YOLO Scope-X Object Detection Dataset with Multi-Tool Annotations

Underlying dataRepository name: Zenodo: YOLO Scope-X Dataset—Multi-Tool Object Detection Annotations.https://doi.org/10.5281/zenodo.18052474 The project contains the following underlying data: MakeSense.ai annotation tool MakeSense_aiTool/train/(Training images and corresponding YOLO-format bounding box annotations generated using the MakeSense.ai annotation tool.) MakeSense_aiTool/val/(Validation images and YOLO-format annotations produced with MakeSense.ai.) MakeSense_aiTool/test/(Testing images and YOLO-format annotations produced with MakeSense.ai.) MakeSense_aiTool/data.yml(YOLO-compatible dataset configuration file defining class indices and dataset paths.) MakeSense_aiTool/labels_2025-07-27-12-13-19.csv(Raw annotation export file generated by MakeSense.ai.) MakeSense_aiTool/labels_2025-07-27-01-47-35/(Individual YOLO-format label files corresponding to each annotated image, e.g.,481069944_607307268764594_8607083815216875903_n.txt,512692295_721114720708881_5286103856534793536_n.txt.).... Roboflow annotation tool RobFlowTool/train/(Training images and YOLO-format annotations generated using the Roboflow Annotate platform.) RobFlowTool/val/(Validation images and YOLO-format annotations generated using Roboflow.) RobFlowTool/test/(Testing images and YOLO-format annotations generated using Roboflow.) VGG Image Annotator (VIA) tool VGG(VIA)Tool/images/(Original images used for annotation with the VGG Image Annotator.) VGG(VIA)Tool/labels/(Annotation files generated using the VIA annotation tool.) VGG(VIA)Tool/ConvertedToVGG-to-YOLOFormat/(Converted YOLO-format annotation files derived from the original VIA annotations to ensure compatibility with YOLOv12.) VGG(VIA)Tool/data.yml(YOLO-compatible dataset configuration file for the VIA-derived annotations.) VGG(VIA)Tool/via_project_26Jul2025_19h12m_csv(Original VIA project annotation file exported in CSV format.) Image source and reuse The original images were collected from publicly accessible internet sources and reorganized solely for academic research and benchmarking purposes. No personal or sensitive data are included. Reproducibility The repository provides complete annotation outputs from three independent annotation tools, along with configuration files, enabling full reproducibility of the experiments and direct retraining of YOLOv12 models under identical data conditions. Reference (add to Reference list) Use this entry and format it according to your manuscript’s reference style: Al-Hitawi MAS, Abu-Alsaad HA, Al-Shibly MA, Tharthar MA, Al-Jumaili AHA.YOLO Scope-X Dataset: Multi-Tool Object Detection Annotations.Zenodo; 2025. https://doi.org/10.5281/zenodo.18052474