Labeled Mask Dataset (YOLO_darknet)

This dataset includes 1,510 images, divided into two distinct classes. Each image comes with YOLO format bounding boxes, providing exact object locations. These text file annotations ensure seamless integration into machine learning models.

The dataset’s clear labeling and precise bounding boxes are crucial for training and validating object detection algorithms. Consequently, it is highly valuable for developers and researchers working on computer vision projects. Moreover, the clear class separation and accurate bounding boxes enhance its utility, aiding the development of robust AI models capable of detecting and recognizing objects in various settings.

By offering high-quality annotations, this dataset becomes an invaluable asset for researchers and developers dedicated to advancing the field of object detection. The meticulous attention to detail in the annotations ensures that the dataset meets the highest standards, providing a solid foundation for training and testing machine learning models. This level of precision is crucial for enhancing the accuracy of object detection algorithms, which in turn leads to more reliable and efficient AI-driven applications.

The classes are:

With mask;
Without mask;