Animals Dataset for 6-Class Object Detection (YOLO annotation)

This dataset contains images used in the monograph titled Computer Vision in Python. Practical Applications of Deep Learning (Computer vision w Pythonie. Praktyczne zastosowania uczenia głębokiego) to build the yolov9t model. The full collection consists of 700 image files showing 6 classes of objects: kot (cat), krowa (cow), pies (dog), koń (horse), człowiek (person), owca (sheep). All images were scaled so that the smaller side is no shorter than 600 pixels and the larger side is no longer than 1000 pixels. The dataset was randomly divided into a training set (60% of the full dataset) and validation and test sets (20% each). As a result, the training part contains 420 files, validation and test parts - 140. The images are labeled with bounding boxes in the YOLO format, according to which the description of each file is contained in an TXT file with the same name. The dataset can be used to build another models for object detection.