Scallop Yolo26x Lr 1280 v2

--- license: cc-by-4.0 library_name: ultralytics tags: - yolo - yolo26x - object-detection - marine-biology - underwater - fishingrov pipeline_tag: object-detection --- # FishingROV YOLO26x L/R 1280 v2 (WIP) **Work in progress**: this public release is for transparency and community testing. Metrics and deployment packaging may change. ## Function 5-class scallop detector trained as a **teacher/pseudo-labeler** for FishingROV. Classes: - scallop - king - queen - dead - recessed ## Input format (Left/Right) Training/eval data are generated from 1920x1080 frames split into **left and right panels**, each rendered as 1280-scale inputs for detection (L/R panel workflow). ## Current metrics From run artifact `results.csv` (`best mAP50` row): - best mAP50: **0.4109** - mAP50-95 at best mAP50: **0.2664** - best epoch: **102** From class evaluation artifact `class_eval_best.json`: - precision: **0.5303** - recall: **0.4118** - mAP50: **0.4317** - mAP50-95: **0.2723** ## Attribution & License This model is a derivative work based on the **University of St Andrews King Scallop dataset**. - Original DOI: [10.5281/zenodo.10156830](https://doi.org/10.5281/zenodo.10156830) In accordance with the original dataset terms, this derivative work is released under the **Creative Commons Attribution 4.0 International (CC-BY 4.0)** license. ## Included artifacts - `best.pt` - `results.csv` - `class_eval_best.json` - `public_FishingROV_model_card_example.md` (pulled from public FishingROV repo for provenance/template continuity)

Source context: 9 downloads · 0 likes · Pipeline object-detection · Library ultralytics · Repo FishingROV/scallop_yolo26x_lr_1280_v2