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LibreYOLO/hand-gestures-jps7z

Hand Gestures Jps7Z This dataset is part of the Roboflow 100 benchmark, a diverse collection of 100 object detection datasets spanning 7 imagery domains. Dataset Statistics Split Images Train 642 Validation 178 Test 94 Total 914 Classes (14) 0 1 10 11 12 13 2 3 4 5 6 7 8 9 Usage With LibreYOLO from libreyolo import LIBREYOLO # Load a model model = LIBREYOLO(model_path="libreyoloXnano.pt") #… See the full description on the dataset page: https://huggingface.co/datasets/LibreYOLO/hand-gestures-jps7z.

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Dataset Card

Hand Gestures Jps7Z

This dataset is part of the Roboflow 100 benchmark, a diverse collection of 100 object detection datasets spanning 7 imagery domains.

Dataset Description

—Source: Roboflow 100
—Category: Real World
—License: CC-BY-4.0
—Format: YOLO (LibreYOLO compatible)
—Mirrored on: 2026-01-20

Dataset Statistics

Split	Images
Train	642
Validation	178
Test	94
Total	914

Classes (14)

—0
—1
—10
—11
—12
—13
—2
—3
—4
—5
—6
—7
—8
—9

Usage

With LibreYOLO

python

from libreyolo import LIBREYOLO

# Load a model
model = LIBREYOLO(model_path="libreyoloXnano.pt")

# Train on this dataset
model.train(data='path/to/data.yaml', epochs=100)

Download from HuggingFace

python

from huggingface_hub import snapshot_download

# Download the dataset
snapshot_download(
    repo_id="Libre-YOLO/hand-gestures-jps7z",
    repo_type="dataset",
    local_dir="./hand-gestures-jps7z"
)

Directory Structure

hand-gestures-jps7z/
├── data.yaml           # Dataset configuration
├── README.md           # This file
├── train/
│   ├── images/         # Training images
│   └── labels/         # Training labels (YOLO format)
├── valid/
│   ├── images/         # Validation images
│   └── labels/         # Validation labels
└── test/
    ├── images/         # Test images (if available)
    └── labels/         # Test labels

Label Format

Labels are in YOLO format (one .txt file per image):

<class_id> <x_center> <y_center> <width> <height>

All coordinates are normalized to [0, 1].

Citation

If you use this dataset, please cite the Roboflow 100 benchmark:

bibtex

@misc{rf100_2022,
    Author = {Floriana Ciaglia and Francesco Saverio Zuppichini and Paul Guerrie and Mark McQuade and Jacob Solawetz},
    Title = {Roboflow 100: A Rich, Multi-Domain Object Detection Benchmark},
    Year = {2022},
    Eprint = {arXiv:2211.13523},
}

License

This dataset is released under the CC-BY-4.0 license. Please check the original source for any additional terms.

Acknowledgments

—Original dataset from Roboflow Universe
—Part of the Roboflow 100 Benchmark
—Sponsored by Intel