Florence-2-Large: A Unified Vision Model for Captioning, Detection and Segmentation

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Lucataco's Florence-2-Large is a vision foundation model that handles captioning, object detection, grounding and segmentation through text prompts within one architecture. It is the larger version of Florence-2 and was trained on the FLD-5B dataset, which contains 5.4 billion annotations across 126 million images. The model turns visual and text inputs into text-formatted outputs using a sequence-to-sequence design, so it can perform several vision tasks without task-specific fine-tuning. The article suggests use cases such as product catalog annotation, document understanding and zero-shot object localization. Its text-based output, however, requires post-processing to convert coordinates into machine-readable formats.

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