Upscaling with Ultimate SD Upscale/Tile Controlnet SD Upscale &amp; Anima Models 基于 Ultimate SD Upscale 或 Tile Controlnet 与 Anima 模型的放大工作流 Thanks <a target="_blank" rel="ugc" href="https://civarchive.com/models/2708551/anima-tile-and-repair-controlnet-lllite">@L_A_X</a> for the tile Controlnet whith new node made by <a target="_blank" rel="ugc" href="https://github.com/Lebensignal/ComfyUI-UltimateSDUpscale-FLS-LLLite">Lebensignal</a> u can use cntile with padding and seam fix features of USDU now. Parameters: - Prompt: Use the original image's prompt(when doing 1.5-3x upscale with low cn strength), or just quility and style prompt(when doing 3x+ upscale with high cn strength). - Denoising Strength: Recommended range is 0.25 – 0.75. - Steps: Adjust according to denoising strength, typically 8 – 20 steps. - Sampler: er_sde is recommended. - Controlnet strength: 0.4–1.0; Controlnet end at 0.8 - 1.0 - Plz download CN model from here: <a target="_blank" rel="ugc" href="https://civarchive.com/models/2708551">https://civarchive.com/models/2708551</a> 参数: - 提示词：使用原图的提示词(1.5-3倍放大且使用低cn强度)或者只保留质量提示词和画风提示词(3倍以上放大且使用高cn强度)。 - 重绘幅度（Denoising Strength）：建议范围 0.25～0.75。 - 步数（Steps）：根据重绘幅度调整，通常为 8～20 步。 - 采样器（Sampler）：推荐使用 er_sde。 - ControlNet 强度（CN strength）：范围 0.4～1.0，结束位置在0.8-1.0. - CN tile模型在这里下载: <a target="_blank" rel="ugc" href="https://civarchive.com/models/2708551">https://civarchive.com/models/2708551</a> Update Log - 26/04/12: Version 1.1 updated to preview3. - 26/04/18: Version 1.1 added a Lora loader and adjusted parameters; - 26/05/14: Version 1.2 introduced the following QoL (Quality of Life) nodes: - Auto tile sizing - Comparison preview - Save with metadata - 26/06/21: Version 1.2a adjusted baseline parameters for improved default performance. - 26/06/21: add first controlnet tile upscale experimental workflow - 26/06/24: moved to Lebensignal's USDU node that support controlnet lllite

Anima USDU/CNTile Upscale workflow (Anima 放大工作流)

animaUSDUCntileUpscale_cntilev01e.zip

CNTilev0.1e

Files with SHA256: ac59660491f0fd0918ad8541cd4a4c44f7cb38c894dfb0ac3f8c6a7d6faf09ad