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Yolov26 Product Detection v2

Single-class product detector trained on the Retail Product Dataset. All original classes were collapsed into one class: product.

KindOtherVersionRevision 4d78357

Model source

Kind
Other
File size
42.0 MB
Version
vRevision 4d78357
Updated
Sep 19, 2026
Downloads
35
Source
Hugging Face

Source description

YOLO26 Medium — Retail Product Detector

Single-class product detector trained on the Retail Product Dataset.
All original classes were collapsed into one class: product.

Metrics (val set)

MetricValue
mAP500.8070
mAP50-950.5114
Precision0.8334
Recall0.8107

Usage

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

Sources

1 source
Hugging FacePrimaryVersion 4d78357a470de2ea17e9f905ce10bd2e7f7568bd
huggingface.co/prince4332/yolov26-product-detection-v2/tree/4d78357a470de2ea17e9f905ce10bd2e7f7568bd

Verified Sep 9

Model artifacts

2 artifacts

best.pt

pt · 42.0 MB · SHA-256 3b25f886d874…41e9 · Hugging Face

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last.pt

pt · 42.0 MB · SHA-256 f8a7e1bf06ab…8cf5 · Hugging Face

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Source excerpts

2 excerpts

--- 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