hatlem/nmiai-norgesgruppen
By hatlem · ↓ 0 · ♥ 0 · Updated 2026-03-22
What's in this repo
This page lists the files in hatlem/nmiai-norgesgruppen, including aug_v2_best.onnx, fold0_best.onnx, fold2_best.onnx and more.
- 12 ONNX models (.onnx files)
- 14 files, including 12 .onnx, 1 .md
- Last updated 2026-03-22
ONNX files
| File | Size | Download |
|---|---|---|
| aug/aug_v2_best.onnx | — | Download |
| ensemble/fold0_best.onnx | — | Download |
| ensemble/fold2_best.onnx | — | Download |
| ensemble/pseudo_best.onnx | — | Download |
| folds/fold1_best.onnx | — | Download |
| folds/fold4_best.onnx | — | Download |
| fulldata/fulldata_best.onnx | — | Download |
| highres/img1600_best.onnx | — | Download |
| multi/multi_best_v2.onnx | — | Download |
| progressive/progressive_best.onnx | — | Download |
Showing 10 of 12 .onnx files — see the full file list on the right.
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
NM i AI 2026 — NorgesGruppen Object Detection Models
YOLO26-x multi-class object detection models trained for the NorgesGruppen grocery shelf detection task.
Ensemble (submission #8: mAP@0.5 = 0.9139)
ensemble/pseudo_best.onnx— Pseudo-label model (mAP50=0.789)ensemble/fold0_best.onnx— K-fold 0 (mAP50=0.726)ensemble/fold2_best.onnx— K-fold 2 (mAP50=0.749)
Combined with WBF (Weighted Box Fusion) + TTA.
Additional Models
folds/— K-fold 1, 4multi/— Multi-class v2single/— Full-data YOLO26 single modelprogressive/— Progressive resize pretrainedpseudo/— Pseudo-label long trainingaug/— Augmentation v2highres/— 1600px resolution
License
MIT
Files (14)
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