13 KiB
orisys-sensor-design
Nominal sensor geometry and Blender authoring for Orisys. This repo is the design
source of truth. Measured calibration, unroll maps, and shipped runtime bundles live in
orisys-sdk and compiled .oryscene packages live in orisys-app.
For the full long-term workflow see sensor-design-workflow.md in the workspace root.
This repository intentionally implements a minimal v1 for a small team.
Two buckets (daily work)
| Bucket | Where | Contents |
|---|---|---|
| Design | this repo | .blend, nominal export, release manifest |
| Runtime | orisys-sdk / orisys-app |
measured cal, unroll map, wheel/App assets, .oryscene |
Never copy runtime NPZ files into this repo to “fix” a mismatch. Promote through a manifest + lock file instead.
Layout
sensors/finger/
├── current.yaml # active revision pointer
└── r01/
├── design.yaml # units, frames, object names
├── source/geometry.blend # named collections + objects
├── profiles/
│ ├── compute.yaml # → SDK bundle layout (Studio runtime)
│ └── studio.yaml # inputs for orisys-app compile_scene
└── golden/ # optional preview + metrics
Prerequisites
- Python 3.10+
- Blender version pinned in
blender.lock.json(install separately)
No Git LFS is required — binaries are committed as ordinary files.
Finding Blender on Windows
The CLI looks for Blender in this order:
- Env
ORISYS_BLENDERorBLENDER_EXE(absolute path toblender.exe) blender/blender.exeonPATH- Auto-scan
%ProgramFiles%\Blender Foundation\Blender *\blender.exe(prefersblender.lock.jsonversion when installed, otherwise newest) - Optional
"executable"inblender.lock.json(local only; do not commit machine paths)
$env:ORISYS_BLENDER = "C:\Program Files\Blender Foundation\Blender 5.0\blender.exe"
Convenience launcher (auto-finds Blender for this process, then exports):
.\tools\export-compute.bat
Commands
Install the CLI (editable):
cd D:\orisys_ws\orisys-sensor-design
python -m pip install -e .
Four commands for v1:
# 1) Check revision metadata and (optionally) Blender scene conventions
orisys-design validate sensors/finger/r01
# 2) Export nominal geometry for a profile (compute → SDK layout)
orisys-design export sensors/finger/r01 --profile compute
# 3) Generate the colored patch texture headlessly
orisys-design texture sensors/finger/r01
# 4) Write release manifest with file hashes
orisys-design manifest sensors/finger/r01
Headless Blender export uses a JSON job file (stdlib json inside Blender — no
PyYAML required). orisys-design export writes it automatically from design.yaml:
orisys-design export sensors/finger/r01 --profile compute
# writes build/export/finger/r01/_export_job.json then runs Blender
Manual Blender invocation with the same job:
blender -b sensors/finger/r01/source/geometry.blend -P blender/scripts/export.py -- `
--job D:\orisys_ws\orisys-sensor-design\build\export\finger\r01\_export_job.json
Optional flag overrides (--output, --mesh, --cam, --origin) win over job values.
Export output is grouped by revision:
build/export/finger/r01/
├── _export_job.json # Blender input, regenerated by export
├── manifest.json # release manifest from `orisys-design manifest`
└── compute/ # clean SDK-shaped payload
├── mesh.npz
├── camera_intrinsics.npz
└── world_to_cam.npy
Texture patches (headless)
orisys-design texture generates a PNG, editable SVG, and native vector PDF for
each UV map on the sensing surface. The SVG/PDF are built directly from the UV
mesh and camera-space patch polygons — they do not embed or trace the PNG.
UV unwrapping is still an in-app Blender step: this command
consumes the UV maps already stored in source_blend and never creates or
unwraps one. Unwrap the mesh in the Blender GUI, save the .blend, then run the
command. A .blend saved in Edit mode is fine — the headless run enters Object
mode in memory and never writes the file.
orisys-design texture sensors/finger/r01
# writes build/textures/finger/r01/_texture_job.json then runs Blender
Output is revision-scoped, so nothing has to be copied by hand:
build/textures/finger/r01/
├── _texture_job.json # Blender input, regenerated by texture (gitignored)
├── patch_texture_produce.png # raster preview/use (tracked)
├── patch_texture_produce.svg # editable grouped vector artwork
├── patch_texture_produce.pdf # vector production/print handoff (tracked)
├── patch_texture_compute.png
├── patch_texture_compute.svg
└── patch_texture_compute.pdf
produce is the hardware-production layout and compute the compute/runtime
layout; they are the two UV maps authored on sensing_surface. Both outputs
share one set of settings and one seed, and both read the same camera-space
patch grid, so a given physical patch carries the same colour in either file —
the images differ only in how the unwrap arranges the patches.
Square in which space? The patch grid is defined in the camera image, not in
flat UV coordinates or physical surface distances. For square camera pixels,
nx / ny must match the camera image aspect ratio (80×80 for a square frame,
80×45 for 16:9). Changing the PNG dimensions does not change the camera grid.
Curvature and UV unwrapping can make these camera-space squares look rectangular,
skewed, or curved in the flat texture; that alone is not a defect. Thin spikes
outside the UV surface, however, are not expected projection distortion.
Generated artifacts are committed so a revision's textures can be synced to
hardware production. They are stored as real files, not Git LFS pointers, so a
plain git clone yields usable images and .blend files; .gitattributes only
marks binaries as non-text to protect them from line-ending conversion. Only
_texture_job.json is ignored, because it records absolute machine paths and is
rewritten every run.
SVG imports into CorelDRAW as named groups (background, mesh, patches, and
reference-cross) containing individual editable polygons. PDF contains the
same filled vector paths on a correctly sized page, with no embedded bitmap.
Seam-wrapped duplicate polygons are clipped to the page, so no stray objects sit
outside the artwork.
Defaults come from the texture_patch block in design.yaml — mesh, camera, the
uv_outputs map (UV map → artifact stem), raster dimensions, vector page size in
millimetres, patch grid, colour separation, edge sampling, reference cross, and
an optional seed. The current production page is configurable as:
vector:
width_mm: 164
height_mm: 160
CLI flags override the shared rendering values for every output:
orisys-design texture sensors/finger/r01 `
--width 1024 --height 1024 --nx 16 --ny 12 --seed 7 --no-cross
Manual Blender invocation with the same job:
blender -b sensors/finger/r01/source/geometry.blend -P blender/scripts/random_patch_dd02c.py -- `
--job D:\orisys_ws\orisys-sensor-design\build\textures\finger\r01\_texture_job.json
A single manual target is also possible (this cannot be combined with --job).
--output names the PNG; same-stem SVG/PDF files are generated alongside it.
The vector page defaults to 164×160 mm and can be overridden manually:
blender -b sensors/finger/r01/source/geometry.blend -P blender/scripts/random_patch_dd02c.py -- `
--uv-map produce --output D:\tmp\produce.png --width 1024 --height 999 `
--vector-width-mm 164 --vector-height-mm 160
Only the colored "patches" mode is reachable headlessly; the checker and dot
helpers remain in random_patch_dd02c.py but are not exposed by the CLI. The
default 3280×3200 grid matches the in-app script and is deliberately slow
(pure-Python rasterization) — use smaller --width/--height/--nx/--ny for quick
check runs, and the full default grid for the textures you actually ship.
Collection check:
blender -b sensors/finger/r01/source/geometry.blend -P blender/scripts/validate.py -- sensors/finger/r01
Profiles
compute—sensing_surface+cam_sensorrelative toorigin_sensor. Writesmesh.npz,camera_intrinsics.npz,world_to_cam.npy(here “world” means the sensor frame). Studio and the wheel build consume this tree viaorisys-sdk→assets_dir.studio— documents how to compile a.oryscenefrom the compute export plus the measured unroll map in SDK. Observation cameras in Studio are derived from mesh bounds; no Blendercam_vizis required.
Promotion (SDK / App)
After export:
- Tag this repo, e.g.
finger-r01-assets-v1.0.0. - Copy or attach the
build/export/finger/r01/compute/folder to the SDK asset path (or publish as a release artifact). - Keep
build/export/finger/r01/manifest.jsonbeside the payload, and update optionaldesign-lock.jsoninorisys-sdkwith commit + bundle SHA256. - Run
orisys-appcompile_scene.pyusing the locked compute export + SDK unroll map.
Example lock file: examples/design-lock.json.
Conventions
- Units: metres at export boundaries. Author in mm if you like; set
meters_per_source_unit: 0.001indesign.yaml. - Collections:
FRAMES,EXPORT_COMPUTE,ASSEMBLY,DESIGN_SIM,EXCLUDE. - Objects:
origin_sensor,sensing_surface,cam_sensor. - Matrix names must state direction; exported pose file remains
world_to_cam.npyfor SDK compatibility (sensor frame → camera). - Binary files:
.blend, textures and exported*.npzare committed as ordinary files (no Git LFS)..gitattributesmarks them-textonly.
Git LFS on Gitea (NAS) — not currently used
Status: this repository does not use Git LFS. .gitattributes only marks
binaries as non-text, and real .blend / .png / .pdf bytes are committed
directly. This is deliberate: LFS pointers are unusable without a reachable LFS
server, so a plain clone or git checkout would hand you 131-byte files instead
of images. The notes below are kept as a migration guide for when the NAS server
is ready.
Short answer: not difficult. Gitea has built-in LFS; NAS hosting is common. Plan for extra disk on the NAS volume that holds LFS objects, not just the git bare repos.
Server (one-time, ~5 minutes)
-
Enable LFS in Gitea — edit
app.ini(or Docker env):[server] LFS_START_SERVER = true [lfs] PATH = /data/git/lfsDocker Compose equivalent:
environment: - GITEA__server__LFS_START_SERVER=truePoint
PATHat persistent NAS storage (same volume as/datais fine). -
Restart Gitea after changing config.
-
Optional: set
LFS_JWT_SECRETin Docker/env for stable LFS auth across restarts (generate once, keep in your NAS secrets). -
Reverse proxy: LFS uploads use HTTP(S) batch API. Ensure your NAS proxy allows large request bodies (nginx
client_max_body_size, etc.). SSH git push still works for normal objects; LFS file transfer is usually HTTPS unless you enable pure SSH LFS. -
Backup: include the LFS directory in NAS backup — it is not inside git history.
Requirements: Git ≥ 2.1.2 on the server (Gitea’s embedded git is enough).
Clients (each developer)
git lfs install
git clone git@your-nas:team/orisys-sensor-design.git
cd orisys-sensor-design
git lfs pull
This repo’s .gitattributes does not track anything through LFS today. To turn
LFS on, add the extensions back with a filter (the file contains a ready-made
example line), run git add --renormalize . so real bytes become pointers, and
commit .gitattributes together with the renormalized files.
Typical pitfalls
| Issue | Fix |
|---|---|
Push succeeds but .blend is a tiny pointer file |
Run git lfs install before commit; re-add file |
| LFS upload 413 / timeout | Increase proxy body size and Gitea [server] LFS_HTTP_TIMEOUT if needed |
| Wrong permissions on NAS volume | Match container USER_UID / USER_GID to volume owner |
| Repo already has large blobs in history | Do not rewrite history casually; use git lfs migrate only with team agreement |
Pure SSH LFS (LFS_ALLOW_PURE_SSH) is optional and still has client quirks; HTTPS LFS
behind your NAS reverse proxy is the path of least resistance.
Phase plan
| Phase | Goal |
|---|---|
| A (now) | Repo + r01 + headless compute export |
| B | Lock file in SDK/App + CI reproduces export hashes |
| C (later) | Markers, camera metrics, simulation datasets |