750 images of U.S. coins annotated for object detection tasks. The dataset is designed for use with YOLO pipelines. It was sourced from Kaggle, but the author, organization, and last update date are unknown.
Use Cases
- Train object detection models based on the annotated coin images.
- Benchmark YOLO pipeline performance on a specific, constrained visual domain.
- Develop coin recognition or classification systems based on the visual data.
- Test model robustness on metallic, reflective objects based on the coin imagery.
Strengths
- 750 images provide a defined starting point for model training.
- Annotations are specifically prepared for object detection workflows.
Limitations
- Row count and dataset size are 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
- Images were annotated for object detection, but the specific collection method is unknown.
- Time Range
- null
- Freshness
- Last update date is unknown; freshness unverified.
- Geography
- United States (based on coin type)