Dataset from Zenodo · Yunus, Fajrian
COCO 2017 object detections with YOLOv5 confidence scores: a probabilistic image-retrieval database
- License
- CC BY 4.0commercial use allowedLicense text
- This license allows commercial use. Usually you must credit the author; read the license for the exact terms.
- Formats
- SQL, ZIP, MD
- Size
- 68 MB
- Updated
- Sep 29, 2026
Description
A probabilistic image-retrieval database: the objects detected by a YOLOv5 model on the images of the COCO 2017 dataset (training and validation sets), together with the detector's confidence scores, plus the COCO ground-truth annotations of the same images. It is meant as a benchmark for probabilistic databases and provenance management, and ships with scripts loading it into PostgreSQL and into ProvSQL . The data was built for the EDBT 2025 demonstration “Using a Probabilistic Database in an Image Retrieval Application” and is the dataset used in the experiments of “Provenance of HAVING Queries in Semirings with Monus”. The tables are identical to those distributed in the demonstration's source repository ; this record adds documentation, a stable identifier and loading scripts. See README.md for the schema, the per-split counts, how the stained images were produced, and loading instructions.
Description from Zenodo, shortened.
Files (5)
- SQLload.sql1.8 kB
- —SHA256SUMS323 byte
- ZIPcoco_yolov5_annotations.zip68 MB
- SQLprovsql.sql1.1 kB
- MDREADME.md6.8 kB
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