two legs open

海艺的XL出图点模糊，出图后用sd图生图可以清晰一点。各种风格转换。不同模型作用不同。自己更换发挥。可以在sd1.5换上自己喜欢的人物lora。两个条件控制足够了，可以更换。封面是二次元旗袍转真人。

This is a merger of the following two workflows I'm using to combine the two workflows. One way I figured out how to get rid of the VRAM fullness was to add WanVideoBlockSwap. Since I don't use the GGUF model myself, I'm used to using the official version. So if you guys have your own favorite version, you can replace the nodes by yourselves. Below is the URL of two workflows that I referenced that gave me great ideas. Simple Video Interpolate and Upscale - v1.0 | Wan Video Workflows | Civitai Wan i2v with 720p smoothing - v1.1 | Wan Video Workflows | Civitai They gave me a lot of ideas, and then I improved them and merged them, so you can use them. If you come across a node that doesn't work, download it. That's the basics. English is not my native language, so I'm using DEEPL to translate it. -------------------------------------------------------------------------------- 這是我參考 以下兩個工作流 所合併起來的用法 我有想辦法解決VRAM滿的方式 就是添加了 WanVideoBlockSwap 因為我本身沒有使用GGUF模型 我個人習慣用官方版本 所以你們有自己喜歡用的版本 就自己替換節點 下面是我參考兩個工作流的網址 他們工作流給了我很大的想法 Simple Video Interpolate and Upscale - v1.0 | Wan Video Workflows | Civitai Wan i2v with 720p smoothing - v1.1 | Wan Video Workflows | Civitai 然後改善並且合併 你們可以使用看看 遇到無法使用的節點就去下載 這是基本 英文不是我的母語 所以我是用DEEPL翻譯的

Flux Kontext Fast + Upscale Workflow Status: Work in Progress - Still refining output quality This workflow combines the power of FLUX.1 Kontext with the Alimama Turbo LoRA to achieve fast, high-quality image generation and upscaling in just 8 steps. Key Features Fast Generation: Utilizes the alimama-creative/FLUX.1-Turbo-Alpha LoRA for rapid image generation with only 8 inference steps Context-Aware Editing: Leverages FLUX.1 Kontext capabilities for intelligent image editing and manipulation Two-Stage Process: Initial generation followed by upscaling for enhanced detail and resolution Efficient Workflow: Optimized for speed while maintaining quality output Workflow Components Stage 1: Fast Generation Model: FLUX.1 Kontext with Turbo Alpha LoRA Steps: 8 (significantly reduced from standard 20-50 steps) Guidance Scale: 2.5 (optimized for Turbo LoRA) Sampler: Euler with simple scheduler Stage 2: Upscaling Method: Ultimate SD Upscale with custom sampling Upscale Model: 4x-ClearRealityV1 Tile Processing: Intelligent slicing for memory efficiency Denoising: 0.2 strength for detail enhancement Technical Setup Required Models FLUX.1 Kontext DEV (FP8 quantized) Alimama FLUX.1-Turbo-Alpha LoRA 4x upscale model Standard FLUX text encoders (CLIP-L + T5) Memory Optimization FP8 model quantization for reduced VRAM usage Tile-based upscaling to handle large images Optional caching nodes for faster iterations Prompt Guidelines The workflow works best with detailed, descriptive prompts. The Turbo LoRA has been trained on high-aesthetic images (6.3+ rating) with resolution >800px, so it excels at: Detailed scene descriptions Lighting and atmosphere specifications Style and aesthetic directions Object replacement and background changes Current Limitations ⚠️ Work in Progress: Output quality is still being refined Some inconsistencies in fine details Occasional artifacts in upscaled regions This workflow represents an efficient approach to context-aware image editing with FLUX, trading some quality for significant speed improvements. Perfect for rapid prototyping and iterative design work.

[Workflow introduction] online running URL ： https://www.runninghub.ai/post/1851088322331561986 After opening the workflow, you need to upload two images. One is a face image, and a frontal portrait is preferred here; the other is a clothing image. First, use Runninghub Captioner to reverse the prompt words, then use Apply PuLID Flux to perform facial migration, and then combine the FLUX model to generate a new image. Then, use the SUPIR model to optimize the image. Finally, generate the ID photo layout effect through the HivisionNode node. The built-in parameters have been set, and you are welcome to experience it. [Usage scenario] You only need to upload two images to generate ID photos with different outfits. You can change them according to different needs to generate a variety of images. Convenient, fast and practical, come and try it! [Key Node] PULD FLUX [Model Version] Flux Model Name: flux1-dev-fp8-Kijai.safetensors SUPIR Model Name: SUPIR-vOQ.ckpt [LoRA Model] None [ControlNet Application] None [K Sampler] CFG: 1.0 Scheduler: beta Noise Reduction: 1.00 Sampler: euler