Flux-Kontext - Wan 2.2 Character Lora Training Image Generation

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Model description

🧩 Flux-Kontext Character Expansion Workflow

Overview

This custom Flux-Kontext workflow is a major extension of the base model, built to handle multi-image composition, LoRA stacking, and multi-step generation for high-quality, consistent character datasets.
It’s designed for character creation, LoRA training, and regeneration of low-quality inputs β€” giving you complete control over appearance, context, and detail.


πŸ–ΌοΈ Dual-Image Context System

The workflow allows you to combine two different input images into a single coherent generation:

  • If both inputs are active, the system blends their visual and semantic context β€” e.g., β€œthe man and the woman are dancing.”

  • If only one image is active, the model evolves that image using the new prompt β€” e.g., β€œsame face and clothes, the man is riding a horse.”

This setup enables dynamic, instruction-based image merging without losing character identity.


🧠 LoRA Power Loader

A custom LoRA Power Loader lets you stack multiple LoRAs simultaneously, each with independent strength control.
You can fine-tune how each LoRA influences the output β€” controlling aspects like:

  • Facial identity

  • Body type and proportions

  • Clothing style

  • Lighting or artistic detail

This provides granular creative direction for dataset generation or character refinement.


πŸ” Latent Upscale & Restoration

A built-in Latent Upscale node enhances weak or low-resolution inputs before re-generation.
It restores missing structure and detail at the latent level, producing clean, high-resolution results without introducing blur or artifact noise.

Use this feature to:

  • Improve dataset quality

  • Restore bad or compressed source images

  • Regenerate old renders into consistent HD-quality material


🧩 Multi-Prompt / Multi-Step Generation

The workflow supports multiple prompts and generation passes, automatically rendering your character in:

  • Different poses

  • Varied lighting and environments

  • Multiple angles and camera distances

This produces a rich, consistent dataset ideal for training LoRAs or any character model requiring 360Β° diversity and visual coherence.


🎯 Use Cases

  • Creating training data for LoRA or DreamBooth

  • Generating pose/lighting variation sets for the same character

  • Cleaning and enhancing low-quality reference material

  • Building consistent visual identity across scenes


βš™οΈ Requirements

  • Flux-Kontext nodes (ComfyUI Flux / Florence integration)

  • LoRA Power Loader node

  • Latent Upscale node

  • Any Flux-compatible base model

  • Optional: additional LoRAs placed in /models/Lora/

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