stable-diffusion-webui/script.js

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",

	"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.",

    "Interrupt": "Stop processing images and return any results accumulated so far.",
    "Save": "Write image to a directory (default - log/images) and generation parameters into csv file.",

    "X values": "Separate values for X axis using commas.",
    "Y values": "Separate values for Y axis using commas.",

    "None": "Do not do anything special",
    "Prompt matrix": "Separate prompts into parts using vertical pipe character (|) and the script will create a picture for every combination of them (except for the first part, which will be present in all combinations)",
    "X/Y plot": "Create a grid where images will have different parameters. Use inputs below to specify which parameterswill be shared by columns and rows",
    "Custom code": "Run python code. Advanced user only. Must run program with --allow-code for this to work",

    "Prompt S/R": "Separate a list of words with commas, and the first word will be used as a keyword: script will search for this word in the prompt, and replace it with others",

    "Tiling": "Produce an image that can be tiled.",
    "Tile overlap": "For SD upscale, how much overlap in pixels should there be between tiles. Tils overlap so that when they are merged back into one oicture, there is no clearly visible seam.",

    "Roll": "Add a random artist to the prompt.",
}

function gradioApp(){
    return document.getElementsByTagName('gradio-app')[0].shadowRoot;
}

function addTitles(root){
	root.querySelectorAll('span, button, select').forEach(function(span){
		tooltip = titles[span.textContent];

		if(!tooltip){
		    tooltip = titles[span.value];
		}

		if(tooltip){
			span.title = tooltip;
		}
	})

	root.querySelectorAll('select').forEach(function(select){
	    if (select.onchange != null) return;

	    select.onchange = function(){
            select.title = titles[select.value] || "";
	    }
	})
}

document.addEventListener("DOMContentLoaded", function() {
    var mutationObserver = new MutationObserver(function(m){
        addTitles(gradioApp());
    });
    mutationObserver.observe( gradioApp(), { childList:true, subtree:true })

});

function selected_gallery_index(){
    var gr = gradioApp()
    var buttons = gradioApp().querySelectorAll(".gallery-item")
    var button = gr.querySelector(".gallery-item.\\!ring-2")

    var result = -1
    buttons.forEach(function(v, i){ if(v==button) { result = i } })

    return result
}

function extract_image_from_gallery(gallery){
    if(gallery.length == 1){
        return gallery[0]
    }

    index = selected_gallery_index()

    if (index < 0 || index >= gallery.length){
        return []
    }

    return gallery[index];
}