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grocery-detection-nmiai
SanderHelgesen/grocery-detection-nmiai
grocery-detection-nmiai is a object detection model from SanderHelgesen. Use it when you need objects located in an image. The card lists the license as apache-2.0.
Ensemble model for detecting and classifying grocery products on store shelves.
Access
Public
Updated Mar 22, 2026
Repo size
631 MB
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Repo makeup
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.onnx354 MB · 56%
At a glance
- Task
- Object Detection
- License
- apache-2.0
- Access
- Public
- Created
- Mar 22, 2026
- Updated
- Mar 22, 2026
- SHA
- 687c64fe
Datasets
Model card
From the Hugging Face model README
Grocery Product Detection — NM i AI Competition
Ensemble model for detecting and classifying grocery products on store shelves.
Models
- yolo26x_1600.onnx — YOLO26x detector trained at 1600px resolution
- rfdetr_large_704.onnx — RF-DETR Large detector at 704px resolution
- efficientnet_b4_classifier.safetensors — Product classifier (356 classes, FP16)
- yolo26x_best.pt — YOLO26x PyTorch weights (accuracy-focused, 500 epochs)
- yolo26x_finetuned.pt — Fine-tuned on refined Roboflow dataset
Architecture
Two-stage ensemble:
- Detection: YOLO26x + RF-DETR with Weighted Boxes Fusion
- Classification verification: EfficientNet-B4 corrects low-confidence class predictions
Competition Score
- Best public leaderboard: 0.9021
- Scoring: 0.7 × [email protected] + 0.3 × [email protected]
Training Data
- 248 shelf images from Norwegian grocery stores
- 22,731 COCO-format bounding box annotations
- 356 product categories
- Additional refined annotations via Roboflow
- Task
- Object Detection
- License
- apache-2.0
- Created
- Mar 22, 2026
- Updated
- Mar 22, 2026