CIVITAI / Workflows

FireRed-Image-Edit-1.0 Single-Image Creative Divergent Editing Workflow

This workflow is designed for FireRed-Image-Edit-1.0 single-image editing with a more divergent and creative transformation style. Compared with the anti-drift version, this workflow is more suitable when you want to keep the core subject recognizable while allowing the scene, clothing, environment, atmosphere, and visual concept to change more aggressively. It is useful for turning one source image into a new cinematic concept, fantasy scene, sci-fi poster, commercial visual, character redesign, or creative image-editing result. The workflow uses FireRed-Image-Edit-1.0_fp8_e4m3fn.safetensors as the main image editing model, with qwen_2.5_vl_7b_fp8_scaled.safetensors as the Qwen image text encoder and qwen_image_vae.safetensors as the VAE. It also applies the Qwen-Image-Lightning 8-step LoRA route, making the generation process faster and more practical for repeated testing. The sampling configuration uses an 8-step, low-CFG editing route, which is useful for fast iteration when testing larger creative changes. The core of the workflow is built around TextEncodeQwenImageEditPlus, multi-reference image input, FluxKontextMultiReferenceLatentMethod, ReferenceLatent-style conditioning, CFGNorm, ModelSamplingAuraFlow, VAEEncode, KSampler, and VAEDecodeTiled. These nodes work together to let the model understand the input image, read the editing instruction, preserve key image information where needed, and still allow strong visual transformation. The included prompt example shows the intended use clearly. It asks the workflow to transform a half-body portrait into an astronaut performing an EVA spacewalk outside a spacecraft. The instruction keeps the person’s identity, facial structure, gaze, expression, head direction, and pose stable, while changing the clothing into a realistic white EVA spacesuit, adding a transparent helmet visor, replacing the background with outer space, Earth’s curve, spacecraft surfaces, and solar panels, and rebuilding the lighting with strong sunlight plus blue Earth-reflected fill light. This makes the workflow suitable for “controlled divergence”: it is not a simple color edit, and it is not a full random regeneration. It sits between both. The user can ask for major creative changes while still writing preservation rules for identity, posture, texture, lighting consistency, and edge blending. This is especially useful for AI po