COCO 2017 dataset labeled for face detection. Contribute to HapKoM/coco-faces development by creating an account on GitHub.

For each image in the 2017 COCO dataset (val and train), we created a single csv where each crowd is a detected face using yoloface. If an image has no detected faces, it's represented by …

COCO has several features: Object segmentation, Recognition in context, Superpixel stuff segmentation, 330K images (>200K labeled), 1.5 million object instances, 80 object …

COCO-WholeBody dataset is the first large-scale benchmark for whole-body pose estimation. It is an extension of COCO 2017 dataset with the same train/val split as COCO. Here is an …

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COCO-WholeBody is an extension of COCO dataset with whole-body annotations. There are 4 types of bounding boxes (person box, face box, left-hand box, and right-hand box) and 133 …

The COCO dataset is a comprehensive collection designed for object detection, segmentation, and captioning tasks. It comprises over 200,000 images, encompassing a diverse array of …

The MS COCO (Microsoft Common Objects in Context) dataset is a large-scale object detection, segmentation, key-point detection, and captioning dataset. The dataset consists of 328K …

1. 什么是 datasets 库和 load_dataset？. datasets 是 Hugging Face 提供的一个强大工具，用于加载、处理和操作大规模数据集。 它支持多种格式（如 CSV、JSON、Parquet 等）以及在线数 …