Arabic Sign Language Numbers Detection Dataset for YOLOv8

YOLOv8 dataset designed for real-time detection of Arabic Sign Language (ArSL) numbers. The dataset is intended for training models to recognize numerical gestures used in ArSL. No information is available on its size, creator, or date of publication.

Use Cases

• Train a YOLOv8 model to detect and classify ArSL number gestures from image frames.
• Benchmark real-time object detection performance on isolated sign language number recognition tasks.
• Develop applications for translating Arabic Sign Language numbers into text or speech output.

Strengths

• Dataset is specifically formatted for the YOLOv8 architecture, facilitating immediate use for training.
• Focuses on a defined task of real-time number detection within Arabic Sign Language.

Limitations

• Unknown dataset size, row count, and image resolution prevents assessment of model training potential.
• Lack of sample data or column descriptions prevents verification of label quality and class balance.
• No information on the diversity of signers, lighting conditions, or backgrounds limits understanding of generalization capability.