | Organization |
| is_verified | — |
| owner_login | BrainLesion |
| public_repos | 17 |
| account_age_days | 1,067 |
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 — 82 published versions |
| 20/20 | Not deprecated — active, not deprecated or yanked |
Inputs used
| packages | panoptica |
| ecosystems | pypi |
| any_deprecated | no |
| min_days_since_publish | 10 |
Engineering Quality
Are baseline engineering and documentation practices in place?
92
Engineering practices
94Exceptional
How it's scored
| 24/24 | CI workflows — 3 workflow(s) |
| 24/24 | Tests present |
| 16/16 | Linter config |
| 9.6/9.6 | Pre-commit hooks |
| 0/6.4 | .editorconfig |
| 20/20 | OpenSSF Scorecard: CI-Tests — 4 out of 4 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://arxiv.org/abs/2312.02608 |
| 10/10 | Repository description |
| 10/10 | Topics — 8 topics |
| 0/10 | Wiki |
Inputs used
| topics | 3d, evaluation, instance, metrics, panoptic, segmentation, semantic, instance-wise |
| has_wiki | no |
| homepage | https://arxiv.org/abs/2312.02608 |
| 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?
54
Security posture
42Weak
How it's scored
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 3/7.5 | Branch-Protection — branch protection is not maximal on development and all release branches |
| 2.5/2.5 | CI-Tests — 4 out of 4 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 |
| 3.8/7.5 | Code-Review — Found 2/4 approved changesets -- score normalized to 5 |
| 2.5/2.5 | Contributors — project has 5 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 8 issue activity found in the last 90 days -- score normalized to 10 |
| 0/5 | Packaging — no data |
| 0/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
| 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 — no data |
| 0/7.5 | Token-Permissions — detected GitHub workflow tokens with excessive permissions |
| 0/7.5 | Vulnerabilities — 29 existing vulnerabilities detected |
Inputs used
| source | openssf_scorecard |
| checks_evaluated | 16 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 2 |
| scorecard_aggregate | 4.2 |
Excluded from scoring (no data or not applicable): packaging, signed_releases. Remaining weights renormalized.
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 | 26 |
| 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:panoptica@2.1.4 runtime dependency closure — what installing the published package pulls in — 26 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.
49
Agent context & guidance
21At Risk
How it's scored
| 0/45 | Agent instructions — no CLAUDE.md / AGENTS.md / editor rules |
| 0/15 | Machine-readable docs (llms.txt) |
| 21/40 | Legible commit history — 37 of 94 human commits state their intent (structured subject or explanatory body) |
Inputs used
| has_llms_txt | no |
| legible_history_share | 0.394 |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
How it's scored
| 18/18 | One-command bootstrap — docs/Makefile |
| 22/22 | Automated tests |
| 11/11 | Lint / format config |
| 0/11 | Static type checking |
| 10/10 | Reproducible environment — lockfile |
| 10/10 | Demonstrated agent practice — 17 of the last 100 commits agent-authored or agent-credited |
| 0/8 | Automated maintenance — no automated dependency updates observed |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
Inputs used
| has_nix | no |
| has_tests | yes |
| lockfiles | poetry.lock |
| has_dockerfile | no |
| typed_language | no |
| bootstrap_files | docs/Makefile |
| has_devcontainer | no |
| has_linter_config | yes |
| typecheck_configs | — |
| agent_commit_share | 0.17 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
Code legibility for models
55Moderate
How it's scored
| 0/45 | Type-checkable code — Python without a type-check config |
| 55/55 | Manageable file sizes — 0/89 source files over 60KB |
Inputs used
| primary_language | Python |
| largest_source_bytes | 42,626 |
| source_files_sampled | 89 |
| oversized_source_files | 0 |
How it's scored
| 0/40 | API schema (OpenAPI/GraphQL/proto) |
| 0/20 | MCP server |
| 40/40 | Runnable examples — examples, notebooks |
Inputs used
| example_dirs | examples, notebooks |
| has_mcp_signal | no |
| api_schema_files | — |
Key facts
33GitHub stars
9contributors
315commits, last 12 months
1days since last push
67releases
2bus factor
20open 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 ★ / 11 ⇿
0Stars
11Forks
63Releases
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.
Major 2Minor 9Patch 52
Each point covers 3 days.
OpenSSF Scorecard 4.2 / 10
4.2aggregate
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).
| 10 | Binary-Artifacts | no binaries found in the repo |
| 4 | Branch-Protection | branch protection is not maximal on development and all release branches |
| 10 | CI-Tests | 4 out of 4 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 |
| 5 | Code-Review | Found 2/4 approved changesets -- score normalized to 5 |
| 10 | Contributors | project has 5 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 8 issue activity found in the last 90 days -- score normalized to 10 |
| n/a | Packaging | packaging workflow not detected |
| 0 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 0 |
| 0 | SAST | SAST tool is not run on all commits -- score normalized to 0 |
| 0 | Security-Policy | security policy file not detected |
| n/a | Signed-Releases | no releases found |
| 0 | Token-Permissions | detected GitHub workflow tokens with excessive permissions |
| 0 | Vulnerabilities | 29 existing vulnerabilities detected |
Direct dependencies 10
| Registry | Package | Version constraint | Manifest |
|---|---|---|---|
| PyPI | numpy | >=1.22,<2.3 | pyproject.toml |
| PyPI | connected-components-3d | >=3.12.3,<4.0.0 | pyproject.toml |
| PyPI | scipy | >=1.7.0,<2.0.0 | pyproject.toml |
| PyPI | rich | >=13.6.0,<14.0.0 | pyproject.toml |
| PyPI | scikit-image | >=0.22.0,<1.0.0 | pyproject.toml |
| PyPI | ruamel.yaml | >=0.18.6,<1.0.0 | pyproject.toml |
| PyPI | plotly | >=5.16.1,<6.0.0 | pyproject.toml |
| PyPI | pandas | >=2.1.0,<3.0.0 | pyproject.toml |
| PyPI | typer | >=0.15.0,<1.0.0 | pyproject.toml |
| PyPI | tqdm | >=4.62.3 | pyproject.toml |
All dependencies 124
Full resolved dependency set from the GitHub dependency graph: 10 direct and 114 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.
| Registry | Package | Version | Relation |
|---|---|---|---|
| PyPI | connected-components-3d | 3.26.1 | direct |
| PyPI | numpy | 2.2.6 | direct |
| PyPI | pandas | 2.3.3 | direct |
| PyPI | plotly | 5.24.1 | direct |
| PyPI | rich | 13.9.4 | direct |
| PyPI | ruamel-yaml | 0.19.1 | direct |
| PyPI | scikit-image | 0.25.2 | direct |
| PyPI | scipy | 1.15.3 | direct |
| PyPI | tqdm | 4.67.3 | direct |
| PyPI | typer | 0.24.1 | direct |
| PyPI | accessible-pygments | 0.0.5 | indirect |
| PyPI | alabaster | 1.0.0 | indirect |
| PyPI | annotated-doc | 0.0.4 | indirect |
| PyPI | ast-serialize | 0.5.0 | indirect |
| PyPI | babel | 2.18.0 | indirect |
| PyPI | beautifulsoup4 | 4.14.3 | indirect |
| PyPI | certifi | 2026.2.25 | indirect |
| PyPI | cfgv | 3.5.0 | indirect |
| PyPI | charset-normalizer | 3.4.7 | indirect |
| PyPI | click | 8.3.2 | indirect |
| PyPI | colorama | 0.4.6 | indirect |
| PyPI | coverage | 7.13.5 | indirect |
| PyPI | cuda-bindings | 13.2.0 | indirect |
| PyPI | cuda-pathfinder | 1.5.2 | indirect |
| PyPI | cuda-toolkit | 13.0.2 | indirect |
| PyPI | distlib | 0.4.0 | indirect |
| PyPI | docutils | 0.21.2 | indirect |
| PyPI | exceptiongroup | 1.3.1 | indirect |
| PyPI | filelock | 3.25.2 | indirect |
| PyPI | fsspec | 2026.3.0 | indirect |
| PyPI | furo | 2025.12.19 | indirect |
| PyPI | future | 0.18.3 | indirect |
| PyPI | identify | 2.6.18 | indirect |
| PyPI | idna | 3.11 | indirect |
| PyPI | imageio | 2.37.3 | indirect |
| PyPI | imagesize | 1.5.0 | indirect |
| PyPI | importlib-resources | 6.5.2 | indirect |
| PyPI | iniconfig | 2.3.0 | indirect |
| PyPI | jinja2 | 3.1.6 | indirect |
| PyPI | joblib | 1.5.3 | indirect |
| PyPI | lazy-loader | 0.5 | indirect |
| PyPI | librt | 0.11.0 | indirect |
| PyPI | markdown-it-py | 3.0.0 | indirect |
| PyPI | markupsafe | 3.0.3 | indirect |
| PyPI | mdit-py-plugins | 0.5.0 | indirect |
| PyPI | mdurl | 0.1.2 | indirect |
| PyPI | mpmath | 1.3.0 | indirect |
| PyPI | mypy | 2.1.0 | indirect |
| PyPI | mypy-extensions | 1.1.0 | indirect |
| PyPI | myst-parser | 4.0.1 | indirect |
| PyPI | networkx | 3.4.2 | indirect |
| PyPI | nibabel | 5.4.2 | indirect |
| PyPI | nodeenv | 1.10.0 | indirect |
| PyPI | nvidia-cublas | 13.1.0.3 | indirect |
| PyPI | nvidia-cublas-cu12 | 12.6.4.1 | indirect |
| PyPI | nvidia-cuda-cupti | 13.0.85 | indirect |
| PyPI | nvidia-cuda-cupti-cu12 | 12.6.80 | indirect |
| PyPI | nvidia-cuda-nvrtc | 13.0.88 | indirect |
| PyPI | nvidia-cuda-nvrtc-cu12 | 12.6.77 | indirect |
| PyPI | nvidia-cuda-runtime | 13.0.96 | indirect |
| PyPI | nvidia-cuda-runtime-cu12 | 12.6.77 | indirect |
| PyPI | nvidia-cudnn-cu12 | 9.5.1.17 | indirect |
| PyPI | nvidia-cudnn-cu13 | 9.19.0.56 | indirect |
| PyPI | nvidia-cufft | 12.0.0.61 | indirect |
| PyPI | nvidia-cufft-cu12 | 11.3.0.4 | indirect |
| PyPI | nvidia-cufile | 1.15.1.6 | indirect |
| PyPI | nvidia-cufile-cu12 | 1.11.1.6 | indirect |
| PyPI | nvidia-curand | 10.4.0.35 | indirect |
| PyPI | nvidia-curand-cu12 | 10.3.7.77 | indirect |
| PyPI | nvidia-cusolver | 12.0.4.66 | indirect |
| PyPI | nvidia-cusolver-cu12 | 11.7.1.2 | indirect |
| PyPI | nvidia-cusparse | 12.6.3.3 | indirect |
| PyPI | nvidia-cusparse-cu12 | 12.5.4.2 | indirect |
| PyPI | nvidia-cusparselt-cu12 | 0.6.3 | indirect |
| PyPI | nvidia-cusparselt-cu13 | 0.8.0 | indirect |
| PyPI | nvidia-nccl-cu12 | 2.26.2 | indirect |
| PyPI | nvidia-nccl-cu13 | 2.28.9 | indirect |
| PyPI | nvidia-nvjitlink | 13.0.88 | indirect |
| PyPI | nvidia-nvjitlink-cu12 | 12.6.85 | indirect |
| PyPI | nvidia-nvshmem-cu13 | 3.4.5 | indirect |
| PyPI | nvidia-nvtx | 13.0.85 | indirect |
| PyPI | nvidia-nvtx-cu12 | 12.6.77 | indirect |
| PyPI | packaging | 26.0 | indirect |
| PyPI | pathspec | 1.1.1 | indirect |
| PyPI | pillow | 12.2.0 | indirect |
| PyPI | platformdirs | 4.9.6 | indirect |
| PyPI | pluggy | 1.6.0 | indirect |
| PyPI | pre-commit | 2.21.0 | indirect |
| PyPI | pygments | 2.20.0 | indirect |
| PyPI | pynrrd | 1.1.3 | indirect |
| PyPI | pytest | 9.0.3 | indirect |
| PyPI | pytest-mock | 3.15.1 | indirect |
| PyPI | python-dateutil | 2.9.0.post0 | indirect |
| PyPI | python-discovery | 1.2.2 | indirect |
| PyPI | pytz | 2026.1.post1 | indirect |
| PyPI | pyyaml | 6.0.3 | indirect |
| PyPI | requests | 2.33.1 | indirect |
| PyPI | roman-numerals | 4.1.0 | indirect |
| PyPI | ruff | 0.15.20 | indirect |
| PyPI | setuptools | 81.0.0 | indirect |
| PyPI | shellingham | 1.5.4 | indirect |
| PyPI | simpleitk | 2.5.3 | indirect |
| PyPI | six | 1.17.0 | indirect |
| PyPI | snowballstemmer | 3.0.1 | indirect |
| PyPI | soupsieve | 2.8.3 | indirect |
| PyPI | sphinx | 8.1.3 | indirect |
| PyPI | sphinx-basic-ng | 1.0.0b2 | indirect |
| PyPI | sphinx-copybutton | 0.5.2 | indirect |
| PyPI | sphinxcontrib-applehelp | 2.0.0 | indirect |
| PyPI | sphinxcontrib-devhelp | 2.0.0 | indirect |
| PyPI | sphinxcontrib-htmlhelp | 2.1.0 | indirect |
| PyPI | sphinxcontrib-jsmath | 1.0.1 | indirect |
| PyPI | sphinxcontrib-qthelp | 2.0.0 | indirect |
| PyPI | sphinxcontrib-serializinghtml | 2.0.0 | indirect |
| PyPI | sympy | 1.14.0 | indirect |
| PyPI | tenacity | 9.1.4 | indirect |
| PyPI | tifffile | 2025.5.10 | indirect |
| PyPI | tomli | 2.4.1 | indirect |
| PyPI | torch | 2.7.1 | indirect |
| PyPI | triton | 3.3.1 | indirect |
| PyPI | typing-extensions | 4.15.0 | indirect |
| PyPI | tzdata | 2026.1 | indirect |
| PyPI | urllib3 | 2.6.3 | indirect |
| PyPI | virtualenv | 21.2.1 | indirect |
Dependency advisories 0
Installing pypi:panoptica@2.1.4 pulls in 26 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
{
"data": {
"repo": {
"topics": [
"3d",
"evaluation",
"instance",
"metrics",
"panoptic",
"segmentation",
"semantic",
"instance-wise"
],
"is_fork": false,
"size_kb": 8202,
"has_wiki": false,
"homepage": "https://arxiv.org/abs/2312.02608",
"languages": {
"Python": 772546,
"Jupyter Notebook": 310710
},
"pushed_at": "2026-07-29T14:51:31Z",
"created_at": "2023-10-05T00:58:57Z",
"owner_type": "Organization",
"updated_at": "2026-07-29T09:29:04Z",
"description": "panoptica -- instance-wise evaluation of 3D semantic and instance segmentation maps",
"is_archived": false,
"is_disabled": false,
"license_spdx": "Apache-2.0",
"default_branch": "main",
"license_spdx_raw": "Apache-2.0",
"primary_language": "Python",
"significant_languages": [
"Python",
"Jupyter Notebook"
]
},
"owner": {
"blog": "https://arxiv.org/abs/2507.09036",
"name": "BrainLesion Suite",
"type": "Organization",
"login": "BrainLesion",
"company": null,
"location": null,
"followers": 26,
"avatar_url": "https://avatars.githubusercontent.com/u/143446642?v=4",
"created_at": "2023-08-28T19:20:30Z",
"is_verified": null,
"public_repos": 17,
"account_age_days": 1067
},
"license": {
"state": "standard",
"spdx_id": "Apache-2.0",
"raw_spdx": "Apache-2.0",
"file_present": true,
"scorecard_found": true,
"profile_has_license": true
},
"activity": {
"releases": [
{
"tag": "v2.1.4",
"kind": "patch",
"published_at": "2026-07-20T14:53:15Z"
},
{
"tag": "v2.1.3",
"kind": "patch",
"published_at": "2026-07-08T15:29:40Z"
},
{
"tag": "v2.1.2",
"kind": "patch",
"published_at": "2026-06-30T08:32:58Z"
},
{
"tag": "v2.1.1",
"kind": "patch",
"published_at": "2026-06-15T22:01:32Z"
},
{
"tag": "v2.1.0",
"kind": "minor",
"published_at": "2026-05-22T16:00:02Z"
},
{
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"headline": "added unit tests that checks all our current test cases with 0 threshold",
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"body": "Each instance metric was registered by hand: a per-metric # region block in\nPanopticaResult.__init__ (sq / sq_std / pq via _add_metric) plus a matching set of\nmodule-level sq_X / sq_X_std / pq_X calc functions. Adding a metric meant editing\nboth places in lockstep.\n\nReplace both with a single _INSTA\n[…]\n\nbyte-identical (verified against a snapshot of main and the full metric test suite).\nNet ~226 fewer lines in panoptica_result.py.\n\nCloses #189\n\nCo-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>",
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"headline": "Auto-generate instance metric members from a spec table",
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"body": "Implements the requested lesion-/instance-wise recall by user-supplied volume bins.\nrecall_by_volume_bins(volumes, matched_flags, thresholds) buckets reference instances\ninto len(thresholds)+1 bins (rec_q0..rec_qn) and reports the matched fraction per bin;\nempty bins yield nan. The thresholds are ap\n[…]\nll_by_volume(thresholds, volume=\"volume\"|\"voxel_count\"):\n single-sample helper from the matched/unmatched reference volume lists.\n\nCloses #241\n\nCo-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>",
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"headline": "Add instance detection recall stratified by volume (recall_by_volume)",
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"body": "score_beats_threshold only supported >= / <=, so matching_threshold=0 accepted\nevery overlapping pair and users had to pass a tiny epsilon to mean \"any real\noverlap\". Add a strict flag to Metric.score_beats_threshold (strict uses > for\nincreasing metrics and < for decreasing ones) and a strict_thres\n[…]\n MaximizeMerge) and their YAML serialization. With\nstrict_threshold=True a score exactly equal to the threshold no longer matches.\n\nCloses #218\n\nCo-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>",
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"body": "When several segmentation class groups are configured but only a subset is of\ninterest, callers had to evaluate everything and discard the rest. Add an optional\nskip_groups: list[str] argument to both Panoptica_Evaluator.evaluate() and\nevaluate_autc(): named groups are omitted from the returned dict\n[…]\n with a\nwarning via the panoptica logger rather than raising, so a stale skip list can never\nsilently turn into \"skip everything\".\n\nCloses #221\n\nCo-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>",
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"body": "panoptica routes its output through logging.getLogger(\"panoptica\") but offered no\npublic way to change its level without importing logging and knowing the logger\nname. Add set_log_level(level), accepting either an int (logging.WARNING) or a\ncase-insensitive level name (\"WARNING\"), and re-export it from the top-level\npackage. Callers can now do panoptica.set_log_level(\"WARNING\") to silence routine\nstatus messages.\n\nCloses #213\n\nCo-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>",
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"body": "Now that the code is clean, turn on the gates:\n- ruff (lint + format) and mypy configured in pyproject.toml; import sorting is\n intentionally disabled (order-sensitive circular imports);\n- a CI \"lint\" job runs ruff check, ruff format --check and mypy as required\n checks; mypy is blocking because the package is now mypy-clean;\n- .pre-commit-config.yaml runs ruff on commit;\n- benchmark/bench_eval.py to measure the compute-heavy paths.\n\nCo-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>",
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"body": "Brings the rest of the package to its final state:\n- None-sentinel argument defaults in Panoptica_Evaluator and EdgeCaseHandler;\n- removed dead code (DirectValueMeta) and dead imports; small lint fixes\n (closure-captured loop vars, raise-from, *args-after-kwargs);\n- accurate docstrings in place of \n[…]\nis mypy-clean (numpy_utils bbox\n helpers reworked, Optional threaded through, etc.).\n\nBehaviour is unchanged; the full test suite stays green.\n\nCo-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>",
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"headline": "Finish the refactor: remaining cleanup, type hints, and docstrings",
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"body": "Add panoptica.utils.logger (a rich-backed logging.Logger with no panoptica\nimports, so it is free of the package's import cycles) and route the\ndiagnostic/status/error print() calls through it -- output is now structured,\nlevel-filterable and silenceable. Genuinely user-facing output (CLI, citation\n\n[…]\nment defaults,\n_ProcessingPair de-mangling and type hints that live in these files. Behaviour\nis unchanged and the full test suite stays green.\n\nCo-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>",
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"body": "Behavior-preserving performance work across the metric and evaluation code,\neach covered by regression tests:\n\n- Vectorize IoU/Dice instance matching with np.unique + bincount instead of a\n per-pair full-array metric evaluation (O(pairs*voxels) -> O(voxels+pairs)).\n- Share the two directional surfa\n[…]\nolumes).\n- Drop a redundant array .copy() on the per-metric/per-match hot path, and remove\n the dead commented-out multiprocessing Pool block.\n\nCo-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>",
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{
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{
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{
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{
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{
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{
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"components": [
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{
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{
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{
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{
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{
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{
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{
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"points": 7.5,
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{
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"status": "excluded",
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{
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{
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"status": "missed",
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{
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"status": "missed",
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{
"key": "signed_releases",
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"status": "excluded",
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"code": "no_data",
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],
"max_points": 7.5
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{
"key": "token_permissions",
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"status": "missed",
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{
"key": "vulnerabilities",
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"status": "missed",
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]
},
{
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"notes": [
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"code": "advisories_scope_published",
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"params": {}
}
],
"value": 100,
"inputs": {
"source": "osv",
"advisories": 0,
"affected_packages": 0,
"assessed_packages": 26,
"unassessed_packages": 0,
"affected_by_severity": "none",
"direct_affected_packages": 0
},
"components": [
{
"key": "direct_dependencies_free_of_known_advisories",
"name": "Direct dependencies free of known advisories",
"detail": "no direct dependency carries a known advisory",
"points": 35,
"status": "met",
"details": [
{
"code": "no_direct_advisories",
"params": {}
}
],
"max_points": 35
},
{
"key": "indirect_dependencies_free_of_known_advisories",
"name": "Indirect dependencies free of known advisories",
"detail": "no indirect dependency carries a known advisory",
"points": 25,
"status": "met",
"details": [
{
"code": "no_indirect_advisories",
"params": {}
}
],
"max_points": 25
},
{
"key": "no_advisories_left_outstanding",
"name": "No advisories left outstanding",
"detail": "no advisory carries a publication date",
"points": 0,
"status": "excluded",
"details": [
{
"code": "advisories_no_publication_date",
"params": {}
}
],
"max_points": 40
}
]
},
{
"key": "malicious_dependencies",
"band": "exceptional",
"name": "Malicious dependencies",
"note": null,
"notes": [],
"value": 100,
"inputs": {
"source": "osv",
"meaning": "reported as a malicious package by the OpenSSF corpus; the remedy is removal or moving off the compromised name, never an upgrade of the same artifact. Versions the registry has since pulled are listed but not scored",
"packages": [],
"red_flag": false,
"assessed_packages": 26,
"malicious_packages": 0,
"direct_malicious_packages": 0,
"withdrawn_malicious_packages": 0,
"installable_malicious_packages": 0
},
"components": [
{
"key": "no_dependency_reported_as_a_malicious_package",
"name": "No dependency reported as a malicious package",
"detail": "no dependency is reported as a malicious package",
"points": 100,
"status": "met",
"details": [
{
"code": "no_malicious_dependencies",
"params": {}
}
],
"max_points": 100
}
]
},
{
"key": "high_risk_jurisdiction_exposure",
"band": "exceptional",
"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"
],
"commit_weight_rule": {
"min_commits": 50,
"min_commit_share": 0.1
},
"review_only_matches": 0,
"below_threshold_exposures": [],
"assessed_self_published_locations": 4
},
"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": "weak",
"name": "AI Readiness",
"value": 49,
"weight": 0.04,
"metrics": [
{
"key": "ai_agent_context",
"band": "at_risk",
"name": "Agent context & guidance",
"note": null,
"notes": [],
"value": 21,
"inputs": {
"has_llms_txt": false,
"legible_history_share": 0.394,
"agent_instruction_files": [],
"agent_instruction_max_bytes": null
},
"components": [
{
"key": "agent_instructions",
"name": "Agent instructions",
"detail": "no CLAUDE.md / AGENTS.md / editor rules",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_agent_instructions",
"params": {}
}
],
"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": "37 of 94 human commits state their intent (structured subject or explanatory body)",
"points": 21,
"status": "partial",
"details": [
{
"code": "legible_history",
"params": {
"legible": 37,
"sampled": 94
}
}
],
"max_points": 40
}
]
},
{
"key": "ai_verify_loop",
"band": "good",
"name": "Verify loop (build / test / typecheck)",
"note": null,
"notes": [],
"value": 71,
"inputs": {
"has_nix": false,
"has_tests": true,
"lockfiles": [
"poetry.lock"
],
"has_dockerfile": false,
"typed_language": false,
"bootstrap_files": [
"docs/Makefile"
],
"has_devcontainer": false,
"has_linter_config": true,
"typecheck_configs": [],
"agent_commit_share": 0.17,
"toolchain_manifests": [],
"dependency_bot_commit_share": 0
},
"components": [
{
"key": "one_command_bootstrap",
"name": "One-command bootstrap",
"detail": "docs/Makefile",
"points": 18,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "docs/Makefile"
}
}
],
"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": 11,
"status": "met",
"details": [],
"max_points": 11
},
{
"key": "static_type_checking",
"name": "Static type checking",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "reproducible_environment",
"name": "Reproducible environment",
"detail": "lockfile",
"points": 10,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "lockfile"
}
}
],
"max_points": 10
},
{
"key": "demonstrated_agent_practice",
"name": "Demonstrated agent practice",
"detail": "17 of the last 100 commits agent-authored or agent-credited",
"points": 10,
"status": "met",
"details": [
{
"code": "agent_authored_commits",
"params": {
"count": 17,
"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 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
}
]
},
{
"key": "ai_code_legibility",
"band": "moderate",
"name": "Code legibility for models",
"note": null,
"notes": [],
"value": 55,
"inputs": {
"primary_language": "Python",
"largest_source_bytes": 42626,
"source_files_sampled": 89,
"oversized_source_files": 0
},
"components": [
{
"key": "type_checkable_code",
"name": "Type-checkable code",
"detail": "Python without a type-check config",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_typecheck_config_language",
"params": {
"language": "Python"
}
}
],
"max_points": 45
},
{
"key": "manageable_file_sizes",
"name": "Manageable file sizes",
"detail": "0/89 source files over 60KB",
"points": 55,
"status": "met",
"details": [
{
"code": "oversized_source_files",
"params": {
"kb": 60,
"sampled": 89,
"oversized": 0
}
}
],
"max_points": 55
}
]
},
{
"key": "ai_interfaces",
"band": "weak",
"name": "Machine-readable interfaces",
"note": null,
"notes": [],
"value": 40,
"inputs": {
"example_dirs": [
"examples",
"notebooks"
],
"has_mcp_signal": false,
"api_schema_files": []
},
"components": [
{
"key": "api_schema_openapi_graphql_proto",
"name": "API schema (OpenAPI/GraphQL/proto)",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 40
},
{
"key": "mcp_server",
"name": "MCP server",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 20
},
{
"key": "runnable_examples",
"name": "Runnable examples",
"detail": "examples, notebooks",
"points": 40,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "examples, notebooks"
}
}
],
"max_points": 40
}
]
}
],
"description": "How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight: agent tooling is a real maintenance signal, but its absence must never gate the top of the scale (calibration saturates at raw 91, so 100/100 remains reachable with AI Readiness at zero)."
}
],
"classification": {
"top": [
"library",
"application"
],
"labels": [
"library",
"cli"
],
"scores": {
"cli": 4,
"library": 6
},
"primary": "library",
"evidence": [
{
"tier": "distribution",
"label": "library",
"source": "registry:pypi",
"weight": 6
},
{
"tier": "dependencies",
"label": "cli",
"source": "dep:typer",
"weight": 4
}
],
"artifacts": [],
"confidence": "medium",
"host_extension": false,
"runs_as_process": true,
"consumed_by_code": true
},
"metrics_version": "2.5.0"
},
"warnings": [
"Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token"
],
"report_type": "repository",
"generated_at": "2026-07-31T00:22:56.922370Z",
"schema_version": "0.27.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/b/BrainLesion/panoptica.svg",
"full_name": "BrainLesion/panoptica",
"license_state": "standard",
"license_spdx": "Apache-2.0"
}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 v2.5.0, schema v0.27.0 — full methodology · metrics wiki.
How one result sits in the wider record: aggregate statistics — PyPI.