qubvel-org/segmentation_models.pytorch
What happens to a stranger's pull request here, in the Porchlamp snapshot of 14 October 2026.
Outside pull requests to segmentation_models.pytorch got a first human reply in a median of 5.4 hours (96 pull requests, 10 April to 7 October 2026). The share with no reply within 14 days has too small a sample to measure (8 pull requests counted; 10 needed). It ranks 255 of 3,833 overall and 110 of 1,968 for first-time contributors.
Rating
- Score: 65.96
- Coverage: 88% · Ceiling A
- Tier: B
- Quadrant: Sweet Spot
- Ecosystem: PyPI
Five pillars
| Pillar | Score | Coverage |
|---|---|---|
| Responsiveness | 99.7 | 60% |
| Criticality | 53.3 | 100% |
| Governance | 50.5 | 100% |
| Rigor | 53.1 | 100% |
| Accessibility | 64.4 | 85% |
Rank in each lens
| Lens | Standing |
|---|---|
| Balanced | Rank 255 of 3,833 |
| First-timer | Rank 110 of 1,968 |
| Career capital | Not ranked: This repository's production-criticality signal is not yet high enough for career-capital ranking. |
| Senior systems | Not ranked: Fewer than 3 organizations account for most commits (not multi-vendor). |
| AI-assisted | Rank 449 of 3,929 |
The measured parameters
| Parameter | Value | Count | Window | What it measures |
|---|---|---|---|---|
| Time to First Response | 5.3681 | 96 | 10 April to 7 October 2026 | Median hours from an outside pull request opening to its first substantive human reply. |
| Decision Rate (90d) | Not shown: Insufficient sample size | — | — | Share of outside pull requests that were merged or closed within 90 days. |
| First-timer Merge Rate | 0.8 | 5 | — | Share of first-time outside authors' decided pull requests that were merged. |
| PR Ghost Rate (14d) | Not shown: Insufficient sample size | — | — | Share of outside pull requests with no maintainer response, merge or close within 14 days. |
| Time to Merge (p90) | 7.7594 | 88 | 10 April to 7 October 2026 | Hours within which 90% of merged outside pull requests were merged. |
| Dependents | 42 | — | — | Packages in the registry that depend on this project, counted once each. |
| OpenSSF Criticality | 0.3558 | — | — | OpenSSF criticality score from 0 to 1, computed from the project's public activity signals. |
| Monthly Downloads | 378469 | — | — | Downloads from the package registry in a month. |
| Legal IP Regime | NONE | — | — | The contributor licence regime: DCO, none, a foundation CLA or a corporate CLA. |
| Elephant Factor | 1 | 151 | — | The fewest organisations that account for half of the last year's commits. |
| Promotion Ladder | AD_HOC | — | — | How openly a contributor can become a maintainer, from closed to verified. |
| Pipeline Defenses | 100 | 89 | — | How well the project's build and review pipeline defends against bad changes, 0 to 100. |
| AI Policy Posture | AD_HOC | — | — | Whether the project has a written policy on AI-assisted contributions. |
| Substantive Review Rate | 0.0291 | 103 | 10 April to 7 October 2026 | Share of decided pull requests that received a substantive review. |
| Newcomer Issue Supply | 2 | — | — | Open, unassigned, up-to-date issues marked for newcomers. |
| Newcomer Conversion | 0.8 | 5 | — | Share of first-time authors whose first pull request merged within 180 days. |
| Newcomer Return Rate | Not shown: Insufficient sample size | — | — | Share of those merged first-time authors who sent a second pull request within 90 days. |
| Developer Experience | 85 | 30 | — | Developer experience, 0 to 100: half CI run time, half setup signals. |
Similar projects
The ranked projects nearest this one in the same ecosystem.
- astral-sh/ty (rank 238)
- sympy/sympy (rank 246)
- plotly/plotly.py (rank 248)
- kedro-org/kedro (rank 258)
- gorakhargosh/watchdog (rank 276)
Evidence
- Snapshot 2026-10-14, data as of 13 October 2026.
- Record hash:
1b8904050b8e00a6b53519be02a95036fd15fb95b18746e45d0319163779af01 - The full record is in data/2026-10-14/repos/e0.json, under the key
qubvel-org/segmentation_models.pytorch. - How every number is measured: Porchlamp methodology.
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Open an issue about this record and say what looks wrong.