sea-turtle-assets
Public assets for the sea turtle behavior pipeline.
Contents
| Path | Description |
|---|---|
models/yolo/best.pt |
YOLO11m-seg model — sea turtle detection |
models/yolo/inference_config.json |
Calibrated conf/iou/max_det this checkpoint needs — see below |
models/breathing/best_model.keras |
ResNet50 classifier - breathing detection |
models/breathing/optimal_threshold.json |
F1-optimal threshold for breathing classifier |
1min_sample/ |
1-minute sample clips (2 cameras, 2 days) for pipeline testing |
Downloaded automatically by setup.sh -- no manual action needed.
YOLO inference settings
Always run this model with max_det=1 — every tank holds exactly one turtle,
so this is a domain constraint, not a tuning choice. Use inference_config.json's
conf (0.40) rather than a generic default: it's calibrated against the full
validation set under max_det=1, the model's actual deployment shape, and
holds P=R=F1=1.0 across a wide safe range (0.05-0.75) rather than sitting at
either edge of it.
2026-09-05: replaced the previous checkpoint, which scored well on paper (fitness in the top 10 of ~40 sweep runs) but had 89 false positives and 80% recall when actually run at real inference settings. Root cause was two independent bugs — a checkpoint-selection bug in training.py that could save the wrong epoch's weights as best.pt, and 2 of 50 validation images carrying duplicate ground-truth labels — both since fixed. This checkpoint is a full retrain under the corrected code and corrected labels, verified with a clean P=R=F1=1.0 sweep on the full val set.