Mirrors
/
stable-diffusion-webui
mirror of https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

eslint the merged code

This commit is contained in:
AUTOMATIC 2023-05-18 10:03:48 +03:00
parent c08f229318
commit bb80eea9d4
2 changed files with 43 additions and 43 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

84
javascript/hints.js
View File

@ -3,15 +3,15 @@
var titles = {
"Sampling steps": "How many times to improve the generated image iteratively; 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 a completely different picture depending on step count, setting steps higher than 30-40 does not help",
"DDIM": "Denoising Diffusion Implicit Models - best at inpainting",
"UniPC": "Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Models",
"DPM adaptive": "Ignores step count - uses a number of steps determined by the CFG and resolution",
"GFPGAN": "Restore low quality faces using GFPGAN neural network",
"Euler a": "Euler Ancestral - very creative, each can get a completely different picture depending on step count, setting steps higher than 30-40 does not help",
"DDIM": "Denoising Diffusion Implicit Models - best at inpainting",
"UniPC": "Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Models",
"DPM adaptive": "Ignores step count - uses a number of steps determined by the CFG and resolution",
"\u{1F4D0}": "Auto detect size from img2img",
"Batch count": "How many batches of images to create (has no impact on generation performance or VRAM usage)",
"Batch size": "How many image to create in a single batch (increases generation performance at cost of higher VRAM usage)",
"Batch count": "How many batches of images to create (has no impact on generation performance or VRAM usage)",
"Batch size": "How many image to create in a single batch (increases generation performance at cost of higher VRAM usage)",
"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",
"\u{1f3b2}\ufe0f": "Set seed to -1, which will cause a new random number to be used every time",
@ -116,53 +116,53 @@ var titles = {
"Negative Guidance minimum sigma": "Skip negative prompt for steps where image is already mostly denoised; the higher this value, the more skips there will be; provides increased performance in exchange for minor quality reduction."
};
function updateTooltipForSpan(span){
if (span.title) return; // already has a title
function updateTooltipForSpan(span) {
if (span.title) return; // already has a title
let tooltip = localization[titles[span.textContent]] || titles[span.textContent];
if(!tooltip){
if (!tooltip) {
tooltip = localization[titles[span.value]] || titles[span.value];
}
if(!tooltip){
for (const c of span.classList) {
if (c in titles) {
tooltip = localization[titles[c]] || titles[c];
break;
}
}
}
if (!tooltip) {
for (const c of span.classList) {
if (c in titles) {
tooltip = localization[titles[c]] || titles[c];
break;
}
}
}
if(tooltip){
span.title = tooltip;
}
}
function updateTooltipForSelect(select){
if (select.onchange != null) return;
select.onchange = function(){
select.title = localization[titles[select.value]] || titles[select.value] || "";
if (tooltip) {
span.title = tooltip;
}
}
observedTooltipElements = {"SPAN": 1, "BUTTON": 1, "SELECT": 1, "P": 1}
function updateTooltipForSelect(select) {
if (select.onchange != null) return;
onUiUpdate(function(m){
m.forEach(function(record){
record.addedNodes.forEach(function(node){
if(observedTooltipElements[node.tagName]){
updateTooltipForSpan(node)
select.onchange = function() {
select.title = localization[titles[select.value]] || titles[select.value] || "";
};
}
var observedTooltipElements = {SPAN: 1, BUTTON: 1, SELECT: 1, P: 1};
onUiUpdate(function(m) {
m.forEach(function(record) {
record.addedNodes.forEach(function(node) {
if (observedTooltipElements[node.tagName]) {
updateTooltipForSpan(node);
}
if(node.tagName == "SELECT"){
updateTooltipForSelect(node)
if (node.tagName == "SELECT") {
updateTooltipForSelect(node);
}
if(node.querySelectorAll){
node.querySelectorAll('span, button, select, p').forEach(updateTooltipForSpan)
node.querySelectorAll('select').forEach(updateTooltipForSelect)
if (node.querySelectorAll) {
node.querySelectorAll('span, button, select, p').forEach(updateTooltipForSpan);
node.querySelectorAll('select').forEach(updateTooltipForSelect);
}
})
})
})
});
});
});

2
javascript/ui.js
View File

@ -442,7 +442,7 @@ function updateImg2imgResizeToTextAfterChangingImage() {
gradioApp().getElementById('img2img_update_resize_to').click();
}, 500);
return []
return [];
}