RegionGPT is a novel framework designed to enhance the region-level understanding and captioning capabilities of vision language models (VLMs). It addresses the limitations of existing VLMs in handling detailed regional visual understanding by improving spatial awareness through modifications to visual encoders and integrating task-guided instruction prompts. The framework supports any-shape regions of interest and enhances performance on tasks requiring specific output scopes. Additionally, it introduces an automated pipeline for generating detailed region-level captions, enriching the training dataset. RegionGPT demonstrates significant improvements in various region-level tasks, including complex region descriptions, reasoning, object classification, and referring expression comprehension. The model's effectiveness is validated through experiments on datasets like COCO and ReferCOCO, showing superior performance in object classification, captioning, and expression comprehension.RegionGPT is a novel framework designed to enhance the region-level understanding and captioning capabilities of vision language models (VLMs). It addresses the limitations of existing VLMs in handling detailed regional visual understanding by improving spatial awareness through modifications to visual encoders and integrating task-guided instruction prompts. The framework supports any-shape regions of interest and enhances performance on tasks requiring specific output scopes. Additionally, it introduces an automated pipeline for generating detailed region-level captions, enriching the training dataset. RegionGPT demonstrates significant improvements in various region-level tasks, including complex region descriptions, reasoning, object classification, and referring expression comprehension. The model's effectiveness is validated through experiments on datasets like COCO and ReferCOCO, showing superior performance in object classification, captioning, and expression comprehension.