COCO8: A Small Object Detection Dataset for Model Testing

8 images from the COCO train 2017 set, split into 4 for training and 4 for validation. Ultralytics created this dataset, which was last updated on the platform in November 2024. It is designed for testing and debugging object detection models.

Use Cases

• Debugging object detection training pipelines based on the small, manageable image count.
• Testing new detection approaches on a limited but diverse set of images.
• Performing a sanity check before training larger models on the full COCO dataset.

Strengths

• Contains 8 images, making it small and easily manageable for quick tests.
• Split into 4 training and 4 validation images, providing a basic structure for evaluation.
• Derived from the first images of the established COCO train 2017 set, suggesting a known provenance.

Limitations

• Row count is unknown, which may limit suitability assessment for specific tasks.
• 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

Ultralytics, derived from the COCO train 2017 dataset.

Collection Method

Composed of the first 8 images from the COCO train 2017 set.

Freshness

Last updated 2024-11-14 09:30:49; freshness should be verified.