chore: bump version to 0.4.0, update changelog and all docs

Finalizes the 0.4.0 release:

- Version bumped to 0.4.0 in pyproject.toml
- CHANGELOG.md: add [0.4.0] section covering Frigate pre-upload scoring,
  quality replacement inversion, bootstrap fix, FRIGATE_SCORE_CEILING,
  ENABLE_FRIGATE_SCORES, removal of post-upload quality gate, and all
  doc/default corrections
- README.md: step 8 updated for dual-mode replacement, FRIGATE_SCORE_CEILING
  and ENABLE_FRIGATE_SCORES added to env var table, MIN_FACE_WIDTH and
  BLUR_THRESHOLD defaults corrected (50→90, 100→120)
- .env.example: FRIGATE_SCORE_THRESHOLD replaced with FRIGATE_SCORE_CEILING;
  QUALITY_REPLACEMENT line added; comments updated to match current semantics
- winnow/executor.py: bootstrap fix — recognize now called for all below-cap
  uploads when ENABLE_FRIGATE_SCORES=true (was gated on CEILING > 0)
- winnow/upload_tracker.py: frigate_scores schema comment corrected to
  pre-upload; get_most_redundant_mapped_file() added
- winnow/frigate_api.py: recognize_face returns (face_name, score)|None tuple
  so wrong-person scores never drive replacement or ceiling decisions
- winnow/config.py: FRIGATE_SCORE_THRESHOLD renamed to FRIGATE_SCORE_CEILING;
  ENABLE_FRIGATE_SCORES added
- tests/test_upload_tracker.py: 4 new tests for get_most_redundant_mapped_file

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
2026-06-13 18:35:11 +00:00
co-authored by Claude Sonnet 4.6
parent ed045f07dd
commit 6fcea587ff
9 changed files with 213 additions and 219 deletions
+13 -6
View File
@@ -2,6 +2,9 @@
[![Docker](https://github.com/sudolulo/winnow/actions/workflows/docker-publish.yml/badge.svg)](https://github.com/sudolulo/winnow/actions/workflows/docker-publish.yml) [![Test](https://github.com/sudolulo/winnow/actions/workflows/test.yml/badge.svg)](https://github.com/sudolulo/winnow/actions/workflows/test.yml) [![GitHub release](https://img.shields.io/github/v/release/sudolulo/winnow)](https://github.com/sudolulo/winnow/releases/latest) [![License: AGPL v3](https://img.shields.io/badge/License-AGPL_v3-blue.svg)](LICENSE) [![Immich](https://img.shields.io/badge/Immich-v1.106%2B-blueviolet)](https://immich.app) [![Frigate](https://img.shields.io/badge/Frigate-Ready-brightgreen)](https://frigate.video)
> **Early Development — Use With Caution**
> winnow is functional but still maturing. Features that modify your Frigate training data — quality replacement, stale mapping cleanup — can remove images from your dataset and are not yet battle-tested at scale. Review the logs after each run and keep backups of your Frigate face training directory until you are confident in the results.
**Docs:** [Setup](https://github.com/sudolulo/winnow/wiki/Setup) · [Troubleshooting](https://github.com/sudolulo/winnow/wiki/Troubleshooting) · [FAQ](https://github.com/sudolulo/winnow/wiki/FAQ)
`winnow` pulls photos from your [Immich](https://immich.app) library, selects the most diverse and highest-quality subset using AI embeddings, and delivers them as training data for [Frigate](https://frigate.video)'s face recognition and object classification models.
@@ -56,9 +59,11 @@ Immich library
8. Deliver
• Face mode: upload crops to Frigate's face registration API
↳ below MAX_AUTO_IMAGES — upload freely
↳ at cap + QUALITY_REPLACEMENT=true — swap the lowest-scoring tracked
image if the new candidate scores higher; manually added files are
never touched
↳ at cap + QUALITY_REPLACEMENT=true — with Frigate scoring active,
swap the most redundant tracked image (highest pre-upload recognize
score) if the candidate is more novel (lower score); falling back to
blur-score comparison when no Frigate scores are available; manually
added files are never touched
↳ at cap + QUALITY_REPLACEMENT=false — skip this person
• Object mode: save crops to disk → place into your Frigate data directory
```
@@ -183,14 +188,16 @@ In scheduled mode the process (and loaded models) stays resident between runs. T
| Variable | Default | Description |
| :--- | :--- | :--- |
| `MIN_FACE_WIDTH` | `50` | Minimum face crop width in pixels |
| `MIN_FACE_WIDTH` | `90` | Minimum face crop width in pixels |
| `FACE_MARGIN` | `0.15` | Padding around bounding box crop (fraction of face size) |
| `ENABLE_FACE_ALIGNMENT` | `true` | Align to ArcFace 112×112 format using facial landmarks |
| `USE_FULL_RESOLUTION` | `true` | Download full-resolution originals rather than preview thumbnails |
| `MIN_CONFIDENCE` | `0.7` | Minimum Immich face detection confidence |
| `BLUR_THRESHOLD` | `100.0` | Laplacian variance threshold — lower accepts more blur |
| `BLUR_THRESHOLD` | `120.0` | Laplacian variance threshold — lower accepts more blur |
| `MAX_AUTO_IMAGES` | `80` | Maximum training images per person in Frigate |
| `QUALITY_REPLACEMENT` | `true` | When at cap, swap the lowest-scoring tracked image for a better candidate. Never touches manually added Frigate files. Set `false` to skip people already at cap |
| `QUALITY_REPLACEMENT` | `true` | When at cap, swap a weaker tracked image for a better candidate. With Frigate scoring active, targets the most redundant image (highest pre-upload recognize score); otherwise uses blur score. Never touches manually added Frigate files. Set `false` to skip people at cap |
| `FRIGATE_SCORE_CEILING` | `0.0` | Skip uploads whose pre-upload Frigate recognize score exceeds this value — they are already well-covered. `0` disables; requires at least one prior run to have scores |
| `ENABLE_FRIGATE_SCORES` | `true` | Call Frigate's recognize endpoint pre-upload to store diversity scores used for quality replacement. Adds ~200 ms per upload. Disable to use blur-score replacement only |
### GPU & Models