mirror of
https://github.com/easydiffusion/easydiffusion.git
synced 2024-11-23 16:53:35 +01:00
1270 lines
44 KiB
JavaScript
1270 lines
44 KiB
JavaScript
"use strict" // Opt in to a restricted variant of JavaScript
|
|
const HEALTH_PING_INTERVAL = 5 // seconds
|
|
const MAX_INIT_IMAGE_DIMENSION = 768
|
|
|
|
const IMAGE_REGEX = new RegExp('data:image/[A-Za-z]+;base64')
|
|
|
|
let sessionId = Date.now()
|
|
|
|
let promptField = document.querySelector('#prompt')
|
|
let promptsFromFileSelector = document.querySelector('#prompt_from_file')
|
|
let promptsFromFileBtn = document.querySelector('#promptsFromFileBtn')
|
|
let negativePromptField = document.querySelector('#negative_prompt')
|
|
let numOutputsTotalField = document.querySelector('#num_outputs_total')
|
|
let numOutputsParallelField = document.querySelector('#num_outputs_parallel')
|
|
let numInferenceStepsField = document.querySelector('#num_inference_steps')
|
|
let guidanceScaleSlider = document.querySelector('#guidance_scale_slider')
|
|
let guidanceScaleField = document.querySelector('#guidance_scale')
|
|
let randomSeedField = document.querySelector("#random_seed")
|
|
let seedField = document.querySelector('#seed')
|
|
let widthField = document.querySelector('#width')
|
|
let heightField = document.querySelector('#height')
|
|
let initImageSelector = document.querySelector("#init_image")
|
|
let initImagePreview = document.querySelector("#init_image_preview")
|
|
let initImageSizeBox = document.querySelector("#init_image_size_box")
|
|
let maskImageSelector = document.querySelector("#mask")
|
|
let maskImagePreview = document.querySelector("#mask_preview")
|
|
let turboField = document.querySelector('#turbo')
|
|
let useCPUField = document.querySelector('#use_cpu')
|
|
let useFullPrecisionField = document.querySelector('#use_full_precision')
|
|
let saveToDiskField = document.querySelector('#save_to_disk')
|
|
let diskPathField = document.querySelector('#diskPath')
|
|
// let allowNSFWField = document.querySelector("#allow_nsfw")
|
|
let useBetaChannelField = document.querySelector("#use_beta_channel")
|
|
let promptStrengthSlider = document.querySelector('#prompt_strength_slider')
|
|
let promptStrengthField = document.querySelector('#prompt_strength')
|
|
let samplerField = document.querySelector('#sampler')
|
|
let samplerSelectionContainer = document.querySelector("#samplerSelection")
|
|
let useFaceCorrectionField = document.querySelector("#use_face_correction")
|
|
let useUpscalingField = document.querySelector("#use_upscale")
|
|
let upscaleModelField = document.querySelector("#upscale_model")
|
|
let stableDiffusionModelField = document.querySelector('#stable_diffusion_model')
|
|
let outputFormatField = document.querySelector('#output_format')
|
|
let showOnlyFilteredImageField = document.querySelector("#show_only_filtered_image")
|
|
let updateBranchLabel = document.querySelector("#updateBranchLabel")
|
|
let streamImageProgressField = document.querySelector("#stream_image_progress")
|
|
|
|
let makeImageBtn = document.querySelector('#makeImage')
|
|
let stopImageBtn = document.querySelector('#stopImage')
|
|
|
|
let imagesContainer = document.querySelector('#current-images')
|
|
let initImagePreviewContainer = document.querySelector('#init_image_preview_container')
|
|
let initImageClearBtn = document.querySelector('.init_image_clear')
|
|
let promptStrengthContainer = document.querySelector('#prompt_strength_container')
|
|
|
|
let initialText = document.querySelector("#initial-text")
|
|
let previewTools = document.querySelector("#preview-tools")
|
|
let clearAllPreviewsBtn = document.querySelector("#clear-all-previews")
|
|
|
|
// let maskSetting = document.querySelector('#editor-inputs-mask_setting')
|
|
// let maskImagePreviewContainer = document.querySelector('#mask_preview_container')
|
|
// let maskImageClearBtn = document.querySelector('#mask_clear')
|
|
let maskSetting = document.querySelector('#enable_mask')
|
|
|
|
let imagePreview = document.querySelector("#preview")
|
|
|
|
// let previewPrompt = document.querySelector('#preview-prompt')
|
|
|
|
let showConfigToggle = document.querySelector('#configToggleBtn')
|
|
// let configBox = document.querySelector('#config')
|
|
// let outputMsg = document.querySelector('#outputMsg')
|
|
// let progressBar = document.querySelector("#progressBar")
|
|
|
|
let soundToggle = document.querySelector('#sound_toggle')
|
|
|
|
let serverStatusColor = document.querySelector('#server-status-color')
|
|
let serverStatusMsg = document.querySelector('#server-status-msg')
|
|
|
|
|
|
document.querySelector('.drawing-board-control-navigation-back').innerHTML = '<i class="fa-solid fa-rotate-left"></i>'
|
|
document.querySelector('.drawing-board-control-navigation-forward').innerHTML = '<i class="fa-solid fa-rotate-right"></i>'
|
|
|
|
let maskResetButton = document.querySelector('.drawing-board-control-navigation-reset')
|
|
maskResetButton.innerHTML = 'Clear'
|
|
maskResetButton.style.fontWeight = 'normal'
|
|
maskResetButton.style.fontSize = '10pt'
|
|
|
|
let serverState = {'status': 'Offline', 'time': Date.now()}
|
|
let lastPromptUsed = ''
|
|
let bellPending = false
|
|
|
|
let taskQueue = []
|
|
let currentTask = null
|
|
|
|
function getLocalStorageBoolItem(key, fallback) {
|
|
let item = localStorage.getItem(key)
|
|
if (item === null) {
|
|
return fallback
|
|
}
|
|
|
|
return (item === 'true' ? true : false)
|
|
}
|
|
|
|
function handleBoolSettingChange(key) {
|
|
return function(e) {
|
|
localStorage.setItem(key, e.target.checked.toString())
|
|
}
|
|
}
|
|
|
|
function handleStringSettingChange(key) {
|
|
return function(e) {
|
|
localStorage.setItem(key, e.target.value.toString())
|
|
}
|
|
}
|
|
|
|
function isSoundEnabled() {
|
|
return getSetting("sound_toggle")
|
|
}
|
|
|
|
function getSavedDiskPath() {
|
|
return getSetting("diskPath")
|
|
}
|
|
|
|
function setStatus(statusType, msg, msgType) {
|
|
}
|
|
|
|
function setServerStatus(msgType, msg) {
|
|
switch(msgType) {
|
|
case 'online':
|
|
serverStatusColor.style.color = 'green'
|
|
serverStatusMsg.style.color = 'green'
|
|
serverStatusMsg.innerText = 'Stable Diffusion is ' + msg
|
|
break
|
|
case 'busy':
|
|
serverStatusColor.style.color = 'rgb(200, 139, 0)'
|
|
serverStatusMsg.style.color = 'rgb(200, 139, 0)'
|
|
serverStatusMsg.innerText = 'Stable Diffusion is ' + msg
|
|
break
|
|
case 'error':
|
|
serverStatusColor.style.color = 'red'
|
|
serverStatusMsg.style.color = 'red'
|
|
serverStatusMsg.innerText = 'Stable Diffusion has stopped'
|
|
break
|
|
}
|
|
}
|
|
function isServerAvailable() {
|
|
if (typeof serverState !== 'object') {
|
|
return false
|
|
}
|
|
switch (serverState.status) {
|
|
case 'LoadingModel':
|
|
case 'Rendering':
|
|
case 'Online':
|
|
return true
|
|
default:
|
|
return false
|
|
}
|
|
}
|
|
|
|
function logMsg(msg, level, outputMsg) {
|
|
if (outputMsg.hasChildNodes()) {
|
|
outputMsg.appendChild(document.createElement('br'))
|
|
}
|
|
if (level === 'error') {
|
|
outputMsg.innerHTML += '<span style="color: red">Error: ' + msg + '</span>'
|
|
} else if (level === 'warn') {
|
|
outputMsg.innerHTML += '<span style="color: orange">Warning: ' + msg + '</span>'
|
|
} else {
|
|
outputMsg.innerText += msg
|
|
}
|
|
console.log(level, msg)
|
|
}
|
|
|
|
function logError(msg, res, outputMsg) {
|
|
logMsg(msg, 'error', outputMsg)
|
|
|
|
console.log('request error', res)
|
|
setStatus('request', 'error', 'error')
|
|
}
|
|
function asyncDelay(timeout) {
|
|
return new Promise(function(resolve, reject) {
|
|
setTimeout(resolve, timeout, true)
|
|
})
|
|
}
|
|
|
|
function playSound() {
|
|
const audio = new Audio('/media/ding.mp3')
|
|
audio.volume = 0.2
|
|
var promise = audio.play()
|
|
if (promise !== undefined) {
|
|
promise.then(_ => {}).catch(error => {
|
|
console.warn("browser blocked autoplay")
|
|
})
|
|
}
|
|
}
|
|
|
|
async function healthCheck() {
|
|
try {
|
|
let res = undefined
|
|
if (sessionId) {
|
|
res = await fetch('/ping?session_id=' + sessionId)
|
|
} else {
|
|
res = await fetch('/ping')
|
|
}
|
|
serverState = await res.json()
|
|
if (typeof serverState !== 'object' || typeof serverState.status !== 'string') {
|
|
serverState = {'status': 'Offline', 'time': Date.now()}
|
|
setServerStatus('error', 'offline')
|
|
return
|
|
}
|
|
// Set status
|
|
switch(serverState.status) {
|
|
case 'Init':
|
|
// Wait for init to complete before updating status.
|
|
break
|
|
case 'Online':
|
|
setServerStatus('online', 'ready')
|
|
break
|
|
case 'LoadingModel':
|
|
setServerStatus('busy', 'loading..')
|
|
break
|
|
case 'Rendering':
|
|
setServerStatus('busy', 'rendering..')
|
|
break
|
|
default: // Unavailable
|
|
setServerStatus('error', serverState.status.toLowerCase())
|
|
break
|
|
}
|
|
serverState.time = Date.now()
|
|
} catch (e) {
|
|
serverState = {'status': 'Offline', 'time': Date.now()}
|
|
setServerStatus('error', 'offline')
|
|
}
|
|
}
|
|
|
|
function showImages(reqBody, res, outputContainer, livePreview) {
|
|
let imageItemElements = outputContainer.querySelectorAll('.imgItem')
|
|
if(typeof res != 'object') return
|
|
res.output.reverse()
|
|
res.output.forEach((result, index) => {
|
|
const imageData = result?.data || result?.path + '?t=' + Date.now(),
|
|
imageSeed = result?.seed,
|
|
imagePrompt = reqBody.prompt,
|
|
imageInferenceSteps = reqBody.num_inference_steps,
|
|
imageGuidanceScale = reqBody.guidance_scale,
|
|
imageWidth = reqBody.width,
|
|
imageHeight = reqBody.height;
|
|
|
|
if (!imageData.includes('/')) {
|
|
// res contained no data for the image, stop execution
|
|
setStatus('request', 'invalid image', 'error')
|
|
return
|
|
}
|
|
|
|
let imageItemElem = (index < imageItemElements.length ? imageItemElements[index] : null)
|
|
if(!imageItemElem) {
|
|
imageItemElem = document.createElement('div')
|
|
imageItemElem.className = 'imgItem'
|
|
imageItemElem.innerHTML = `
|
|
<div class="imgContainer">
|
|
<img/>
|
|
<div class="imgItemInfo">
|
|
<span class="imgSeedLabel"></span>
|
|
</div>
|
|
</div>
|
|
`
|
|
outputContainer.appendChild(imageItemElem)
|
|
}
|
|
const imageElem = imageItemElem.querySelector('img')
|
|
imageElem.src = imageData
|
|
imageElem.width = parseInt(imageWidth)
|
|
imageElem.height = parseInt(imageHeight)
|
|
imageElem.setAttribute('data-prompt', imagePrompt)
|
|
imageElem.setAttribute('data-steps', imageInferenceSteps)
|
|
imageElem.setAttribute('data-guidance', imageGuidanceScale)
|
|
|
|
|
|
const imageInfo = imageItemElem.querySelector('.imgItemInfo')
|
|
imageInfo.style.visibility = (livePreview ? 'hidden' : 'visible')
|
|
|
|
if ('seed' in result && !imageElem.hasAttribute('data-seed')) {
|
|
const req = Object.assign({}, reqBody, {
|
|
seed: result?.seed || reqBody.seed
|
|
})
|
|
imageElem.setAttribute('data-seed', req.seed)
|
|
const imageSeedLabel = imageItemElem.querySelector('.imgSeedLabel')
|
|
imageSeedLabel.innerText = 'Seed: ' + req.seed
|
|
|
|
let buttons = [
|
|
{ text: 'Use as Input', on_click: onUseAsInputClick },
|
|
{ text: 'Download', on_click: onDownloadImageClick },
|
|
{ text: 'Make Similar Images', on_click: onMakeSimilarClick },
|
|
{ text: 'Draw another 25 steps', on_click: onContinueDrawingClick },
|
|
{ text: 'Upscale (new)', on_click: onUpscaleClick, filter: (req, img) => !req.use_upscale },
|
|
{ text: 'Fix Faces', on_click: onFixFacesClick, filter: (req, img) => !req.use_face_correction }
|
|
]
|
|
|
|
// include the plugins
|
|
buttons = buttons.concat(PLUGINS['IMAGE_INFO_BUTTONS'])
|
|
|
|
const imgItemInfo = imageItemElem.querySelector('.imgItemInfo')
|
|
const img = imageItemElem.querySelector('img')
|
|
const createButton = function(btnInfo) {
|
|
const newButton = document.createElement('button')
|
|
newButton.classList.add('tasksBtns')
|
|
newButton.innerText = btnInfo.text
|
|
newButton.addEventListener('click', function() {
|
|
btnInfo.on_click(req, img)
|
|
})
|
|
imgItemInfo.appendChild(newButton)
|
|
}
|
|
buttons.forEach(btn => {
|
|
if (btn.filter && btn.filter(req, img) === false) {
|
|
return
|
|
}
|
|
|
|
createButton(btn)
|
|
})
|
|
}
|
|
})
|
|
}
|
|
|
|
function onUseAsInputClick(req, img) {
|
|
const imgData = img.src
|
|
|
|
initImageSelector.value = null
|
|
initImagePreview.src = imgData
|
|
|
|
initImagePreviewContainer.style.display = 'block'
|
|
inpaintingEditorContainer.style.display = 'none'
|
|
promptStrengthContainer.style.display = 'table-row'
|
|
maskSetting.checked = false
|
|
samplerSelectionContainer.style.display = 'none'
|
|
}
|
|
|
|
function onDownloadImageClick(req, img) {
|
|
const imgData = img.src
|
|
const imageSeed = img.getAttribute('data-seed')
|
|
const imagePrompt = img.getAttribute('data-prompt')
|
|
const imageInferenceSteps = img.getAttribute('data-steps')
|
|
const imageGuidanceScale = img.getAttribute('data-guidance')
|
|
|
|
const imgDownload = document.createElement('a')
|
|
imgDownload.download = createFileName(imagePrompt, imageSeed, imageInferenceSteps, imageGuidanceScale, req['output_format'])
|
|
imgDownload.href = imgData
|
|
imgDownload.click()
|
|
}
|
|
|
|
function onMakeSimilarClick(req, img) {
|
|
let newTaskRequest = getCurrentUserRequest()
|
|
|
|
newTaskRequest.reqBody = Object.assign({}, req, {
|
|
num_outputs: 1,
|
|
use_cpu: useCPUField.checked,
|
|
num_inference_steps: 50,
|
|
guidance_scale: 7.5,
|
|
prompt_strength: 0.7,
|
|
init_image: img.src,
|
|
seed: Math.floor(Math.random() * 10000000)
|
|
})
|
|
|
|
newTaskRequest.numOutputsTotal = 5
|
|
newTaskRequest.batchCount = 5
|
|
newTaskRequest.seed = newTaskRequest.reqBody.seed
|
|
|
|
delete newTaskRequest.reqBody.mask
|
|
|
|
createTask(newTaskRequest)
|
|
}
|
|
|
|
function onUpscaleClick(req, img) {
|
|
let newTaskRequest = getCurrentUserRequest()
|
|
const imageSeed = img.getAttribute('data-seed')
|
|
|
|
newTaskRequest.reqBody = Object.assign({}, req, {
|
|
num_outputs: 1,
|
|
use_cpu: useCPUField.checked,
|
|
use_upscale: upscaleModelField.value,
|
|
seed: imageSeed
|
|
})
|
|
|
|
newTaskRequest.numOutputsTotal = 1
|
|
newTaskRequest.batchCount = 1
|
|
newTaskRequest.seed = newTaskRequest.reqBody.seed
|
|
|
|
createTask(newTaskRequest)
|
|
}
|
|
|
|
function onFixFacesClick(req, img) {
|
|
let newTaskRequest = getCurrentUserRequest()
|
|
const imageSeed = img.getAttribute('data-seed')
|
|
|
|
newTaskRequest.reqBody = Object.assign({}, req, {
|
|
num_outputs: 1,
|
|
use_cpu: useCPUField.checked,
|
|
use_face_correction: 'GFPGANv1.3',
|
|
seed: imageSeed
|
|
})
|
|
|
|
newTaskRequest.numOutputsTotal = 1
|
|
newTaskRequest.batchCount = 1
|
|
newTaskRequest.seed = newTaskRequest.reqBody.seed
|
|
|
|
createTask(newTaskRequest)
|
|
}
|
|
|
|
function onContinueDrawingClick(req, img) {
|
|
let newTaskRequest = getCurrentUserRequest()
|
|
const imageSeed = img.getAttribute('data-seed')
|
|
|
|
newTaskRequest.reqBody = Object.assign({}, req, {
|
|
num_outputs: 1,
|
|
use_cpu: useCPUField.checked,
|
|
num_inference_steps: parseInt(req.num_inference_steps) + 25,
|
|
seed: imageSeed
|
|
})
|
|
|
|
newTaskRequest.numOutputsTotal = 1
|
|
newTaskRequest.batchCount = 1
|
|
newTaskRequest.seed = newTaskRequest.reqBody.seed
|
|
|
|
createTask(newTaskRequest)
|
|
}
|
|
|
|
// makes a single image. don't call this directly, use makeImage() instead
|
|
async function doMakeImage(task) {
|
|
if (task.stopped) {
|
|
return
|
|
}
|
|
|
|
const reqBody = task.reqBody
|
|
const batchCount = task.batchCount
|
|
const outputContainer = document.createElement('div')
|
|
|
|
outputContainer.className = 'img-batch'
|
|
task.outputContainer.insertBefore(outputContainer, task.outputContainer.firstChild)
|
|
|
|
const outputMsg = task['outputMsg']
|
|
const previewPrompt = task['previewPrompt']
|
|
const progressBar = task['progressBar']
|
|
|
|
let res = undefined
|
|
try {
|
|
const lastTask = serverState.task
|
|
let renderRequest = undefined
|
|
do {
|
|
res = await fetch('/render', {
|
|
method: 'POST',
|
|
headers: {
|
|
'Content-Type': 'application/json'
|
|
},
|
|
body: JSON.stringify(reqBody)
|
|
})
|
|
renderRequest = await res.json()
|
|
// status_code 503, already a task running.
|
|
} while (renderRequest.status_code === 503 && await asyncDelay(30 * 1000))
|
|
if (typeof renderRequest?.stream !== 'string') {
|
|
console.log('Endpoint response: ', renderRequest)
|
|
throw new Error('Endpoint response does not contains a response stream url.')
|
|
}
|
|
task['taskStatusLabel'].innerText = "Waiting"
|
|
task['taskStatusLabel'].classList.add('waitingTaskLabel')
|
|
task['taskStatusLabel'].classList.remove('activeTaskLabel')
|
|
|
|
do { // Wait for server status to update.
|
|
await asyncDelay(250)
|
|
if (!isServerAvailable()) {
|
|
throw new Error('Connexion with server lost.')
|
|
}
|
|
} while (serverState.time > (Date.now() - (10 * 1000)) && serverState.task !== renderRequest.task)
|
|
if (serverState.session !== 'pending' && serverState.session !== 'running' && serverState.session !== 'buffer') {
|
|
if (serverState.session === 'stopped') {
|
|
return false
|
|
}
|
|
|
|
throw new Error('Unexpected server task state: ' + serverState.session || 'Undefined')
|
|
}
|
|
while (serverState.task === renderRequest.task && serverState.session === 'pending') {
|
|
// Wait for task to start on server.
|
|
await asyncDelay(1500)
|
|
}
|
|
|
|
// Task started!
|
|
res = await fetch(renderRequest.stream, {
|
|
headers: {
|
|
'Content-Type': 'application/json'
|
|
},
|
|
})
|
|
|
|
task['taskStatusLabel'].innerText = "Processing"
|
|
task['taskStatusLabel'].classList.add('activeTaskLabel')
|
|
task['taskStatusLabel'].classList.remove('waitingTaskLabel')
|
|
|
|
let stepUpdate = undefined
|
|
let reader = res.body.getReader()
|
|
let textDecoder = new TextDecoder()
|
|
let finalJSON = ''
|
|
let readComplete = false
|
|
while (!readComplete || finalJSON.length > 0) {
|
|
let t = Date.now()
|
|
let jsonStr = ''
|
|
if (!readComplete) {
|
|
const {value, done} = await reader.read()
|
|
if (done) {
|
|
readComplete = true
|
|
}
|
|
if (value) {
|
|
jsonStr = textDecoder.decode(value)
|
|
}
|
|
}
|
|
stepUpdate = undefined
|
|
try {
|
|
// hack for a middleman buffering all the streaming updates, and unleashing them on the poor browser in one shot.
|
|
// this results in having to parse JSON like {"step": 1}{"step": 2}{"step": 3}{"ste...
|
|
// which is obviously invalid and can happen at any point while rendering.
|
|
// So we need to extract only the next {} section
|
|
if (finalJSON.length > 0) {
|
|
// Append new data when required
|
|
if (jsonStr.length > 0) {
|
|
jsonStr = finalJSON + jsonStr
|
|
} else {
|
|
jsonStr = finalJSON
|
|
}
|
|
finalJSON = ''
|
|
}
|
|
// Find next delimiter
|
|
let lastChunkIdx = jsonStr.indexOf('}{')
|
|
if (lastChunkIdx !== -1) {
|
|
finalJSON = jsonStr.substring(0, lastChunkIdx + 1)
|
|
jsonStr = jsonStr.substring(lastChunkIdx + 1)
|
|
} else {
|
|
finalJSON = jsonStr
|
|
jsonStr = ''
|
|
}
|
|
// Try to parse
|
|
stepUpdate = (finalJSON.length > 0 ? JSON.parse(finalJSON) : undefined)
|
|
finalJSON = jsonStr
|
|
} catch (e) {
|
|
if (e instanceof SyntaxError && !readComplete) {
|
|
finalJSON += jsonStr
|
|
} else {
|
|
throw e
|
|
}
|
|
}
|
|
if (typeof stepUpdate === 'object' && 'step' in stepUpdate) {
|
|
let batchSize = stepUpdate.total_steps
|
|
let overallStepCount = stepUpdate.step + task.batchesDone * batchSize
|
|
let totalSteps = batchCount * batchSize
|
|
let percent = 100 * (overallStepCount / totalSteps)
|
|
percent = (percent > 100 ? 100 : percent)
|
|
percent = percent.toFixed(0)
|
|
let timeTaken = stepUpdate.step_time // sec
|
|
|
|
let stepsRemaining = totalSteps - overallStepCount
|
|
stepsRemaining = (stepsRemaining < 0 ? 0 : stepsRemaining)
|
|
let timeRemaining = (timeTaken === -1 ? '' : stepsRemaining * timeTaken * 1000) // ms
|
|
|
|
outputMsg.innerHTML = `Batch ${task.batchesDone+1} of ${batchCount}`
|
|
outputMsg.innerHTML += `. Generating image(s): ${percent}%`
|
|
|
|
timeRemaining = (timeTaken !== -1 ? millisecondsToStr(timeRemaining) : '')
|
|
outputMsg.innerHTML += `. Time remaining (approx): ${timeRemaining}`
|
|
outputMsg.style.display = 'block'
|
|
|
|
if (stepUpdate.output !== undefined) {
|
|
showImages(reqBody, stepUpdate, outputContainer, true)
|
|
}
|
|
}
|
|
if (stepUpdate?.status) {
|
|
break
|
|
}
|
|
if (readComplete && finalJSON.length <= 0) {
|
|
if (res.status === 200) {
|
|
await asyncDelay(1000)
|
|
res = await fetch(renderRequest.stream, {
|
|
headers: {
|
|
'Content-Type': 'application/json'
|
|
},
|
|
})
|
|
reader = res.body.getReader()
|
|
readComplete = false
|
|
} else {
|
|
console.log('Stream stopped: ', res)
|
|
}
|
|
}
|
|
}
|
|
|
|
if (typeof stepUpdate === 'object' && stepUpdate.status !== 'succeeded') {
|
|
let msg = ''
|
|
if ('detail' in stepUpdate && typeof stepUpdate.detail === 'string' && stepUpdate.detail.length > 0) {
|
|
msg = stepUpdate.detail
|
|
if (msg.toLowerCase().includes('out of memory')) {
|
|
msg += `<br/><br/>
|
|
<b>Suggestions</b>:
|
|
<br/>
|
|
1. If you have set an initial image, please try reducing its dimension to ${MAX_INIT_IMAGE_DIMENSION}x${MAX_INIT_IMAGE_DIMENSION} or smaller.<br/>
|
|
2. Try disabling the '<em>Turbo mode</em>' under '<em>Advanced Settings</em>'.<br/>
|
|
3. Try generating a smaller image.<br/>`
|
|
}
|
|
} else {
|
|
msg = `Unexpected Read Error:<br/><pre>StepUpdate: ${JSON.stringify(stepUpdate, undefined, 4)}</pre>`
|
|
}
|
|
logError(msg, res, outputMsg)
|
|
return false
|
|
}
|
|
if (typeof stepUpdate !== 'object' || !res || res.status != 200) {
|
|
if (!isServerAvailable()) {
|
|
logError("Stable Diffusion is still starting up, please wait. If this goes on beyond a few minutes, Stable Diffusion has probably crashed. Please check the error message in the command-line window.", res, outputMsg)
|
|
} else if (typeof res === 'object') {
|
|
let msg = 'Stable Diffusion had an error reading the response: '
|
|
try { // 'Response': body stream already read
|
|
msg += 'Read: ' + await res.text()
|
|
} catch(e) {
|
|
msg += 'Unexpected end of stream. '
|
|
}
|
|
if (finalJSON) {
|
|
msg += 'Buffered data: ' + finalJSON
|
|
}
|
|
logError(msg, res, outputMsg)
|
|
} else {
|
|
let msg = `Unexpected Read Error:<br/><pre>Response: ${res}<br/>StepUpdate: ${typeof stepUpdate === 'object' ? JSON.stringify(stepUpdate, undefined, 4) : stepUpdate}</pre>`
|
|
logError(msg, res, outputMsg)
|
|
}
|
|
progressBar.style.display = 'none'
|
|
return false
|
|
}
|
|
|
|
lastPromptUsed = reqBody['prompt']
|
|
showImages(reqBody, stepUpdate, outputContainer, false)
|
|
} catch (e) {
|
|
console.log('request error', e)
|
|
logError('Stable Diffusion had an error. Please check the logs in the command-line window. <br/><br/>' + e + '<br/><pre>' + e.stack + '</pre>', res, outputMsg)
|
|
setStatus('request', 'error', 'error')
|
|
progressBar.style.display = 'none'
|
|
return false
|
|
}
|
|
return true
|
|
}
|
|
|
|
async function checkTasks() {
|
|
if (taskQueue.length === 0) {
|
|
setStatus('request', 'done', 'success')
|
|
setTimeout(checkTasks, 500)
|
|
stopImageBtn.style.display = 'none'
|
|
makeImageBtn.innerHTML = 'Make Image'
|
|
|
|
currentTask = null
|
|
|
|
if (bellPending) {
|
|
if (isSoundEnabled()) {
|
|
playSound()
|
|
}
|
|
bellPending = false
|
|
}
|
|
|
|
return
|
|
}
|
|
|
|
setStatus('request', 'fetching..')
|
|
|
|
stopImageBtn.style.display = 'block'
|
|
makeImageBtn.innerHTML = 'Enqueue Next Image'
|
|
bellPending = true
|
|
|
|
previewTools.style.display = 'block'
|
|
|
|
let task = taskQueue.pop()
|
|
currentTask = task
|
|
|
|
let time = Date.now()
|
|
|
|
let successCount = 0
|
|
|
|
task.isProcessing = true
|
|
task['stopTask'].innerHTML = '<i class="fa-solid fa-circle-stop"></i> Stop'
|
|
task['taskStatusLabel'].innerText = "Starting"
|
|
task['taskStatusLabel'].classList.add('waitingTaskLabel')
|
|
|
|
const genSeeds = Boolean(typeof task.reqBody.seed !== 'number' || (task.reqBody.seed === task.seed && task.numOutputsTotal > 1))
|
|
const startSeed = task.reqBody.seed || task.seed
|
|
for (let i = 0; i < task.batchCount; i++) {
|
|
let newTask = task
|
|
if (task.batchCount > 1) {
|
|
// Each output render batch needs it's own task instance to avoid altering the other runs after they are completed.
|
|
newTask = Object.assign({}, task, {
|
|
reqBody: Object.assign({}, task.reqBody)
|
|
})
|
|
}
|
|
if (genSeeds) {
|
|
newTask.reqBody.seed = parseInt(startSeed) + (i * newTask.reqBody.num_outputs)
|
|
newTask.seed = newTask.reqBody.seed
|
|
} else if (newTask.seed !== newTask.reqBody.seed) {
|
|
newTask.seed = newTask.reqBody.seed
|
|
}
|
|
|
|
let success = await doMakeImage(newTask)
|
|
task.batchesDone++
|
|
|
|
if (!task.isProcessing || !success) {
|
|
break
|
|
}
|
|
|
|
if (success) {
|
|
successCount++
|
|
}
|
|
}
|
|
|
|
task.isProcessing = false
|
|
task['stopTask'].innerHTML = '<i class="fa-solid fa-trash-can"></i> Remove'
|
|
task['taskStatusLabel'].style.display = 'none'
|
|
|
|
time = Date.now() - time
|
|
time /= 1000
|
|
|
|
if (successCount === task.batchCount) {
|
|
task.outputMsg.innerText = 'Processed ' + task.numOutputsTotal + ' images in ' + time + ' seconds'
|
|
// setStatus('request', 'done', 'success')
|
|
} else {
|
|
if (task.outputMsg.innerText.toLowerCase().indexOf('error') === -1) {
|
|
task.outputMsg.innerText = 'Task ended after ' + time + ' seconds'
|
|
}
|
|
}
|
|
|
|
if (randomSeedField.checked) {
|
|
seedField.value = task.seed
|
|
}
|
|
|
|
currentTask = null
|
|
|
|
if (typeof requestIdleCallback === 'function') {
|
|
requestIdleCallback(checkTasks, { timeout: 30 * 1000 })
|
|
} else {
|
|
setTimeout(checkTasks, 500)
|
|
}
|
|
}
|
|
if (typeof requestIdleCallback === 'function') {
|
|
requestIdleCallback(checkTasks, { timeout: 30 * 1000 })
|
|
} else {
|
|
setTimeout(checkTasks, 10)
|
|
}
|
|
|
|
function getCurrentUserRequest() {
|
|
const numOutputsTotal = parseInt(numOutputsTotalField.value)
|
|
const numOutputsParallel = parseInt(numOutputsParallelField.value)
|
|
const seed = (randomSeedField.checked ? Math.floor(Math.random() * 10000000) : parseInt(seedField.value))
|
|
|
|
const newTask = {
|
|
isProcessing: false,
|
|
stopped: false,
|
|
batchesDone: 0,
|
|
numOutputsTotal: numOutputsTotal,
|
|
batchCount: Math.ceil(numOutputsTotal / numOutputsParallel),
|
|
seed,
|
|
|
|
reqBody: {
|
|
session_id: sessionId,
|
|
seed,
|
|
negative_prompt: negativePromptField.value.trim(),
|
|
num_outputs: numOutputsParallel,
|
|
num_inference_steps: numInferenceStepsField.value,
|
|
guidance_scale: guidanceScaleField.value,
|
|
width: widthField.value,
|
|
height: heightField.value,
|
|
// allow_nsfw: allowNSFWField.checked,
|
|
turbo: turboField.checked,
|
|
use_cpu: useCPUField.checked,
|
|
use_full_precision: useFullPrecisionField.checked,
|
|
use_stable_diffusion_model: stableDiffusionModelField.value,
|
|
stream_progress_updates: true,
|
|
stream_image_progress: (numOutputsTotal > 50 ? false : streamImageProgressField.checked),
|
|
show_only_filtered_image: showOnlyFilteredImageField.checked,
|
|
output_format: outputFormatField.value
|
|
}
|
|
}
|
|
if (IMAGE_REGEX.test(initImagePreview.src)) {
|
|
newTask.reqBody.init_image = initImagePreview.src
|
|
newTask.reqBody.prompt_strength = promptStrengthField.value
|
|
|
|
// if (IMAGE_REGEX.test(maskImagePreview.src)) {
|
|
// newTask.reqBody.mask = maskImagePreview.src
|
|
// }
|
|
if (maskSetting.checked) {
|
|
newTask.reqBody.mask = inpaintingEditor.getImg()
|
|
}
|
|
newTask.reqBody.sampler = 'ddim'
|
|
} else {
|
|
newTask.reqBody.sampler = samplerField.value
|
|
}
|
|
if (saveToDiskField.checked && diskPathField.value.trim() !== '') {
|
|
newTask.reqBody.save_to_disk_path = diskPathField.value.trim()
|
|
}
|
|
if (useFaceCorrectionField.checked) {
|
|
newTask.reqBody.use_face_correction = 'GFPGANv1.3'
|
|
}
|
|
if (useUpscalingField.checked) {
|
|
newTask.reqBody.use_upscale = upscaleModelField.value
|
|
}
|
|
return newTask
|
|
}
|
|
|
|
function makeImage() {
|
|
if (!isServerAvailable()) {
|
|
alert('The server is not available.')
|
|
return
|
|
}
|
|
const taskTemplate = getCurrentUserRequest()
|
|
const newTaskRequests = []
|
|
getPrompts().forEach((prompt) => newTaskRequests.push(Object.assign({}, taskTemplate, {
|
|
reqBody: Object.assign({ prompt: prompt }, taskTemplate.reqBody)
|
|
})))
|
|
newTaskRequests.forEach(createTask)
|
|
|
|
initialText.style.display = 'none'
|
|
}
|
|
|
|
function createTask(task) {
|
|
let taskConfig = `Seed: ${task.seed}, Sampler: ${task.reqBody.sampler}, Inference Steps: ${task.reqBody.num_inference_steps}, Guidance Scale: ${task.reqBody.guidance_scale}, Model: ${task.reqBody.use_stable_diffusion_model}`
|
|
if (negativePromptField.value.trim() !== '') {
|
|
taskConfig += `, Negative Prompt: ${task.reqBody.negative_prompt}`
|
|
}
|
|
if (task.reqBody.init_image !== undefined) {
|
|
taskConfig += `, Prompt Strength: ${task.reqBody.prompt_strength}`
|
|
}
|
|
if (task.reqBody.use_face_correction) {
|
|
taskConfig += `, Fix Faces: ${task.reqBody.use_face_correction}`
|
|
}
|
|
if (task.reqBody.use_upscale) {
|
|
taskConfig += `, Upscale: ${task.reqBody.use_upscale}`
|
|
}
|
|
|
|
let taskEntry = document.createElement('div')
|
|
taskEntry.className = 'imageTaskContainer'
|
|
taskEntry.innerHTML = ` <div class="taskStatusLabel">Enqueued</div>
|
|
<button class="secondaryButton stopTask"><i class="fa-solid fa-trash-can"></i> Remove</button>
|
|
<div class="preview-prompt collapsible active"></div>
|
|
<div class="taskConfig">${taskConfig}</div>
|
|
<div class="collapsible-content" style="display: block">
|
|
<div class="outputMsg"></div>
|
|
<div class="progressBar"></div>
|
|
<div class="img-preview">
|
|
</div>`
|
|
|
|
createCollapsibles(taskEntry)
|
|
|
|
task['taskStatusLabel'] = taskEntry.querySelector('.taskStatusLabel')
|
|
task['outputContainer'] = taskEntry.querySelector('.img-preview')
|
|
task['outputMsg'] = taskEntry.querySelector('.outputMsg')
|
|
task['previewPrompt'] = taskEntry.querySelector('.preview-prompt')
|
|
task['progressBar'] = taskEntry.querySelector('.progressBar')
|
|
task['stopTask'] = taskEntry.querySelector('.stopTask')
|
|
|
|
task['stopTask'].addEventListener('click', async function() {
|
|
if (task['isProcessing']) {
|
|
task.isProcessing = false
|
|
try {
|
|
let res = await fetch('/image/stop?session_id=' + sessionId)
|
|
} catch (e) {
|
|
console.log(e)
|
|
}
|
|
} else {
|
|
let idx = taskQueue.indexOf(task)
|
|
if (idx >= 0) {
|
|
taskQueue.splice(idx, 1)
|
|
}
|
|
|
|
taskEntry.remove()
|
|
}
|
|
})
|
|
|
|
imagePreview.insertBefore(taskEntry, previewTools.nextSibling)
|
|
|
|
task.previewPrompt.innerText = task.reqBody.prompt
|
|
if (task.previewPrompt.innerText.trim() === '') {
|
|
task.previewPrompt.innerHTML = ' ' // allows the results to be collapsed
|
|
}
|
|
|
|
taskQueue.unshift(task)
|
|
}
|
|
|
|
function getPrompts() {
|
|
let prompts = promptField.value
|
|
if (prompts.trim() === '') {
|
|
return ['']
|
|
}
|
|
|
|
prompts = prompts.split('\n')
|
|
prompts = prompts.map(prompt => prompt.trim())
|
|
prompts = prompts.filter(prompt => prompt !== '')
|
|
|
|
let promptsToMake = applySetOperator(prompts)
|
|
promptsToMake = applyPermuteOperator(promptsToMake)
|
|
|
|
if (activeTags.length <= 0) {
|
|
return promptsToMake
|
|
}
|
|
|
|
const promptTags = activeTags.map(x => x.name).join(", ")
|
|
return promptsToMake.map((prompt) => `${prompt}, ${promptTags}`)
|
|
}
|
|
|
|
function applySetOperator(prompts) {
|
|
let promptsToMake = []
|
|
let braceExpander = new BraceExpander()
|
|
prompts.forEach(prompt => {
|
|
let expandedPrompts = braceExpander.expand(prompt)
|
|
promptsToMake = promptsToMake.concat(expandedPrompts)
|
|
})
|
|
|
|
return promptsToMake
|
|
}
|
|
|
|
function applyPermuteOperator(prompts) {
|
|
let promptsToMake = []
|
|
prompts.forEach(prompt => {
|
|
let promptMatrix = prompt.split('|')
|
|
prompt = promptMatrix.shift().trim()
|
|
promptsToMake.push(prompt)
|
|
|
|
promptMatrix = promptMatrix.map(p => p.trim())
|
|
promptMatrix = promptMatrix.filter(p => p !== '')
|
|
|
|
if (promptMatrix.length > 0) {
|
|
let promptPermutations = permutePrompts(prompt, promptMatrix)
|
|
promptsToMake = promptsToMake.concat(promptPermutations)
|
|
}
|
|
})
|
|
|
|
return promptsToMake
|
|
}
|
|
|
|
function permutePrompts(promptBase, promptMatrix) {
|
|
let prompts = []
|
|
let permutations = permute(promptMatrix)
|
|
permutations.forEach(perm => {
|
|
let prompt = promptBase
|
|
|
|
if (perm.length > 0) {
|
|
let promptAddition = perm.join(', ')
|
|
if (promptAddition.trim() === '') {
|
|
return
|
|
}
|
|
|
|
prompt += ', ' + promptAddition
|
|
}
|
|
|
|
prompts.push(prompt)
|
|
})
|
|
|
|
return prompts
|
|
}
|
|
|
|
// create a file name with embedded prompt and metadata
|
|
// for easier cateloging and comparison
|
|
function createFileName(prompt, seed, steps, guidance, outputFormat) {
|
|
|
|
// Most important information is the prompt
|
|
let underscoreName = prompt.replace(/[^a-zA-Z0-9]/g, '_')
|
|
underscoreName = underscoreName.substring(0, 100)
|
|
//const steps = numInferenceStepsField.value
|
|
//const guidance = guidanceScaleField.value
|
|
|
|
// name and the top level metadata
|
|
let fileName = `${underscoreName}_Seed-${seed}_Steps-${steps}_Guidance-${guidance}`
|
|
|
|
// add the tags
|
|
// let tags = []
|
|
// let tagString = ''
|
|
// document.querySelectorAll(modifyTagsSelector).forEach(function(tag) {
|
|
// tags.push(tag.innerHTML)
|
|
// })
|
|
|
|
// join the tags with a pipe
|
|
// if (activeTags.length > 0) {
|
|
// tagString = '_Tags-'
|
|
// tagString += tags.join('|')
|
|
// }
|
|
|
|
// // append empty or populated tags
|
|
// fileName += `${tagString}`
|
|
|
|
// add the file extension
|
|
fileName += '.' + (outputFormat === 'png' ? 'png' : 'jpeg')
|
|
|
|
return fileName
|
|
}
|
|
|
|
async function stopAllTasks() {
|
|
taskQueue.forEach(task => {
|
|
task.isProcessing = false
|
|
})
|
|
taskQueue = []
|
|
|
|
if (currentTask !== null) {
|
|
currentTask.isProcessing = false
|
|
}
|
|
|
|
try {
|
|
let res = await fetch('/image/stop?session_id=' + sessionId)
|
|
} catch (e) {
|
|
console.log(e)
|
|
}
|
|
}
|
|
|
|
clearAllPreviewsBtn.addEventListener('click', async function() {
|
|
await stopAllTasks()
|
|
|
|
let taskEntries = document.querySelectorAll('.imageTaskContainer')
|
|
taskEntries.forEach(task => {
|
|
task.remove()
|
|
})
|
|
|
|
previewTools.style.display = 'none'
|
|
initialText.style.display = 'block'
|
|
})
|
|
|
|
stopImageBtn.addEventListener('click', async function() {
|
|
await stopAllTasks()
|
|
})
|
|
|
|
widthField.addEventListener('change', onDimensionChange)
|
|
heightField.addEventListener('change', onDimensionChange)
|
|
|
|
function onDimensionChange() {
|
|
if (!maskSetting.checked) {
|
|
return
|
|
}
|
|
let widthValue = parseInt(widthField.value)
|
|
let heightValue = parseInt(heightField.value)
|
|
|
|
resizeInpaintingEditor(widthValue, heightValue)
|
|
}
|
|
|
|
saveToDiskField.addEventListener('click', function(e) {
|
|
diskPathField.disabled = !this.checked
|
|
})
|
|
|
|
useUpscalingField.addEventListener('click', function(e) {
|
|
upscaleModelField.disabled = !this.checked
|
|
})
|
|
|
|
makeImageBtn.addEventListener('click', makeImage)
|
|
|
|
|
|
function updateGuidanceScale() {
|
|
guidanceScaleField.value = guidanceScaleSlider.value / 10
|
|
guidanceScaleField.dispatchEvent(new Event("change"))
|
|
}
|
|
|
|
function updateGuidanceScaleSlider() {
|
|
if (guidanceScaleField.value < 0) {
|
|
guidanceScaleField.value = 0
|
|
} else if (guidanceScaleField.value > 50) {
|
|
guidanceScaleField.value = 50
|
|
}
|
|
|
|
guidanceScaleSlider.value = guidanceScaleField.value * 10
|
|
}
|
|
|
|
guidanceScaleSlider.addEventListener('input', updateGuidanceScale)
|
|
guidanceScaleField.addEventListener('input', updateGuidanceScaleSlider)
|
|
updateGuidanceScale()
|
|
|
|
function updatePromptStrength() {
|
|
promptStrengthField.value = promptStrengthSlider.value / 100
|
|
promptStrengthField.dispatchEvent(new Event("change"))
|
|
}
|
|
|
|
function updatePromptStrengthSlider() {
|
|
if (promptStrengthField.value < 0) {
|
|
promptStrengthField.value = 0
|
|
} else if (promptStrengthField.value > 0.99) {
|
|
promptStrengthField.value = 0.99
|
|
}
|
|
|
|
promptStrengthSlider.value = promptStrengthField.value * 100
|
|
}
|
|
|
|
promptStrengthSlider.addEventListener('input', updatePromptStrength)
|
|
promptStrengthField.addEventListener('input', updatePromptStrengthSlider)
|
|
updatePromptStrength()
|
|
|
|
useBetaChannelField.addEventListener('click', async function(e) {
|
|
if (!isServerAvailable()) {
|
|
// logError('The server is still starting up..')
|
|
alert('The server is not available.')
|
|
e.preventDefault()
|
|
return false
|
|
}
|
|
|
|
let updateBranch = (this.checked ? 'beta' : 'main')
|
|
|
|
try {
|
|
let res = await fetch('/app_config', {
|
|
method: 'POST',
|
|
headers: {
|
|
'Content-Type': 'application/json'
|
|
},
|
|
body: JSON.stringify({
|
|
'update_branch': updateBranch
|
|
})
|
|
})
|
|
res = await res.json()
|
|
|
|
console.log('set config status response', res)
|
|
} catch (e) {
|
|
console.log('set config status error', e)
|
|
}
|
|
})
|
|
|
|
async function getAppConfig() {
|
|
try {
|
|
let res = await fetch('/get/app_config')
|
|
const config = await res.json()
|
|
|
|
if (config.update_branch === 'beta') {
|
|
useBetaChannelField.checked = true
|
|
updateBranchLabel.innerText = "(beta)"
|
|
}
|
|
|
|
console.log('get config status response', config)
|
|
} catch (e) {
|
|
console.log('get config status error', e)
|
|
}
|
|
}
|
|
|
|
async function getModels() {
|
|
try {
|
|
var model_setting_key = "stable_diffusion_model"
|
|
var selectedModel = SETTINGS[model_setting_key].value
|
|
let res = await fetch('/get/models')
|
|
const models = await res.json()
|
|
|
|
// let activeModel = models['active']
|
|
let modelOptions = models['options']
|
|
let stableDiffusionOptions = modelOptions['stable-diffusion']
|
|
|
|
stableDiffusionOptions.forEach(modelName => {
|
|
let modelOption = document.createElement('option')
|
|
modelOption.value = modelName
|
|
modelOption.innerText = modelName
|
|
|
|
if (modelName === selectedModel) {
|
|
modelOption.selected = true
|
|
}
|
|
|
|
stableDiffusionModelField.appendChild(modelOption)
|
|
})
|
|
|
|
// TODO: set default for model here too
|
|
SETTINGS[model_setting_key].default = stableDiffusionOptions[0]
|
|
if (getSetting(model_setting_key) == '' || SETTINGS[model_setting_key].value == '') {
|
|
setSetting(model_setting_key, stableDiffusionOptions[0])
|
|
}
|
|
|
|
console.log('get models response', models)
|
|
} catch (e) {
|
|
console.log('get models error', e)
|
|
}
|
|
}
|
|
|
|
function checkRandomSeed() {
|
|
if (randomSeedField.checked) {
|
|
seedField.disabled = true
|
|
seedField.value = "0"
|
|
} else {
|
|
seedField.disabled = false
|
|
}
|
|
}
|
|
randomSeedField.addEventListener('input', checkRandomSeed)
|
|
checkRandomSeed()
|
|
|
|
function showInitImagePreview() {
|
|
if (initImageSelector.files.length === 0) {
|
|
initImagePreviewContainer.style.display = 'none'
|
|
// inpaintingEditorContainer.style.display = 'none'
|
|
promptStrengthContainer.style.display = 'none'
|
|
// maskSetting.style.display = 'none'
|
|
return
|
|
}
|
|
|
|
let reader = new FileReader()
|
|
let file = initImageSelector.files[0]
|
|
|
|
reader.addEventListener('load', function(event) {
|
|
// console.log(file.name, reader.result)
|
|
initImagePreview.src = reader.result
|
|
initImagePreviewContainer.style.display = 'block'
|
|
inpaintingEditorContainer.style.display = 'none'
|
|
promptStrengthContainer.style.display = 'table-row'
|
|
samplerSelectionContainer.style.display = 'none'
|
|
// maskSetting.checked = false
|
|
})
|
|
|
|
if (file) {
|
|
reader.readAsDataURL(file)
|
|
}
|
|
}
|
|
initImageSelector.addEventListener('change', showInitImagePreview)
|
|
showInitImagePreview()
|
|
|
|
initImagePreview.addEventListener('load', function() {
|
|
inpaintingEditorCanvasBackground.style.backgroundImage = "url('" + this.src + "')"
|
|
// maskSetting.style.display = 'block'
|
|
// inpaintingEditorContainer.style.display = 'block'
|
|
initImageSizeBox.textContent = initImagePreview.naturalWidth + " x " + initImagePreview.naturalHeight
|
|
initImageSizeBox.style.display = 'block'
|
|
})
|
|
|
|
initImageClearBtn.addEventListener('click', function() {
|
|
initImageSelector.value = null
|
|
// maskImageSelector.value = null
|
|
|
|
initImagePreview.src = ''
|
|
// maskImagePreview.src = ''
|
|
maskSetting.checked = false
|
|
|
|
initImagePreviewContainer.style.display = 'none'
|
|
// inpaintingEditorContainer.style.display = 'none'
|
|
// maskImagePreviewContainer.style.display = 'none'
|
|
|
|
// maskSetting.style.display = 'none'
|
|
|
|
promptStrengthContainer.style.display = 'none'
|
|
samplerSelectionContainer.style.display = 'table-row'
|
|
initImageSizeBox.style.display = 'none'
|
|
})
|
|
|
|
maskSetting.addEventListener('click', function() {
|
|
inpaintingEditorContainer.style.display = (this.checked ? 'block' : 'none')
|
|
onDimensionChange()
|
|
})
|
|
|
|
promptsFromFileBtn.addEventListener('click', function() {
|
|
promptsFromFileSelector.click()
|
|
})
|
|
|
|
promptsFromFileSelector.addEventListener('change', function() {
|
|
if (promptsFromFileSelector.files.length === 0) {
|
|
return
|
|
}
|
|
|
|
let reader = new FileReader()
|
|
let file = promptsFromFileSelector.files[0]
|
|
|
|
reader.addEventListener('load', function() {
|
|
promptField.value = reader.result
|
|
})
|
|
|
|
if (file) {
|
|
reader.readAsText(file)
|
|
}
|
|
})
|
|
|
|
async function getDiskPath() {
|
|
try {
|
|
var diskPath = getSetting("diskPath")
|
|
if (diskPath == '' || diskPath == undefined || diskPath == "undefined") {
|
|
let res = await fetch('/get/output_dir')
|
|
if (res.status === 200) {
|
|
res = await res.json()
|
|
res = res.output_dir
|
|
|
|
setSetting("diskPath", res)
|
|
}
|
|
}
|
|
} catch (e) {
|
|
console.log('error fetching output dir path', e)
|
|
}
|
|
}
|
|
|
|
createCollapsibles() |