# wyrde's basic WAS node workflow This is a workflow utilizing several WAS nodes. ## Switching nodes The workflow uses noodles (the lines between nodes) to switch from img2img to txt2img and baked vae to loaded vae. * To switch from img2img to txt2img, drag a noodle from the LATENT dot on the "_EmptyLatentImage_" node to the _redirect_ node in the blue box. (The old noodle is replaced.) * Switch back by draging from the LATENT dot on the _VAEEncode_ box to the _redirect_ node. Switching from baked VAE to loaded vae is similar. (Baked VAEs are included inside the model file.) * Drag a noodle from the VAE dot in the _VAELoader_ node to the purple _redirect_ node below. * To change back, drag a noodle from the VAE dot in the _CheckpointLoaderSimple_ node to the purple _redirect_ node below. ## In stable diffusion, size does matter When using img2img, images should be resized to better fit the model. Most models are designed for 512x512 _initial_ generations. 768x512 and 512x768 are also common. Large images will also suck of VRAM and time during sampling for the first generation. Instead of creating a big image in stable diffusion, it is better to go through a process called Hi-Res Fixing. That's a subject for another time, but for this basic workflow, stick to smaller initial images. (This can easily be changed for experimenting.) Back to img2img. * Use the _Resize Image_ node. The node is initially configured to resize images to 512x768. It is best to crop/alter your image in another program so it it fits 1:1 or 1:2 ratio for easy scaling. (Nodes can be used to alter images, but that's a more advanced topic.) Doesn't matter if the ratio isn't perfect, the image is a guide. Closer the better though. * The _node's_ "mode" can be changed from "resize" to "rescale" to easily reduce larger images as well. ## Prompts The workflow includes some basic propmts. Prompts are split into 2 types, positive and negative. * Positive prompts are what what you hope to see in the result. - (Positive prompts are often referred to simply as _prompts_, but sometimes _prompts_ means both positive and negative prompts. Confusing? Welcome to Stable Diffusion!) * Negative prompts are items the user hopes **don't** show up in the result. * There are all sorts of guides on making good prompts. - Basically, a good prompt has a subject and conditionals. - Subject is the main thing desired in the result, such as `adorable cat girl wearing a striped bikini` - conditionals are further details about the subject or the _type_ of image desired. `detailed eyes, detailed hair, pastel hair,` give further detail about the subject. - `absurdres, vibrant, photograph, photographic photo, photogenic, rule of thirds, anime, illustration, medium shot, Azulejo, finely detailed, realistic, masterpiece, best quality, illustration, soft focus, HDR 8K, artstation, pixv, unreal engine 5, SFW, ` is a bunch of information about the type of image desired. + as an aside, _Azulejo_ is a Portuguese tile which adds an interesting style to images with many models. - Negative prompts are much shorter. Usually. Some real doozies exist out there, generally fighting specific things showing up in results. For the basics, `bad hands, NSFW, nude` does well. A couple of those can be removed for more risqué images. (: + Stable Diffusion is often a contrary beast and seems to fight tooth and nail against negativet prompting. ## Click on _Queue Prompt_ The most important pat is, of course, making the images. Click on _Queue Prompt_ to start the process. If ComfyUI doesn't like how nodes are noodles, a bright red error will appear. If it does, various nodes will glow green as it goes through the process. Eventually a picture will appear way at the end. ## Extras What's with the _Latent Upscale by Factor (WAS)_ and second _Image Resize_ at the end? They're there to make it easy to hook in HiRez fixes. Also, I felt like it. At the moment they're not doing much. Changing the _factors_ can easily increase the final image size, but it won't look great. ### The basic of Hi-Rez Fixing: * Move the image saving nodes further to the right. _Shift click_ or _ctrl+drag_ to select multiple nodes. * Move them a bit further. Maybe a litle more. * Space bar can be used to pan, even when nodes are "grabbed". * Holding down _shift_ will snap the selected nodes to the grid. - Grid size can be configured in the cog wheel on the main Queue Prompt box. * Now click on empty space to _deselect_ the nodes. * Return to the _KSampler (WAS)_ node * If the _Latent Upscale_ node was left next to it, great! If not, move it back. * Change the factor to 2. * Now select the _KSampler_ node. Ctrl+C to copy it. * Click empty space to the right of the _Latent Uspcale_ node. Ctrl+V to paste in the sampler. - change _denoise_ to around `0.400`. (The decimal is Very Important™) - for a very basic hi-rez fix, the other settings are okay. * Connect the LATENT dot on the _Latent Upscale to the Latent_image dot on the new _KSampler_. Connect the other noodles from the various objects to the left of the original _KSampler_. - bonus points using more redirects to manage the noodles. Ctrl+C and V to copy paste redirects. - The redirect grab spot is a little buggy. Aim for the top half. * Connect the LATENT dot on the new _KSampler_ to the samples dot on the _VAEDecode_ node (the old noodle vanishes if it wasn't disconnected earlier). * Click Queue Prompt to "fix" the previous image. If comfyUI wasn't restarted at some point, it'll use the old data and start on the new _KSampler_. Otherwise it'll start over from the beginning. * The resulting image is larger, will look a little different (it was sampled), and be of decent quality. ## resources WAS nodes * https://github.com/WASasquatch/was-node-suite-comfyui Model * https://civitai.com/models/8281/perfect-world Info about VAE * https://rentry.org/sdvae Places to find models and other Stable Diffusion goodies * https://civitai.com/ * https://huggingface.co/

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