Face Detection Dataset

The dataset comprises 16.7k images and 2 annotation files, each in a distinct format. The first file, labeled “Label,” contains annotations with the original scale, while the second file, named “yolo_format_labels,” contains annotations in YOLO format. The dataset was obtained by employing the OIDv4 toolkit, specifically designed for scraping data from Google Open Images. Notably, this dataset exclusively focuses on face detection.

This dataset is an excellent resource for training deep learning models focused on face detection tasks. The images in the dataset are of exceptional quality and have been carefully annotated with bounding boxes around the facial regions. These annotations are available in two formats: the original scale, showing the pixel coordinates of the bounding boxes, and the YOLO format, which represents the bounding box coordinates in normalized form.

The dataset was curated by scraping relevant images from Google Open Images using the OIDv4 toolkit. Only images relevant to detection tasks have been included, making this dataset an ideal choice for training deep learning models specifically targeting face detection.

Additionally, the high-quality images and precise annotations ensure that your models receive the best possible training data. Whether you’re developing models for academic research or commercial applications, this dataset provides a robust foundation for achieving accurate face detection results.