FireRedTeam/FireRed-Image-Edit
FireRed-Image-Edit is a powerful image editing foundation model achieving open-source state-of-the-art performance with precise instruction following, high-fidelity generation, superior identity consistency, and seamless multi-element fusion.
What it solves
FireRed-Image-Edit is a general-purpose image editing model designed to provide high-fidelity, consistent edits across various scenarios. It addresses common challenges in AI image editing, such as maintaining character identity across complex changes, fusing multiple visual elements from different images into one scene, and accurately following detailed natural language instructions.
How it works
The project uses a backbone-agnostic architecture where editing capabilities are injected via a Pretrain $\rightarrow$ SFT $\rightarrow$ RL pipeline. It supports 1-3 input images natively. For more complex tasks involving more than 3 images, it employs an intelligent Agent module that uses ROI (Region of Interest) detection to crop and stitch images into composite images, and an LLM-based recaptioning system to rewrite instructions for better context.
Who it’s for
This tool is designed for creators, designers, and developers who need professional-grade image manipulation, such as portrait retouching, old photo restoration, and complex scene composition, without requiring extensive prompt engineering.
Highlights
- Identity Consistency: State-of-the-art open-source performance in preserving subject identity during edits.
- Multi-Element Fusion: Ability to combine 10+ elements using an automated agent-powered cropping and stitching workflow.
- Engineering Optimizations: Includes distillation, quantization, and static compilation to achieve 4.5s generation times with 30GB VRAM.
- Extensible Ecosystem: Provides full LoRA training code and native ComfyUI node support.
- Curation of Specialized Effects: Dedicated capabilities for professional portrait makeup and high-fidelity stylized text reference.