Blueberry Fruit Segmentation Dataset contains annotated images for blueberry fruit segmentation, provided in COCO format. The dataset is intended to advance research in automated fruit harvestability and yield assessment, focusing on blueberry count, maturity, and cluster compactness. It was authored by c-tan and last updated on 2025-09-19.
Use Cases
- Training segmentation models for automated blueberry counting based on annotated images.
- Assessing fruit maturity stages for harvest timing based on visual traits mentioned in the description.
- Evaluating cluster compactness for yield estimation and harvest planning based on image annotations.
Strengths
- Images are annotated in the standardized COCO format, which suggests interoperability with many computer vision tools.
- The dataset has a specific research focus on blueberry traits like count, maturity, and cluster compactness.
Limitations
- Description metadata is limited; actual data quality requires manual inspection after download.
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
Provenance
- Source
- c-tan on Hugging Face
- Collection Method
- Likely contains annotated images constructed for research purposes, as referenced in an associated paper.
- Freshness
- Last updated 2025-09-19 19:16:55; freshness should be verified.