Decision D13 — face inference runtime and model licensing. The runtime half is answered; the licensing half is open.
Why it is not just paperwork
Two face models already ship in models/, and a YOLO segmentation model ships in core/dr-segment/models/. The licences under which those may be redistributed inside a GPLv3 application are unsettled — for models that are already in the tree, not hypothetical ones.
docs/faces.md records the problem directly, and S14 measured the pipeline over an 18,143-face library without settling it.
Consequence
It blocks #21 — AI denoise — because adding a third learned stage adds a third licence to answer for.
What closes this
A decision recorded in requirements.md: for each shipped model, the licence, whether redistribution inside a GPLv3 binary is permitted, and what the fallback is if it is not. Not code.
See docs/outstanding.md §3 and docs/faces.md.
**Decision D13 — face inference runtime and model licensing.** The runtime half is answered; the licensing half is open.
## Why it is not just paperwork
Two face models already ship in `models/`, and a YOLO segmentation model ships in `core/dr-segment/models/`. The licences under which those may be redistributed inside a GPLv3 application are unsettled — for models that are **already in the tree**, not hypothetical ones.
`docs/faces.md` records the problem directly, and S14 measured the pipeline over an 18,143-face library without settling it.
## Consequence
It blocks #21 — AI denoise — because adding a third learned stage adds a third licence to answer for.
## What closes this
A decision recorded in `requirements.md`: for each shipped model, the licence, whether redistribution inside a GPLv3 binary is permitted, and what the fallback is if it is not. Not code.
See `docs/outstanding.md` §3 and `docs/faces.md`.
Position recorded 2026-09-19 (5fe88af): non-commercial software, self-installed, using the weights under their research grant as such, with the risks written where the decision is — the grant binds every user, it is not GPL-compatible, it rules out every public channel, and publishing is what reopens the decision. NFR-COMPAT-2 now names self-distribution only for that reason. S14's licence search remains the way to close it; that is not this issue.
Position recorded 2026-09-19 (5fe88af): non-commercial software, self-installed, using the weights under their research grant as such, with the risks written where the decision is — the grant binds every user, it is not GPL-compatible, it rules out every public channel, and publishing is what reopens the decision. NFR-COMPAT-2 now names self-distribution only for that reason. S14's licence search remains the way to close it; that is not this issue.
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Decision D13 — face inference runtime and model licensing. The runtime half is answered; the licensing half is open.
Why it is not just paperwork
Two face models already ship in
models/, and a YOLO segmentation model ships incore/dr-segment/models/. The licences under which those may be redistributed inside a GPLv3 application are unsettled — for models that are already in the tree, not hypothetical ones.docs/faces.mdrecords the problem directly, and S14 measured the pipeline over an 18,143-face library without settling it.Consequence
It blocks #21 — AI denoise — because adding a third learned stage adds a third licence to answer for.
What closes this
A decision recorded in
requirements.md: for each shipped model, the licence, whether redistribution inside a GPLv3 binary is permitted, and what the fallback is if it is not. Not code.See
docs/outstanding.md§3 anddocs/faces.md.Blocks #21.
Position recorded 2026-09-19 (5fe88af): non-commercial software, self-installed, using the weights under their research grant as such, with the risks written where the decision is — the grant binds every user, it is not GPL-compatible, it rules out every public channel, and publishing is what reopens the decision. NFR-COMPAT-2 now names self-distribution only for that reason. S14's licence search remains the way to close it; that is not this issue.