ml ferret

We have hosted the application ml ferret in order to run this application in our online workstations with Wine or directly.

Quick description about ml ferret:

Ferret is Apple�s end-to-end multimodal large language model designed specifically for flexible referring and grounding: it can understand references of any granularity (boxes, points, free-form regions) and then ground open-vocabulary descriptions back onto the image. The core idea is a hybrid region representation that mixes discrete coordinates with continuous visual features, so the model can fluidly handle �any-form� referring while maintaining precise spatial localization. The repo presents the vision-language pipeline, model assets, and paper resources that show how Ferret answers questions, follows instructions, and returns grounded outputs rather than just text. In practice, this enables tasks like �find that small red icon next to the chart and describe it� where both the linguistic reference and the visual region are ambiguous without fine spatial reasoning.

Features:

• Any-form referring and precise visual grounding
• Hybrid region representation combining coordinates and features
• Open-vocabulary recognition with grounded outputs
• Instruction following for multimodal QA and editing prompts
• Assets and training scripts aligned to the research paper
• Research baseline for fine-grained spatial reasoning in MLLMs

Programming Language: Python.
Categories: