This is the Windows app named MGIE whose latest release can be downloaded as ml-mgiesourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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SCREENSHOTS
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MGIE
DESCRIPTION
MGIE—Guiding Instruction-based Image Editing—demonstrates how a multimodal LLM can parse natural-language editing instructions and then drive image transformations accordingly. The project focuses on making edits explainable and controllable: the model interprets text guidance, reasons over image content, and outputs edits aligned with user intent. It’s positioned as an ICLR 2024 Spotlight work, with code and references that show how to connect language planning to concrete image operations. This bridges a gap between free-form prompts and precise edits by letting users describe “what” and “where” in everyday language. The repo includes instructions, examples, and links that situate MGIE within Apple’s broader line of multimodal research. For practitioners, MGIE provides a blueprint for text-to-edit systems that are more semantically grounded than naive prompt-only pipelines.
Features
- Natural-language instruction parsing for image editing
- Multimodal reasoning that ties text plans to visual changes
- Examples and demos aligned with the research paper
- Fine-grained, region-aware editing behavior
- Open code for reproducibility and adaptation
- Basis for controllable, explainable image-editing agents
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/mgie.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
