127,000 images form a modified subsample of the HAnd Gesture Recognition Image Dataset (HaGRID). The dataset is intended for classification tasks related to hand gestures. It is hosted on Kaggle and is associated with computer vision and human-computer interaction applications.
Use Cases
- Train image classification models based on hand gesture images.
- Benchmark gesture recognition algorithms based on a labeled image collection.
- Develop human-computer interaction systems based on visual gesture input.
Strengths
- The dataset contains 127,000 images, providing a substantial sample for model training.
- It is derived from the established HaGRID dataset, suggesting a focus on hand gesture recognition.
Limitations
- Row count is unknown, which may limit suitability assessment.
- Column-level documentation is absent; field semantics must be inferred after download.
- Description metadata is limited; actual data quality requires manual inspection after download.
Provenance
- Source
- Kaggle
- Collection Method
- Modified subsample of the HAnd Gesture Recognition Image Dataset (HaGRID).