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Single-class product detector trained on the Retail Product Dataset. All original classes were collapsed into one class: product.
Model source
Source description
Single-class product detector trained on the Retail Product Dataset.
All original classes were collapsed into one class: product.
Sources
1 sourceVerified Sep 9
Model artifacts
2 artifactsSource excerpts
2 excerpts| Metric | Value |
|---|
| mAP50 | 0.8070 |
| mAP50-95 | 0.5114 |
| Precision | 0.8334 |
| Recall | 0.8107 |
from ultralytics import YOLO
from huggingface_hub import hf_hub_download
weights = hf_hub_download(repo_id="prince4332/yolov26-product-detection-v2", filename="best.pt")
model = YOLO(weights)
results = model.predict("your_image.jpg", conf=0.25)
--- license: apache-2.0 tags: - object-detection - yolo - yolo26 - retail - ultralytics datasets: - hafizyusufheraldi/retail-product-dataset --- # YOLO26 Medium — Retail Product Detector Single-class product detector trained on the [Retail Product Dataset](https://www.kaggle.com/datasets/hafizyusufheraldi/retail-product-dataset). All original classes were collapsed into one class: **`product`**. ## Metrics (val set) | Metric | Value | |--------|-------| | mAP50 | 0.8070 | | mAP50-95 | 0.5114 | | Precision | 0.8334 | | Recall | 0.8107 | ## Usage ```python from ultralytics import YOLO from huggingface_hub import hf_hub_download weights = hf_hub_download(repo_id="prince4332/yolov26-product-detection-v2", filename="best.pt") model = YOLO(weights) results = model.predict("your_image.jpg", conf=0.25) ``` ## Training Config - **Base model**: yolo26m (COCO pretrained) - **Epochs**: 80 (early stopping patience=20) - **Image size**: 640 - **Optimizer**: auto (MuSGD) - **AMP**: True (FP16) - **Augmentation**: mosaic, mixup, HSV, perspective, flips
Source context: 35 downloads · 0 likes · Pipeline object-detection · Library ultralytics · Repo prince4332/yolov26-product-detection-v2