add pix2pix
This commit is contained in:
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205170e1e5
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@ -82,6 +82,11 @@ export default async function inpaint(
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fd.append('paintByExampleImage', paintByExampleImage)
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}
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// InstructPix2Pix
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fd.append('p2pSteps', settings.p2pSteps.toString())
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fd.append('p2pImageGuidanceScale', settings.p2pImageGuidanceScale.toString())
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fd.append('p2pGuidanceScale', settings.p2pGuidanceScale.toString())
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if (sizeLimit === undefined) {
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fd.append('sizeLimit', '1080')
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} else {
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@ -41,10 +41,10 @@ import {
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croperState,
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enableFileManagerState,
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fileState,
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gifImageState,
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imageHeightState,
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imageWidthState,
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interactiveSegClicksState,
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isDiffusionModelsState,
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isInpaintingState,
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isInteractiveSegRunningState,
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isInteractiveSegState,
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@ -118,8 +118,7 @@ export default function Editor() {
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const setToastState = useSetRecoilState(toastState)
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const [isInpainting, setIsInpainting] = useRecoilState(isInpaintingState)
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const runMannually = useRecoilValue(runManuallyState)
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const isSD = useRecoilValue(isSDState)
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const isPaintByExample = useRecoilValue(isPaintByExampleState)
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const isDiffusionModels = useRecoilValue(isDiffusionModelsState)
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const [isInteractiveSeg, setIsInteractiveSeg] = useRecoilState(
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isInteractiveSegState
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)
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@ -842,7 +841,7 @@ export default function Editor() {
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}
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if (
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(isSD || isPaintByExample) &&
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isDiffusionModels &&
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settings.showCroper &&
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isOutsideCroper(mouseXY(ev))
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) {
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@ -1388,7 +1387,7 @@ export default function Editor() {
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minHeight={Math.min(256, original.naturalHeight)}
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minWidth={Math.min(256, original.naturalWidth)}
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scale={scale}
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show={(isSD || isPaintByExample) && settings.showCroper}
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show={isDiffusionModels && settings.showCroper}
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/>
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{isInteractiveSeg ? <InteractiveSeg /> : <></>}
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@ -1442,7 +1441,7 @@ export default function Editor() {
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)}
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<div className="editor-toolkit-panel">
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{isSD || isPaintByExample || file === undefined ? (
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{isDiffusionModels || file === undefined ? (
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<></>
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) : (
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<SizeSelector
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@ -1545,7 +1544,7 @@ export default function Editor() {
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onClick={download}
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/>
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{settings.runInpaintingManually && !isSD && !isPaintByExample && (
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{settings.runInpaintingManually && !isDiffusionModels && (
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<Button
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toolTip="Run Inpainting"
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icon={
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@ -7,6 +7,7 @@ import {
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enableFileManagerState,
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fileState,
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isInpaintingState,
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isPix2PixState,
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isSDState,
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maskState,
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runManuallyState,
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@ -30,6 +31,7 @@ const Header = () => {
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const [uploadElemId] = useState(`file-upload-${Math.random().toString()}`)
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const [maskUploadElemId] = useState(`mask-upload-${Math.random().toString()}`)
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const isSD = useRecoilValue(isSDState)
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const isPix2Pix = useRecoilValue(isPix2PixState)
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const runManually = useRecoilValue(runManuallyState)
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const [openMaskPopover, setOpenMaskPopover] = useState(false)
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const [showFileManager, setShowFileManager] =
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@ -172,7 +174,7 @@ const Header = () => {
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</div>
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</div>
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{isSD && file ? <PromptInput /> : <></>}
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{(isSD || isPix2Pix) && file ? <PromptInput /> : <></>}
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<div className="header-icons-wrapper">
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<CoffeeIcon />
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@ -179,28 +179,16 @@ function ModelSettingBlock() {
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const renderOptionDesc = (): ReactNode => {
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switch (setting.model) {
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case AIModel.LAMA:
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return undefined
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case AIModel.LDM:
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return renderLDMModelDesc()
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case AIModel.ZITS:
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return renderZITSModelDesc()
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case AIModel.MAT:
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return undefined
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case AIModel.FCF:
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return renderFCFModelDesc()
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case AIModel.SD15:
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return undefined
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case AIModel.SD2:
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return undefined
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case AIModel.PAINT_BY_EXAMPLE:
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return undefined
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case AIModel.Mange:
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return undefined
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case AIModel.CV2:
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return renderOpenCV2Desc()
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default:
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return <></>
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return undefined
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}
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}
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@ -266,6 +254,12 @@ function ModelSettingBlock() {
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'https://arxiv.org/abs/2211.13227',
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'https://github.com/Fantasy-Studio/Paint-by-Example'
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)
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case AIModel.PIX2PIX:
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return renderModelDesc(
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'InstructPix2Pix',
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'https://arxiv.org/abs/2211.09800',
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'https://github.com/timothybrooks/instruct-pix2pix'
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)
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default:
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return <></>
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}
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@ -1,6 +1,7 @@
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import React from 'react'
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import { useRecoilState, useRecoilValue } from 'recoil'
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import {
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isDiffusionModelsState,
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isPaintByExampleState,
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isSDState,
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settingState,
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@ -28,7 +29,7 @@ export default function SettingModal(props: SettingModalProps) {
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const { onClose } = props
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const [setting, setSettingState] = useRecoilState(settingState)
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const isSD = useRecoilValue(isSDState)
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const isPaintByExample = useRecoilValue(isPaintByExampleState)
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const isDiffusionModels = useRecoilValue(isDiffusionModelsState)
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const handleOnClose = () => {
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setSettingState(old => {
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@ -56,9 +57,9 @@ export default function SettingModal(props: SettingModalProps) {
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show={setting.show}
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>
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<DownloadMaskSettingBlock />
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{isSD || isPaintByExample ? <></> : <ManualRunInpaintingSettingBlock />}
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{isDiffusionModels ? <></> : <ManualRunInpaintingSettingBlock />}
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<ModelSettingBlock />
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{isSD ? <></> : <HDSettingBlock />}
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{isDiffusionModels ? <></> : <HDSettingBlock />}
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</Modal>
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)
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}
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224
lama_cleaner/app/src/components/SidePanel/P2PSidePanel.tsx
Normal file
224
lama_cleaner/app/src/components/SidePanel/P2PSidePanel.tsx
Normal file
@ -0,0 +1,224 @@
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import React, { FormEvent } from 'react'
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import { useRecoilState, useRecoilValue } from 'recoil'
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import * as PopoverPrimitive from '@radix-ui/react-popover'
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import { useToggle } from 'react-use'
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import {
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isInpaintingState,
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negativePropmtState,
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propmtState,
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settingState,
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} from '../../store/Atoms'
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import NumberInputSetting from '../Settings/NumberInputSetting'
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import SettingBlock from '../Settings/SettingBlock'
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import { Switch, SwitchThumb } from '../shared/Switch'
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import TextAreaInput from '../shared/Textarea'
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import emitter, { EVENT_PROMPT } from '../../event'
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import ImageResizeScale from './ImageResizeScale'
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const INPUT_WIDTH = 30
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const P2PSidePanel = () => {
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const [open, toggleOpen] = useToggle(true)
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const [setting, setSettingState] = useRecoilState(settingState)
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const [negativePrompt, setNegativePrompt] =
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useRecoilState(negativePropmtState)
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const isInpainting = useRecoilValue(isInpaintingState)
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const prompt = useRecoilValue(propmtState)
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const handleOnInput = (evt: FormEvent<HTMLTextAreaElement>) => {
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evt.preventDefault()
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evt.stopPropagation()
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const target = evt.target as HTMLTextAreaElement
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setNegativePrompt(target.value)
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}
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const onKeyUp = (e: React.KeyboardEvent) => {
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if (
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e.key === 'Enter' &&
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(e.ctrlKey || e.metaKey) &&
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prompt.length !== 0 &&
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!isInpainting
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) {
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emitter.emit(EVENT_PROMPT)
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}
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}
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return (
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<div className="side-panel">
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<PopoverPrimitive.Root open={open}>
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<PopoverPrimitive.Trigger
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className="btn-primary side-panel-trigger"
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onClick={() => toggleOpen()}
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>
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Config
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</PopoverPrimitive.Trigger>
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<PopoverPrimitive.Portal>
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<PopoverPrimitive.Content className="side-panel-content">
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<SettingBlock
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title="Croper"
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input={
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<Switch
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checked={setting.showCroper}
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onCheckedChange={value => {
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setSettingState(old => {
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return { ...old, showCroper: value }
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})
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}}
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>
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<SwitchThumb />
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</Switch>
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}
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/>
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<ImageResizeScale />
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<NumberInputSetting
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title="Steps"
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width={INPUT_WIDTH}
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value={`${setting.p2pSteps}`}
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desc="The number of denoising steps. More denoising steps usually lead to a higher quality image at the expense of slower inference."
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onValue={value => {
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const val = value.length === 0 ? 0 : parseInt(value, 10)
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setSettingState(old => {
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return { ...old, p2pSteps: val }
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})
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}}
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/>
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<NumberInputSetting
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title="Guidance Scale"
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width={INPUT_WIDTH}
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allowFloat
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value={`${setting.p2pGuidanceScale}`}
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desc="Higher guidance scale encourages to generate images that are closely linked to the text prompt, usually at the expense of lower image quality."
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onValue={value => {
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const val = value.length === 0 ? 0 : parseFloat(value)
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setSettingState(old => {
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return { ...old, p2pGuidanceScale: val }
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})
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}}
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/>
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<NumberInputSetting
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title="Image Guidance Scale"
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width={INPUT_WIDTH}
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allowFloat
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value={`${setting.p2pImageGuidanceScale}`}
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desc=""
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onValue={value => {
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const val = value.length === 0 ? 0 : parseFloat(value)
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setSettingState(old => {
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return { ...old, p2pImageGuidanceScale: val }
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})
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}}
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/>
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{/* <NumberInputSetting
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title="Mask Blur"
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width={INPUT_WIDTH}
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value={`${setting.sdMaskBlur}`}
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desc="Blur the edge of mask area. The higher the number the smoother blend with the original image"
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onValue={value => {
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const val = value.length === 0 ? 0 : parseInt(value, 10)
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setSettingState(old => {
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return { ...old, sdMaskBlur: val }
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})
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}}
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/> */}
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{/* <SettingBlock
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title="Match Histograms"
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desc="Match the inpainting result histogram to the source image histogram, will improves the inpainting quality for some images."
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input={
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<Switch
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checked={setting.sdMatchHistograms}
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onCheckedChange={value => {
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setSettingState(old => {
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return { ...old, sdMatchHistograms: value }
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})
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}}
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>
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<SwitchThumb />
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</Switch>
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}
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/> */}
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{/* <SettingBlock
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className="sub-setting-block"
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title="Sampler"
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input={
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<Selector
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width={80}
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value={setting.sdSampler as string}
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options={Object.values(SDSampler)}
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onChange={val => {
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const sampler = val as SDSampler
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setSettingState(old => {
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return { ...old, sdSampler: sampler }
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})
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}}
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/>
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}
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/> */}
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<SettingBlock
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title="Seed"
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input={
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<div
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style={{
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display: 'flex',
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gap: 0,
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justifyContent: 'center',
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alignItems: 'center',
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}}
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>
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<NumberInputSetting
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title=""
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width={80}
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value={`${setting.sdSeed}`}
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desc=""
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disable={!setting.sdSeedFixed}
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onValue={value => {
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const val = value.length === 0 ? 0 : parseInt(value, 10)
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setSettingState(old => {
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return { ...old, sdSeed: val }
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})
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}}
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/>
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<Switch
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checked={setting.sdSeedFixed}
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onCheckedChange={value => {
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setSettingState(old => {
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return { ...old, sdSeedFixed: value }
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})
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}}
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style={{ marginLeft: '8px' }}
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>
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<SwitchThumb />
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</Switch>
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</div>
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}
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/>
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<SettingBlock
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className="sub-setting-block"
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title="Negative prompt"
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layout="v"
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input={
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<TextAreaInput
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className="negative-prompt"
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value={negativePrompt}
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onInput={handleOnInput}
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onKeyUp={onKeyUp}
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placeholder=""
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/>
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}
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/>
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</PopoverPrimitive.Content>
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</PopoverPrimitive.Portal>
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</PopoverPrimitive.Root>
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</div>
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)
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}
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export default P2PSidePanel
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@ -8,6 +8,7 @@ import {
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AIModel,
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fileState,
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isPaintByExampleState,
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isPix2PixState,
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isSDState,
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settingState,
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showFileManagerState,
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@ -22,6 +23,7 @@ import {
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import SidePanel from './SidePanel/SidePanel'
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import PESidePanel from './SidePanel/PESidePanel'
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import FileManager from './FileManager/FileManager'
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import P2PSidePanel from './SidePanel/P2PSidePanel'
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const Workspace = () => {
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const setFile = useSetRecoilState(fileState)
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@ -29,6 +31,7 @@ const Workspace = () => {
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const [toastVal, setToastState] = useRecoilState(toastState)
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const isSD = useRecoilValue(isSDState)
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const isPaintByExample = useRecoilValue(isPaintByExampleState)
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const isPix2Pix = useRecoilValue(isPix2PixState)
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const [showFileManager, setShowFileManager] =
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useRecoilState(showFileManagerState)
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@ -98,6 +101,7 @@ const Workspace = () => {
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<>
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{isSD ? <SidePanel /> : <></>}
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{isPaintByExample ? <PESidePanel /> : <></>}
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{isPix2Pix ? <P2PSidePanel /> : <></>}
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<FileManager
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photoWidth={256}
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show={showFileManager}
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@ -14,6 +14,7 @@ export enum AIModel {
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CV2 = 'cv2',
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Mange = 'manga',
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PAINT_BY_EXAMPLE = 'paint_by_example',
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PIX2PIX = 'pix2pix',
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}
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export const maskState = atom<File | undefined>({
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@ -343,6 +344,11 @@ export interface Settings {
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paintByExampleSeedFixed: boolean
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paintByExampleMaskBlur: number
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paintByExampleMatchHistograms: boolean
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// InstructPix2Pix
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p2pSteps: number
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p2pImageGuidanceScale: number
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p2pGuidanceScale: number
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}
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const defaultHDSettings: ModelsHDSettings = {
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@ -402,6 +408,13 @@ const defaultHDSettings: ModelsHDSettings = {
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hdStrategyCropMargin: 128,
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enabled: false,
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},
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[AIModel.PIX2PIX]: {
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hdStrategy: HDStrategy.ORIGINAL,
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hdStrategyResizeLimit: 768,
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hdStrategyCropTrigerSize: 512,
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hdStrategyCropMargin: 128,
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enabled: false,
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},
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[AIModel.Mange]: {
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hdStrategy: HDStrategy.CROP,
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hdStrategyResizeLimit: 1280,
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@ -471,6 +484,11 @@ export const settingStateDefault: Settings = {
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paintByExampleMaskBlur: 5,
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paintByExampleSeedFixed: false,
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paintByExampleMatchHistograms: false,
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// InstructPix2Pix
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p2pSteps: 50,
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p2pImageGuidanceScale: 1.5,
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p2pGuidanceScale: 7.5,
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}
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const localStorageEffect =
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@ -567,12 +585,33 @@ export const isPaintByExampleState = selector({
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},
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})
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export const isPix2PixState = selector({
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key: 'isPix2PixState',
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get: ({ get }) => {
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const settings = get(settingState)
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return settings.model === AIModel.PIX2PIX
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},
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})
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export const runManuallyState = selector({
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key: 'runManuallyState',
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get: ({ get }) => {
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const settings = get(settingState)
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const isSD = get(isSDState)
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const isPaintByExample = get(isPaintByExampleState)
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return settings.runInpaintingManually || isSD || isPaintByExample
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const isPix2Pix = get(isPix2PixState)
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return (
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settings.runInpaintingManually || isSD || isPaintByExample || isPix2Pix
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)
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},
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||||
})
|
||||
|
||||
export const isDiffusionModelsState = selector({
|
||||
key: 'isDiffusionModelsState',
|
||||
get: ({ get }) => {
|
||||
const isSD = get(isSDState)
|
||||
const isPaintByExample = get(isPaintByExampleState)
|
||||
const isPix2Pix = get(isPix2PixState)
|
||||
return isSD || isPaintByExample || isPix2Pix
|
||||
},
|
||||
})
|
||||
|
@ -11,7 +11,8 @@ AVAILABLE_MODELS = [
|
||||
"cv2",
|
||||
"manga",
|
||||
"sd2",
|
||||
"paint_by_example"
|
||||
"paint_by_example",
|
||||
"pix2pix",
|
||||
]
|
||||
|
||||
AVAILABLE_DEVICES = ["cuda", "cpu", "mps"]
|
||||
|
83
lama_cleaner/model/pix2pix.py
Normal file
83
lama_cleaner/model/pix2pix.py
Normal file
@ -0,0 +1,83 @@
|
||||
import PIL.Image
|
||||
import cv2
|
||||
import torch
|
||||
from loguru import logger
|
||||
|
||||
from lama_cleaner.model.base import DiffusionInpaintModel
|
||||
from lama_cleaner.model.utils import set_seed
|
||||
from lama_cleaner.schema import Config
|
||||
|
||||
|
||||
class Pix2Pix(DiffusionInpaintModel):
|
||||
pad_mod = 8
|
||||
min_size = 512
|
||||
|
||||
def init_model(self, device: torch.device, **kwargs):
|
||||
from diffusers import StableDiffusionInstructPix2PixPipeline
|
||||
fp16 = not kwargs.get('no_half', False)
|
||||
|
||||
model_kwargs = {"local_files_only": kwargs.get('local_files_only', kwargs['sd_run_local'])}
|
||||
if kwargs['disable_nsfw'] or kwargs.get('cpu_offload', False):
|
||||
logger.info("Disable Stable Diffusion Model NSFW checker")
|
||||
model_kwargs.update(dict(
|
||||
safety_checker=None,
|
||||
feature_extractor=None,
|
||||
requires_safety_checker=False
|
||||
))
|
||||
|
||||
use_gpu = device == torch.device('cuda') and torch.cuda.is_available()
|
||||
torch_dtype = torch.float16 if use_gpu and fp16 else torch.float32
|
||||
self.model = StableDiffusionInstructPix2PixPipeline.from_pretrained(
|
||||
"timbrooks/instruct-pix2pix",
|
||||
revision="fp16" if use_gpu and fp16 else "main",
|
||||
torch_dtype=torch_dtype,
|
||||
**model_kwargs
|
||||
)
|
||||
|
||||
self.model.enable_attention_slicing()
|
||||
if kwargs.get('enable_xformers', False):
|
||||
self.model.enable_xformers_memory_efficient_attention()
|
||||
|
||||
if kwargs.get('cpu_offload', False) and use_gpu:
|
||||
logger.info("Enable sequential cpu offload")
|
||||
self.model.enable_sequential_cpu_offload(gpu_id=0)
|
||||
else:
|
||||
self.model = self.model.to(device)
|
||||
|
||||
def forward(self, image, mask, config: Config):
|
||||
"""Input image and output image have same size
|
||||
image: [H, W, C] RGB
|
||||
mask: [H, W, 1] 255 means area to repaint
|
||||
return: BGR IMAGE
|
||||
edit = pipe(prompt, image=image, num_inference_steps=20, image_guidance_scale=1.5, guidance_scale=7).images[0]
|
||||
"""
|
||||
set_seed(config.sd_seed)
|
||||
|
||||
output = self.model(
|
||||
image=PIL.Image.fromarray(image),
|
||||
prompt=config.prompt,
|
||||
negative_prompt=config.negative_prompt,
|
||||
num_inference_steps=config.p2p_steps,
|
||||
image_guidance_scale=config.p2p_image_guidance_scale,
|
||||
guidance_scale=config.p2p_guidance_scale,
|
||||
output_type="np.array",
|
||||
).images[0]
|
||||
|
||||
output = (output * 255).round().astype("uint8")
|
||||
output = cv2.cvtColor(output, cv2.COLOR_RGB2BGR)
|
||||
return output
|
||||
|
||||
#
|
||||
# def forward_post_process(self, result, image, mask, config):
|
||||
# if config.sd_match_histograms:
|
||||
# result = self._match_histograms(result, image[:, :, ::-1], mask)
|
||||
#
|
||||
# if config.sd_mask_blur != 0:
|
||||
# k = 2 * config.sd_mask_blur + 1
|
||||
# mask = cv2.GaussianBlur(mask, (k, k), 0)
|
||||
# return result, image, mask
|
||||
|
||||
@staticmethod
|
||||
def is_downloaded() -> bool:
|
||||
# model will be downloaded when app start, and can't switch in frontend settings
|
||||
return True
|
@ -7,13 +7,14 @@ from lama_cleaner.model.ldm import LDM
|
||||
from lama_cleaner.model.manga import Manga
|
||||
from lama_cleaner.model.mat import MAT
|
||||
from lama_cleaner.model.paint_by_example import PaintByExample
|
||||
from lama_cleaner.model.pix2pix import Pix2Pix
|
||||
from lama_cleaner.model.sd import SD15, SD2
|
||||
from lama_cleaner.model.zits import ZITS
|
||||
from lama_cleaner.model.opencv2 import OpenCV2
|
||||
from lama_cleaner.schema import Config
|
||||
|
||||
models = {"lama": LaMa, "ldm": LDM, "zits": ZITS, "mat": MAT, "fcf": FcF, "sd1.5": SD15, "cv2": OpenCV2, "manga": Manga,
|
||||
"sd2": SD2, "paint_by_example": PaintByExample}
|
||||
"sd2": SD2, "paint_by_example": PaintByExample, "pix2pix": Pix2Pix}
|
||||
|
||||
|
||||
class ModelManager:
|
||||
|
@ -88,3 +88,8 @@ class Config(BaseModel):
|
||||
paint_by_example_seed: int = 42
|
||||
paint_by_example_match_histograms: bool = False
|
||||
paint_by_example_example_image: Image = None
|
||||
|
||||
# InstructPix2Pix
|
||||
p2p_steps: int = 50
|
||||
p2p_image_guidance_scale: float = 1.5
|
||||
p2p_guidance_scale: float = 7.5
|
||||
|
@ -228,6 +228,9 @@ def process():
|
||||
paint_by_example_seed=form["paintByExampleSeed"],
|
||||
paint_by_example_match_histograms=form["paintByExampleMatchHistograms"],
|
||||
paint_by_example_example_image=paint_by_example_example_image,
|
||||
p2p_steps=form["p2pSteps"],
|
||||
p2p_image_guidance_scale=form["p2pImageGuidanceScale"],
|
||||
p2p_guidance_scale=form["p2pGuidanceScale"],
|
||||
)
|
||||
|
||||
if config.sd_seed == -1:
|
||||
|
@ -11,7 +11,7 @@ pytest
|
||||
yacs
|
||||
markupsafe==2.0.1
|
||||
scikit-image==0.19.3
|
||||
diffusers[torch]==0.10.2
|
||||
diffusers[torch]==0.12.1
|
||||
transformers>=4.25.1
|
||||
watchdog==2.2.1
|
||||
gradio
|
Loading…
Reference in New Issue
Block a user