foreverCuSO4/Dart_LENs_mixed

Anti-Dart Detection Traditional Data

This dataset repository contains local anti-dart light detection data for YOLO-style object detection.

Contents

• —raw/: source videos and the original archived dataset.
• —extracted/anti-dart-new-lens-0616-ft-v2/: YOLO dataset generated from the 2026-06-16 new-lens data.
• —extracted/anti-dart-new-lens-0626-ft-v1/: YOLO dataset generated from the 2026-06-26 new-lens data.

Each extracted dataset contains:

• —data.yaml: YOLO dataset configuration.
• —manifest.csv: source/output mapping and per-image object metadata.
• —images/{train,val,test}/: image files.
• —labels/{train,val,test}/: YOLO label files.

Labels

The object classes are:

Splits

Usage

Use either extracted dataset by pointing a YOLO training command at its data.yaml file:

yolo detect train data=extracted/anti-dart-new-lens-0626-ft-v1/data.yaml model=yolov8n.pt

The dataset configs use relative paths, so they should work after cloning the repository.

Uploading To Hugging Face

This directory is prepared as a Hugging Face dataset repository. After logging in and creating a dataset repository on the Hub, upload it from this directory:

hf auth login
hf upload <namespace>/<dataset-name> . . --repo-type dataset

For git-based uploads, install Git LFS first so the large media files are stored correctly.