An open-pit mine segmentation dataset for deep learning

The open-pit mine segmentation dataset for deep learning is a carefully curated resource. It was developed through a systematic process. Firstly, by conducting comprehensive literature research, the Point of Interest (POI) data of open-pit mines was summarized. Based on this, Google Level 17 images were obtained. Then, through painstaking manual annotation work, the boundaries of the mines were precisely marked out. The dataset provides the boundary information in YOLO format, which is highly conducive to the training and optimization of deep learning models for tasks related to open-pit mine segmentation. It enables researchers and practitioners in the field of deep learning to have a reliable and accurate dataset at their disposal, facilitating the development of more effective algorithms and applications for understanding and analyzing the characteristics and patterns of open-pit mines, which can have significant implications for mine management, safety monitoring, and resource optimization in the open-pit mining industry.