easydiffusion/ui/media/js/main.js
JeLuF 288e8a65f3
Incr. Server State Validtiy to 90s
By default, healthCheck() is run every 5s. On background tabs, this may get extended. My tests have shown pings every 60s. The ping was older than 10s, so the condition in line 490 evaluates to `false` and the client tries to access the stream before the server is ready. By increasing the validity this can be avoided - at least until the browser runs the healthcheck even less often.

See https://discord.com/channels/1014774730907209781/1041811939380178964/1041812021018120262 for the analysis.
2022-11-14 23:18:03 +01:00

1504 lines
53 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 MIN_GPUS_TO_SHOW_SELECTION = 2
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 autoPickGPUsField = document.querySelector('#auto_pick_gpus')
let useGPUsField = document.querySelector('#use_gpus')
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 vaeModelField = document.querySelector('#vae_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 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 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 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")
})
}
}
function setSystemInfo(devices) {
let cpu = devices.all.cpu.name
let allGPUs = Object.keys(devices.all).filter(d => d != 'cpu')
let activeGPUs = Object.keys(devices.active)
function ID_TO_TEXT(d) {
let info = devices.all[d]
if ("mem_free" in info && "mem_total" in info) {
return `${info.name} <small>(${d}) (${info.mem_free.toFixed(1)}Gb free / ${info.mem_total.toFixed(1)} Gb total)</small>`
} else {
return `${info.name} <small>(${d}) (no memory info)</small>`
}
}
allGPUs = allGPUs.map(ID_TO_TEXT)
activeGPUs = activeGPUs.map(ID_TO_TEXT)
let systemInfo = `
<table>
<tr><td><label>Processor:</label></td><td class="value">${cpu}</td></tr>
<tr><td><label>Compatible Graphics Cards (all):</label></td><td class="value">${allGPUs.join('</br>')}</td></tr>
<tr><td></td><td>&nbsp;</td></tr>
<tr><td><label>Used for rendering 🔥:</label></td><td class="value">${activeGPUs.join('</br>')}</td></tr>
</table>`
let systemInfoEl = document.querySelector('#system-info')
systemInfoEl.innerHTML = systemInfo
}
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
}
if (serverState.devices) {
setSystemInfo(serverState.devices)
}
serverState.time = Date.now()
} catch (e) {
console.log(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', 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 modifyCurrentRequest(...reqDiff) {
const newTaskRequest = getCurrentUserRequest()
newTaskRequest.reqBody = Object.assign(newTaskRequest.reqBody, ...reqDiff, {
use_cpu: useCPUField.checked
})
newTaskRequest.seed = newTaskRequest.reqBody.seed
return newTaskRequest
}
function onMakeSimilarClick(req, img) {
const newTaskRequest = modifyCurrentRequest(req, {
num_outputs: 1,
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
delete newTaskRequest.reqBody.mask
createTask(newTaskRequest)
}
function enqueueImageVariationTask(req, img, reqDiff) {
const imageSeed = img.getAttribute('data-seed')
const newTaskRequest = modifyCurrentRequest(req, reqDiff, {
num_outputs: 1, // this can be user-configurable in the future
seed: imageSeed
})
newTaskRequest.numOutputsTotal = 1 // this can be user-configurable in the future
newTaskRequest.batchCount = 1
createTask(newTaskRequest)
}
function onUpscaleClick(req, img) {
enqueueImageVariationTask(req, img, {
use_upscale: upscaleModelField.value
})
}
function onFixFacesClick(req, img) {
enqueueImageVariationTask(req, img, {
use_face_correction: 'GFPGANv1.3'
})
}
function onContinueDrawingClick(req, img) {
enqueueImageVariationTask(req, img, {
num_inference_steps: parseInt(req.num_inference_steps) + 25
})
}
// makes a single image. don't call this directly, use makeImage() instead
async function doMakeImage(task) {
if (task.stopped) {
return
}
const RETRY_DELAY_IF_BUFFER_IS_EMPTY = 1000 // ms
const RETRY_DELAY_IF_SERVER_IS_BUSY = 30 * 1000 // ms, status_code 503, already a task running
const TASK_START_DELAY_ON_SERVER = 1500 // ms
const SERVER_STATE_VALIDITY_DURATION = 90 * 1000 // ms
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']
const progressBarInner = progressBar.querySelector("div")
let res = undefined
try {
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 (res.status === 503 && await asyncDelay(RETRY_DELAY_IF_SERVER_IS_BUSY))
if (typeof renderRequest?.stream !== 'string') {
console.log('Endpoint response: ', renderRequest)
throw new Error(renderRequest?.detail || '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 (Date.now() < (serverState.time + SERVER_STATE_VALIDITY_DURATION) && serverState.task !== renderRequest.task)
switch(serverState.session) {
case 'pending':
case 'running':
case 'buffer':
// Normal expected messages.
break
case 'completed':
console.warn('Server %o render request %o completed unexpectedly', serverState, renderRequest)
break // Continue anyway to try to read cached result.
case 'error':
console.error('Server %o render request %o has failed', serverState, renderRequest)
break // Still valid, Update UI with error message
case 'stopped':
console.log('Server %o render request %o was stopped', serverState, renderRequest)
return false
default:
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(TASK_START_DELAY_ON_SERVER)
}
// 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): ${timeRemaining}`
outputMsg.style.display = 'block'
progressBarInner.style.width = `${percent}%`
if (percent == 100) {
task.progressBar.style.height = "0px"
task.progressBar.style.border = "0px solid var(--background-color3)"
task.progressBar.classList.remove("active")
}
if (stepUpdate.output !== undefined) {
showImages(reqBody, stepUpdate, outputContainer, true)
}
}
if (stepUpdate?.status) {
break
}
if (readComplete && finalJSON.length <= 0) {
if (res.status === 200) {
await asyncDelay(RETRY_DELAY_IF_BUFFER_IS_EMPTY)
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)
}
return false
}
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')
return false
}
return true
}
async function checkTasks() {
if (taskQueue.length === 0) {
setStatus('request', 'done', 'success')
setTimeout(checkTasks, 500)
stopImageBtn.style.display = 'none'
renameMakeImageButton()
currentTask = null
if (bellPending) {
if (isSoundEnabled()) {
playSound()
}
bellPending = false
}
return
}
setStatus('request', 'fetching..')
stopImageBtn.style.display = 'block'
renameMakeImageButton()
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'
task.progressBar.style.height = "0px"
task.progressBar.style.border = "0px solid var(--background-color3)"
task.progressBar.classList.remove("active")
// 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,
render_device: getCurrentRenderDeviceSelection(),
use_full_precision: useFullPrecisionField.checked,
use_stable_diffusion_model: stableDiffusionModelField.value,
use_vae_model: vaeModelField.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 getCurrentRenderDeviceSelection() {
let selectedGPUs = $('#use_gpus').val()
if (useCPUField.checked && !autoPickGPUsField.checked) {
return 'cpu'
}
if (autoPickGPUsField.checked || selectedGPUs.length == 0) {
return 'auto'
}
return selectedGPUs.join(',')
}
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 (task.reqBody.use_vae_model.trim() !== '') {
taskConfig += `, VAE: ${task.reqBody.use_vae_model}`
}
if (task.reqBody.negative_prompt.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: ${task.reqBody.use_upscale}`
}
let taskEntry = document.createElement('div')
taskEntry.className = 'imageTaskContainer'
taskEntry.innerHTML = ` <div class="header-content panel collapsible active">
<div class="taskStatusLabel">Enqueued</div>
<button class="secondaryButton stopTask"><i class="fa-solid fa-trash-can"></i> Remove</button>
<div class="preview-prompt collapsible active"></div>
<div class="taskConfig">${taskConfig}</div>
<div class="outputMsg"></div>
<div class="progress-bar active"><div></div></div>
</div>
<div class="collapsible-content">
<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('.progress-bar')
task['stopTask'] = taskEntry.querySelector('.stopTask')
task['stopTask'].addEventListener('click', async function(e) {
e.stopPropagation()
if (task['isProcessing']) {
task.isProcessing = false
task.progressBar.classList.remove("active")
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 = '&nbsp;' // 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 renameMakeImageButton() {
let totalImages = Math.max(parseInt(numOutputsTotalField.value), parseInt(numOutputsParallelField.value))
let imageLabel = 'Image'
if (totalImages > 1) {
imageLabel = totalImages + ' Images'
}
if (taskQueue.length == 0) {
makeImageBtn.innerText = 'Make ' + imageLabel
} else {
makeImageBtn.innerText = 'Enqueue Next ' + imageLabel
}
}
numOutputsTotalField.addEventListener('change', renameMakeImageButton)
numOutputsParallelField.addEventListener('change', renameMakeImageButton)
function onDimensionChange() {
if (!maskSetting.checked) {
return
}
let widthValue = parseInt(widthField.value)
let heightValue = parseInt(heightField.value)
resizeInpaintingEditor(widthValue, heightValue)
}
diskPathField.disabled = !saveToDiskField.checked
saveToDiskField.addEventListener('change', function(e) {
diskPathField.disabled = !this.checked
})
upscaleModelField.disabled = !useUpscalingField.checked
useUpscalingField.addEventListener('change', function(e) {
upscaleModelField.disabled = !this.checked
})
makeImageBtn.addEventListener('click', makeImage)
document.onkeydown = function(e) {
if (e.ctrlKey && e.code === 'Enter') {
makeImage()
e.preventDefault()
}
}
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.dispatchEvent(new Event("change"))
}
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.dispatchEvent(new Event("change"))
}
promptStrengthSlider.addEventListener('input', updatePromptStrength)
promptStrengthField.addEventListener('input', updatePromptStrengthSlider)
updatePromptStrength()
useCPUField.addEventListener('click', function() {
let gpuSettingEntry = getParameterSettingsEntry('use_gpus')
let autoPickGPUSettingEntry = getParameterSettingsEntry('auto_pick_gpus')
if (this.checked) {
gpuSettingEntry.style.display = 'none'
autoPickGPUSettingEntry.style.display = 'none'
autoPickGPUsField.setAttribute('data-old-value', autoPickGPUsField.checked)
autoPickGPUsField.checked = false
} else if (useGPUsField.options.length >= MIN_GPUS_TO_SHOW_SELECTION) {
gpuSettingEntry.style.display = ''
autoPickGPUSettingEntry.style.display = ''
let oldVal = autoPickGPUsField.getAttribute('data-old-value')
if (oldVal === null || oldVal === undefined) { // the UI started with CPU selected by default
autoPickGPUsField.checked = true
} else {
autoPickGPUsField.checked = (oldVal === 'true')
}
gpuSettingEntry.style.display = (autoPickGPUsField.checked ? 'none' : '')
}
})
useGPUsField.addEventListener('click', function() {
let selectedGPUs = $('#use_gpus').val()
autoPickGPUsField.checked = (selectedGPUs.length === 0)
})
autoPickGPUsField.addEventListener('click', function() {
if (this.checked) {
$('#use_gpus').val([])
}
let gpuSettingEntry = getParameterSettingsEntry('use_gpus')
gpuSettingEntry.style.display = (this.checked ? 'none' : '')
})
async function changeAppConfig(configDelta) {
// if (!isServerAvailable()) {
// // logError('The server is still starting up..')
// alert('The server is still starting up..')
// e.preventDefault()
// return false
// }
try {
let res = await fetch('/app_config', {
method: 'POST',
headers: {
'Content-Type': 'application/json'
},
body: JSON.stringify(configDelta)
})
res = await res.json()
console.log('set config status response', res)
} catch (e) {
console.log('set config status error', e)
}
}
useBetaChannelField.addEventListener('click', async function(e) {
let updateBranch = (this.checked ? 'beta' : 'main')
await changeAppConfig({
'update_branch': updateBranch
})
})
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 sd_model_setting_key = "stable_diffusion_model"
var vae_model_setting_key = "vae_model"
var selectedSDModel = SETTINGS[sd_model_setting_key].value
var selectedVaeModel = SETTINGS[vae_model_setting_key].value
let res = await fetch('/get/models')
const models = await res.json()
console.log('get models response', models)
let modelOptions = models['options']
let stableDiffusionOptions = modelOptions['stable-diffusion']
let vaeOptions = modelOptions['vae']
vaeOptions.unshift('') // add a None option
function createModelOptions(modelField, selectedModel) {
return function(modelName) {
let modelOption = document.createElement('option')
modelOption.value = modelName
modelOption.innerText = modelName !== '' ? modelName : 'None'
if (modelName === selectedModel) {
modelOption.selected = true
}
modelField.appendChild(modelOption)
}
}
stableDiffusionOptions.forEach(createModelOptions(stableDiffusionModelField, selectedSDModel))
vaeOptions.forEach(createModelOptions(vaeModelField, selectedVaeModel))
// TODO: set default for model here too
SETTINGS[sd_model_setting_key].default = stableDiffusionOptions[0]
if (getSetting(sd_model_setting_key) == '' || SETTINGS[sd_model_setting_key].value == '') {
setSetting(sd_model_setting_key, stableDiffusionOptions[0])
}
} 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)
}
}
async function getDevices() {
try {
let res = await fetch('/get/devices')
if (res.status === 200) {
res = await res.json()
let allDeviceIds = Object.keys(res['all']).filter(d => d !== 'cpu')
let activeDeviceIds = Object.keys(res['active']).filter(d => d !== 'cpu')
if (activeDeviceIds.length === 0) {
useCPUField.checked = true
}
if (allDeviceIds.length < MIN_GPUS_TO_SHOW_SELECTION || useCPUField.checked) {
let gpuSettingEntry = getParameterSettingsEntry('use_gpus')
gpuSettingEntry.style.display = 'none'
let autoPickGPUSettingEntry = getParameterSettingsEntry('auto_pick_gpus')
autoPickGPUSettingEntry.style.display = 'none'
}
if (allDeviceIds.length === 0) {
useCPUField.checked = true
useCPUField.disabled = true // no compatible GPUs, so make the CPU mandatory
}
autoPickGPUsField.checked = (res['config'] === 'auto')
useGPUsField.innerHTML = ''
allDeviceIds.forEach(device => {
let deviceName = res['all'][device]['name']
let deviceOption = `<option value="${device}">${deviceName} (${device})</option>`
useGPUsField.insertAdjacentHTML('beforeend', deviceOption)
})
if (autoPickGPUsField.checked) {
let gpuSettingEntry = getParameterSettingsEntry('use_gpus')
gpuSettingEntry.style.display = 'none'
} else {
$('#use_gpus').val(activeDeviceIds)
}
}
} catch (e) {
console.log('error fetching devices', e)
}
}
/* setup popup handlers */
document.querySelectorAll('.popup').forEach(popup => {
popup.addEventListener('click', event => {
if (event.target == popup) {
popup.classList.remove("active")
}
})
var closeButton = popup.querySelector(".close-button")
if (closeButton) {
closeButton.addEventListener('click', () => {
popup.classList.remove("active")
})
}
})
var tabElements = [];
document.querySelectorAll(".tab").forEach(tab => {
var name = tab.id.replace("tab-", "");
var content = document.getElementById(`tab-content-${name}`)
tabElements.push({
name: name,
tab: tab,
content: content
})
tab.addEventListener("click", event => {
if (!tab.classList.contains("active")) {
tabElements.forEach(tabInfo => {
if (tabInfo.tab.classList.contains("active")) {
tabInfo.tab.classList.toggle("active")
tabInfo.content.classList.toggle("active")
}
})
tab.classList.toggle("active")
content.classList.toggle("active")
}
})
})
window.addEventListener("beforeunload", function(e) {
const msg = "Unsaved pictures will be lost!";
let elementList = document.getElementsByClassName("imageTaskContainer");
if (elementList.length != 0) {
e.preventDefault();
(e || window.event).returnValue = msg;
return msg;
} else {
return true;
}
});
createCollapsibles()