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")

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

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