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:
@@ -2,6 +2,9 @@
|
||||
|
||||
[](https://github.com/sudolulo/winnow/actions/workflows/docker-publish.yml) [](https://github.com/sudolulo/winnow/actions/workflows/test.yml) [](https://github.com/sudolulo/winnow/releases/latest) [](LICENSE) [](https://immich.app) [](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
|
||||
|
||||
|
||||
Reference in New Issue
Block a user