We introduce the Geospatial Reasoning Segmentation Dataset (GRES), a collection of vision and language data designed around remote-sensing applications. GRES consists of two core components: PreGRES, a dataset consisting of over 1M remote-sensing specific visual instruction-tuning Q/A pairs for pre-training geospatial models, and GRES, a semi-synthetic dataset specialized for reasoning segmentation of remote-sensing data and consisting of 9,205 images and 27,615 natural… See the full description on the dataset page:
https://huggingface.co/datasets/jquenum/GRES.
