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Snapstock Fruit Vegetable Detector

This repository stores a YOLOv8m fruit and vegetable object-detection checkpoint used as a baseline model for the SnapStock-AI university project.

Fontehuggingface.co/Senu-12/snapstock-fruit-vegetable-detector/tree/398e0981f777f683aead90144b7d53cd22a4fbf4
TipoOtherVersãoRevision 398e098Bnota

Fonte do modelo

Tipo
Other
Tamanho do arquivo
49,7 MB
Versão
vRevision 398e098
Atualizado
21 de out. de 2026
Downloads
155
Fonte
Hugging Face

Descrição da fonte

SnapStock-AI Fruit and Vegetable Detector

This repository stores a YOLOv8m fruit and vegetable object-detection checkpoint used as a baseline model for the SnapStock-AI university project.

Original source

The checkpoint was obtained from the baseline models published with:

  • Original author: Henning Heyen
  • Original project: Fruits-And-Vegetables-Detection-Dataset
  • Dataset: LVIS Fruits and Vegetables
  • Classes: 63
  • Architecture: YOLOv8m

This repository does not claim authorship of the original dataset or baseline model. The checkpoint is mirrored here to provide stable model downloading for the SnapStock-AI development team.

Intended use

The model is used to:

  • Detect fruits and vegetables
  • Return bounding boxes
  • Identify object classes
  • Count detected items

Limitations

The original project reports class imbalance and duplicate Tomato/tomato and Strawberry/strawberry categories. Performance should be tested using real SnapStock-AI inventory images before production use.

Local loading

from ultralytics import YOLO

model = YOLO("fruit_vegetable_yolov8m.pt")
results = model.predict("inventory-image.jpg")

Fontes

1 fonte
Hugging FacePrimárioVersão 398e0981f777f683aead90144b7d53cd22a4fbf4
huggingface.co/Senu-12/snapstock-fruit-vegetable-detector/tree/398e0981f777f683aead90144b7d53cd22a4fbf4

Verificado 21 de out.

Artefatos de modelo

1 artefato

yolov8/fruit_vegetable_yolov8m.pt

pt · 49,7 MB · SHA-256 a18624d446e2…e5d3 · Hugging Face

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Trechos de fonte

3 trechos
Readme5 de ago.huggingface.co/Senu-12/snapstock-fruit-vegetable-detector

--- library_name: ultralytics pipeline_tag: object-detection tags: - yolov8 - object-detection - fruits - vegetables - snapstock-ai license: other --- # SnapStock-AI Fruit and Vegetable Detector This repository stores a YOLOv8m fruit and vegetable object-detection checkpoint used as a baseline model for the SnapStock-AI university project. ## Original source The checkpoint was obtained from the baseline models published with: - Original author: Henning Heyen - Original project: Fruits-And-Vegetables-Detection-Dataset - Dataset: LVIS Fruits and Vegetables - Classes: 63 - Architecture: YOLOv8m This repository does not claim authorship of the original dataset or baseline model. The checkpoint is mirrored here to provide stable model downloading for the SnapStock-AI development team. ## Intended use The model is used to: - Detect fruits and vegetables - Return bounding boxes - Identify object classes - Count detected items ## Limitations The original project reports class imbalance and duplicate Tomato/tomato and Strawberry/strawberry categories. Performance should be tested using real SnapStock-AI inventory images before production use. ## Local loading ```python from ultralytics import YOLO model = YOLO("fruit_vegetable_yolov8m.pt") results = model.predict("inventory-image.jpg")

Note21 de out.huggingface.co/Senu-12/snapstock-fruit-vegetable-detector

Source context: 155 downloads · 0 likes · Pipeline object-detection · Library ultralytics · Repo Senu-12/snapstock-fruit-vegetable-detector

Note5 de ago.huggingface.co/Senu-12/snapstock-fruit-vegetable-detector

Source context: 69 downloads · 0 likes · Pipeline object-detection · Library ultralytics · Repo Senu-12/snapstock-fruit-vegetable-detector