YOLOv11-coco-segt: Annotated Images for Object Detection and Segmentation
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Description
A dataset likely containing annotated images for computer vision tasks. It is published on Kaggle, but the author, organization, and last update date are unknown. The dataset's name suggests it is related to the YOLOv11 model and the COCO (Common Objects in Context) benchmark, potentially for segmentation tasks.
Use Cases
Fine-tune a YOLO-based model for object detection (inferred from domain, verify after download)
Benchmark segmentation model performance on COCO-style annotations (inferred from domain, verify after download)
Train a model for instance segmentation tasks (inferred from domain, verify after download)
Strengths
Published on Kaggle, a major platform for data science resources.
Limitations
Metadata is minimal; actual content requires verification after download.
Column-level documentation is absent; field semantics must be inferred after download.
Row count, file formats, and license are unknown, which may limit suitability assessment.
Provenance
Source
Kaggle
Collection Method
Likely derived from or related to the COCO dataset.
Time Range
null
Freshness
Last update date is unknown; freshness unverified.
Geography
null
License is unknown; verify terms before commercial use.