Create Breathtaking Mini Worlds with Capsule Micro LoRA and Stable Diffusion
1. Workflow Overview
This workflow generates miniature cityscapes (e.g., Qingdao skyline inside a pill capsule) by combining Stable Diffusion with a "Capsule Micro World" LoRA. It includes text encoding, latent space generation, and 2x upscaling for HD output.
2. Core Models
Stable Diffusion (UNETLoader): Base model (
基础算法_F.1), FP8 precision.Capsule Micro World LoRA: Enhances miniature details (weight=0.8).
T5-XXL & CLIP-L: Dual text encoders for prompt understanding.
2xNomosUni Upscaler: Post-processing 2x super-resolution.
3. Key Nodes
Node Name | Function | Installation | Dependencies |
|---|---|---|---|
DualCLIPLoader | Loads T5+CLIP text encoders | Built-in | Requires |
Lora Loader Stack | Dynamic LoRA loading | Install | Needs LoRA files |
SamplerCustomAdvanced | Advanced noise-controlled sampler | Built-in | None |
ImageUpscaleWithModel | 2x image upscaling | Built-in | Requires |
4. Workflow Structure
Group 1: Text Input
CLIPTextEncode: Processes prompts (e.g., "Shanghai micro-city in a capsule").
Group 2: Image Generation
EmptyLatentImage: Sets resolution (768x1024).
SamplerCustomAdvanced: Generates latent image with LoRA.
Group 3: Post-Processing
VAEDecode: Decodes latent to image.
ImageUpscaleWithModel: 2x upscaling.
5. Inputs & Outputs
Input Parameters:
Required: Prompts, resolution (768x1024).
Optional: Seed (random by default), LoRA weight (default=0.8).
Output: Upscaled PNG (saved to
wangyi AI Studiofolder).
6. Notes
Plugin: Install
rgthree-comfyvia ComfyUI Manager for LoRA stacking.Model Paths: Place LoRA (
胶囊微缩世界) and upscaler (2xNomosUni) in correct folders.Performance: ≥8GB VRAM recommended; use
fp8_e4m3fnfor lower resource usage.Debug: Check CLIP model if prompts fail to encode.