onnxruntime-gpu has no arm64 wheels (manylinux_2_27_x86_64 /
manylinux_2_28_x86_64 only). uv sync --frozen failed on the arm64
image with exit code 2. Gated onnxruntime-gpu behind the x86_64
marker; arm64 and non-Linux use the CPU onnxruntime package. Added
required-environments so the lockfile is solved for both platforms.
Removed onnxruntime-gpu from override-dependencies (it had no marker
support and blocked arm64 resolution).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
curl|gpg --dearmor was silently dropping the deadsnakes key (gpg exits 0
on bad input), leaving apt unable to find python3.13. Reverted to
add-apt-repository with GNUPGHOME=$(mktemp -d) to isolate gpg from any
pre-existing agent socket. Removed --platform=\$BUILDPLATFORM from the
arm64 base so the image contains real arm64 binaries. License updated
from MIT to AGPL-3.0-or-later.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Title first, then badges on one consistent line. Removed redundant
Release and Lint badges. Fixed docs links to point to the wiki.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Ubuntu 26.04 ships Python 3.14, not 3.13. Reverted arm64 to ubuntu:24.04.
Both architectures now add the deadsnakes PPA by fetching the GPG key via
curl and piping through gpg --dearmor — no gpg-agent, safe under QEMU.
Removes the per-arch conditional and ARG TARGETARCH dependency in RUN commands.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Docker automatic platform ARGs are only in scope for FROM instructions.
$TARGETARCH in RUN commands was always empty, so the deadsnakes PPA
conditional never ran and python3.13 could not be found on the Ubuntu
22.04 CUDA base.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
All platforms now use Python 3.13. amd64 installs via deadsnakes PPA on
the Ubuntu 22.04 CUDA base; arm64 gets Python 3.13 natively from Ubuntu
26.04. Verified cp313 wheels exist for onnxruntime-gpu 1.26.0 and
torch 2.12.0+cu126. uv.lock regenerated under CPython 3.13.5.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
add-apt-repository ppa:deadsnakes/ppa fails on arm64 in GitHub Actions
because QEMU emulation doesn't support the GPG agent. Ubuntu 24.04 ships
Python 3.12 natively so the PPA is not needed. amd64 (CUDA/Ubuntu 22.04
base) still uses the PPA. PPA install is now gated on TARGETARCH=amd64.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
uv lock --check in a separate job races against the update-lockfile
bot. Replace with uv lock inline in release.yml and drop the pre-job
from docker-publish.yml entirely.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Store Immich face confidence scores per asset in frigate_uploaded_ids.json
- Add frigate_api.py: query GET /api/faces to count trained images per person
- Record Frigate training count as frigate_count in tracker for offline fallback
- MAX_AUTO_IMAGES cap now uses live Frigate count → cached frigate_count → local uploaded count
- Startup summary shows last known Frigate training count per person
- Migrate by_person entries from flat list to {asset_ids, scores, frigate_count} dict
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Adds context that winnow is especially useful for people who aren't
around enough for Frigate's live detections to supply adequate training
data on their own.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Advises users to review Frigate uploads after a run and remove bad
crops manually. Links to GitHub Issues for feedback.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- entrypoint.sh: replace `uv run` with `/app/.venv/bin/python` to skip
uv's sync check which was re-downloading ruff and rebuilding the package
on every container startup
- compose.yml, .env.example: fix INSIGHTFACE_HOME /models → /models/.insightface;
InsightFace appends models/ to root, so /models produced /models/models/buffalo_l
- README.md: add Immich and Frigate badges from upstream
- CHANGELOG.md, pyproject.toml, uv.lock: bump to 0.2.1
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Runtime stage was missing WORKDIR, so uv run started from / and
couldn't find the .venv or pyproject.toml, causing "No module named
'winnow'" on container startup.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- pyproject.toml: version 0.1.0 → 0.2.0
- CHANGELOG.md: full [0.2.0] entry covering all changes since the fork —
headless operation, Docker/scheduling, object mode, people filtering,
quality controls, CI/CD, tests, docs, and all bug fixes
- uv.lock: regenerated after version bump
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add docs/setup.md, docs/troubleshooting.md, docs/faq.md as user-facing wiki
- Add .env.example with all env vars and inline comments
- Fix compose.override.yml: rename service if-curator → winnow, update volume paths
- Fix CHANGELOG.md: rename if-curator → winnow in release notes
- Link docs from README
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Describes the full pipeline (fetch → filter → embed → cluster → crop →
upload), explains why diversity matters and how the K-Medoids + FPS
selection works, covers both face and object modes in detail, and
documents all env vars in one place.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- LICENSE: add copyright line for Holden Salomon (retain original)
- pyproject.toml: update authors to Holden Salomon <holden@arch.fyi>
- README: lead with what the software does rather than fork attribution;
merge split env var tables into one unified reference; add lint/test
badges; move attribution to footer
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- dependabot.yml: add uv ecosystem (updates pyproject.toml + uv.lock
together), github-actions ecosystem (keeps action versions current),
and group all Python deps into one weekly PR
- lint.yml, test.yml: extend triggers to dev branch so ruff and pytest
run on push/PR to dev, not just main
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- config.py: wire BLUR_THRESHOLD, MIN_CONFIDENCE, MAX_AUTO_IMAGES,
FACE_MARGIN, USE_FULL_RESOLUTION, ENABLE_FACE_ALIGNMENT to env vars
(were hardcoded class defaults, inaccessible in AUTO_MODE)
- jobs.py: add LIMIT env var for custom image count in auto mode;
overrides STRATEGY preset (mirrors interactive Custom Count option)
- compose.yml: document all env vars with inline comments grouped by
concern — mode/strategy, people filtering, image quality, caching,
tracker overrides, scheduling
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Volume was mounted at /app/output but OUTPUT_DIR defaults to
./frigate_train (i.e. /app/frigate_train). Mount was never being used.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- upload_to_frigate() now only processes face-mode jobs; object crops are
saved to the output directory as the deliverable (Frigate has no API for
object classifier training data — it must be copied manually)
- execute_jobs() only wipes the output dir for face mode; object crops
accumulate across runs as intended
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- executor.py: wipe person output dir before each run so stale crops
from previous runs don't accumulate on disk
- compose.yml: move inline comment off CRON_SCHEDULE value (croniter
would parse the comment text as part of the expression)
- compose.yml: add note clarifying <pool> placeholder in volume paths
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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