console.log("running") titles = { "Sampling steps": "How many times to imptove the generated image itratively; higher values take longer; very low values can produce bad results", "Sampling method": "Which algorithm to use to produce the image", "GFPGAN": "Restore low quality faces using GFPGAN neural network", "Euler a": "Euler Ancestral - very creative, each can get acompletely different pictures depending on step count, setting seps tohigher than 30-40 does not help", "DDIM": "Denoising Diffusion Implicit Models - best at inpainting", "Prompt matrix": "Separate prompts into part using vertical pipe character (|) and the script will create a picture for every combination of them (except for first part, which will be present in all combinations)", "Batch count": "How many batches of images to create", "Batch size": "How many image to create in a single batch", "CFG Scale": "Classifier Free Guidance Scale - how strongly the image should conform to prompt - lower values produce more creative results", "Seed": "A value that determines the output of random number generator - if you create an image with same parameters and seed as another image, you'll get the same result", "Inpaint a part of image": "Draw a mask over an image, and the script will regenerate the masked area with content according to prompt", "Loopback": "Process an image, use it as an input, repeat. Batch count determings number of iterations.", "SD upscale": "Upscale image normally, split result into tiles, improve each tile using img2img, merge whole image back", "Just resize": "Resize image to target resolution. Unless height and width match, you will get incorrect aspect ratio.", "Crop and resize": "Resize the image so that entirety of target resolution is filled with the image. Crop parts that stick out.", "Resize and fill": "Resize the image so that entirety of image is inside target resolution. Fill empty space with image's colors.", "Mask blur": "How much to blur the mask before processing, in pixels.", "Masked content": "What to put inside the masked area before processing it with Stable Diffusion.", "fill": "fill it with colors of the image", "original": "keep whatever was there originally", "latent noise": "fill it with latent space noise", "latent nothing": "fill it with latent space zeroes", "Inpaint at full resolution": "Upscale masked region to target resolution, do inpainting, downscale back and paste into original image", "Denoising Strength": "Determines how little respect the algorithm should have for image's content. At 0, nothing will change, and at 1 you'll get an unrelated image.", } function gradioApp(){ return document.getElementsByTagName('gradio-app')[0]; } function addTitles(root){ root.querySelectorAll('span').forEach(function(span){ tooltip = titles[span.textContent]; if(tooltip){ span.title = tooltip; } }) } document.addEventListener("DOMContentLoaded", function() { var mutationObserver = new MutationObserver(function(m){ addTitles(gradioApp().shadowRoot); }); mutationObserver.observe( gradioApp().shadowRoot, { childList:true, subtree:true }) });