Qwen Image 2.1 Fix 1.0 / 2.0 image quality enhancement workflow. Removes the GPT-generated look and high-frequency fake details while keeping the original composition, delivering cleaner, more realistic, more textured results.

Main features:
- Built on Qwen Image 2.1 base (Qwen-Image_2.1 + qwen3vl_8b CLIP + qwen_image_2.1 VAE) with the detail-fix LoRA (qwen2.1-detail-fix-opinionated v1.0)
- Switch-controlled dual output: toggle between Fix 1.0 and Fix 2.0 strength in the same graph
- Each pass: 20 steps, CFG 3.5, euler/simple, randomized seed
- rgthree Image Comparer panels put the original next to Fix 1.0 and Fix 2.0 for direct judging on the same subject (roses, sculptures, water scenes, portraits in the tutorial)
- Prompt construction helpers (TextGenerate / RegexExtract / StringConcatenate) keep the cleaned image on-prompt

Suggested workflow:
1. Load the image to be cleaned up and set the prompt
2. Run the graph; original, Fix 1.0 and Fix 2.0 render for side-by-side comparison
3. Toggle the switch to pick the fix level per image type (portraits vs landscapes vs objects) and save

Dependencies:
- Qwen-Image_2.1.safetensors (base UNET)
- qwen3vl_8b_int8_convrot.safetensors (CLIP)
- qwen_image_2.1_vae_bf16.safetensors (VAE)
- qwen2.1-detail-fix-opinionated-v1.0.safetensors (detail-fix LoRA)
- rgthree Node Suite (Image Comparer), ComfySwitchNode

RunningHub workflow page: https://www.runninghub.ai/zh-cn/post/2109547621848211457?inviteCode=rh-v1111
Bilibili tutorial video: https://www.bilibili.com/video/BV14zp96REo9/
RunningHub registration with invite code rh-v1111 (1000 RH coins): https://www.runninghub.ai/?inviteCode=rh-v1111