Dataset of 476 Laboratory Bottle Images for Color and Size Detection Using YOLO

This dataset contains 476 images of laboratory bottles acquired under different illumination, orientation, and positioning conditions. The dataset was developed for training, validation, and evaluation of computer vision and deep learning models for automatic object detection and classification. The bottles are categorized according to two main characteristics: color and size. The dataset includes three color classes (purple, green, and pink) and three size categories (small, medium, and large). The images were collected and organized to support the development of neural network models capable of simultaneously identifying the color and size of laboratory bottles. This dataset is intended for applications in computer vision, machine learning, deep learning, robotics, and industrial automation. It can be used for training YOLO-based models and other object detection and classification algorithms.