feat: make AI background removal optional with resize-only upload and batch detour selection

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
2026-06-25 08:21:46 +02:00
parent c95093a81f
commit eec9bd5dce
5 changed files with 184 additions and 57 deletions
+67 -40
View File
@@ -59,7 +59,6 @@ function blobToBase64(blob: Blob): Promise<string> {
const reader = new FileReader()
reader.onload = () => {
const result = reader.result as string
// Supprimer le préfixe "data:image/jpeg;base64,"
const base64 = result.split(',')[1]
resolve(base64)
}
@@ -83,24 +82,21 @@ export function useImages() {
async (id: string, ref: string) => {
update(id, { status: 'searching' })
try {
// 1. Cherche d'abord dans Google Sheets (col C = UGS → col A = Shopify ID)
const sheetsRes = await fetch(`/api/products/search-sheets?ref=${encodeURIComponent(ref)}`)
const sheetsData = await sheetsRes.json()
if (sheetsData.found) {
update(id, {
status: 'ready',
status: 'converted',
shopifyProductId: sheetsData.shopifyId,
shopifyProductTitle: sheetsData.title,
})
return
}
// 2. Fallback : recherche directe dans Shopify par handle/titre
const res = await fetch(`/api/products/search?ref=${encodeURIComponent(ref)}`)
const data = await res.json()
if (data.found) {
update(id, {
status: 'ready',
status: 'converted',
shopifyProductId: data.shopifyId,
shopifyProductTitle: data.title,
})
@@ -114,31 +110,40 @@ export function useImages() {
[update],
)
// Pipeline complet pour un item (avec ref)
const runPipeline = useCallback(
async (id: string, blob: Blob, ref: string, feather: number, rotation: number, alphaThreshold: number) => {
// Pipeline léger : conversion HEIC + recherche produit (sans détourage IA)
const runConvertAndSearch = useCallback(
async (id: string, blob: Blob, ref: string) => {
const { convertHeicToJpeg } = await import('@/lib/client/heicConverter')
const { removeBackgroundRaw, compositeOnWhite } = await import('@/lib/client/bgRemover')
const { rotateBlob } = await import('@/lib/client/imageRotator')
let jpegBlob = blob
if (blob.type === 'image/heic' || blob.type === 'image/heif' || blob.type === '') {
try {
update(id, { status: 'converting' })
jpegBlob = await convertHeicToJpeg(blob)
// Met à jour originalBlob avec le JPEG converti (Chrome ne peut pas afficher HEIC)
update(id, { originalBlob: jpegBlob })
} catch (err) {
update(id, { status: 'error', error: `Conversion HEIC : ${(err as Error).message}` })
return
}
} else {
update(id, { status: 'searching' })
}
await searchProduct(id, ref)
},
[update, searchProduct],
)
// Pipeline IA complet : détourage + composite + rotation
const runBgRemoval = useCallback(
async (id: string, blob: Blob, feather: number, rotation: number, alphaThreshold: number) => {
const { removeBackgroundRaw, compositeOnWhite } = await import('@/lib/client/bgRemover')
const { rotateBlob } = await import('@/lib/client/imageRotator')
let rawPng: Blob
try {
update(id, { status: 'processing', progress: null })
rawPng = await removeBackgroundRaw(jpegBlob, (p) => update(id, { progress: p }))
rawPng = await removeBackgroundRaw(blob, (p) => update(id, { progress: p }))
} catch (err) {
update(id, { status: 'error', error: `Détourage IA : ${(err as Error).message}` })
return
@@ -153,10 +158,9 @@ export function useImages() {
return
}
update(id, { rawPngBlob: rawPng, processedBlob: finalBlob })
await searchProduct(id, ref)
update(id, { rawPngBlob: rawPng, processedBlob: finalBlob, status: 'ready' })
},
[update, searchProduct],
[update],
)
// Recomposite rapide (feather, alphaThreshold ou rotation changés) — ne relance pas l'IA
@@ -201,15 +205,13 @@ export function useImages() {
error: null,
progress: null,
}))
// Recalcule la ref depuis le nom du fichier (plus fiable que le nom du dossier ZIP)
// item.filename = "DOSSIER/32263-.heic" → on prend la partie après le dernier "/"
const itemsWithRef = newItems.map(item => {
const basename = item.filename.split('/').pop() ?? item.filename
return { ...item, ref: refFromFilename(basename) }
})
dispatch({ type: 'ADD', items: itemsWithRef })
for (const item of itemsWithRef) {
queueRef.current.enqueue(() => runPipeline(item.id, item.originalBlob, item.ref, item.feather, item.rotation, item.alphaThreshold))
queueRef.current.enqueue(() => runConvertAndSearch(item.id, item.originalBlob, item.ref))
}
} else {
const ref = refFromFilename(file.name)
@@ -231,11 +233,35 @@ export function useImages() {
progress: null,
}
dispatch({ type: 'ADD', items: [newItem] })
queueRef.current.enqueue(() => runPipeline(newItem.id, newItem.originalBlob, newItem.ref, newItem.feather, newItem.rotation, newItem.alphaThreshold))
queueRef.current.enqueue(() => runConvertAndSearch(newItem.id, newItem.originalBlob, newItem.ref))
}
}
},
[runPipeline],
[runConvertAndSearch],
)
// Lancer le détourage IA sur une image (depuis statut converted ou error)
const detour = useCallback(
(id: string) => {
const item = items.find((i) => i.id === id)
if (!item) return
queueRef.current.enqueue(() =>
runBgRemoval(item.id, item.originalBlob, item.feather, item.rotation, item.alphaThreshold)
)
},
[items, runBgRemoval],
)
// Relancer le pipeline complet (conversion + détourage) sur une image déjà traitée
const reprocess = useCallback(
(id: string) => {
const item = items.find((i) => i.id === id)
if (!item) return
queueRef.current.enqueue(() =>
runBgRemoval(item.id, item.originalBlob, item.feather, item.rotation, item.alphaThreshold)
)
},
[items, runBgRemoval],
)
const setFeather = useCallback(
@@ -270,12 +296,23 @@ export function useImages() {
const uploadOne = useCallback(
async (id: string) => {
const item = items.find((i) => i.id === id)
if (!item || item.status !== 'ready' || !item.processedBlob || !item.shopifyProductId) return
if (!item) return
const canUpload = item.status === 'ready' || item.status === 'converted'
if (!canUpload || !item.shopifyProductId) return
update(id, { status: 'uploading' })
try {
const base64 = await blobToBase64(item.processedBlob)
// Si détouré : utilise processedBlob ; sinon : redimensionne à 1000×1000
let uploadBlob: Blob
if (item.processedBlob) {
uploadBlob = item.processedBlob
} else {
const { resizeToSquare } = await import('@/lib/client/imageResizer')
uploadBlob = await resizeToSquare(item.originalBlob)
}
const base64 = await blobToBase64(uploadBlob)
const basename = item.filename.split('/').pop()?.replace(/\.[^.]+$/, '') ?? item.ref
const filename = `${basename}.jpg`
@@ -288,7 +325,7 @@ export function useImages() {
let res = await doUpload(item.shopifyProductId)
// 404 = ID périmé (produit supprimé/recréé) → relancer la recherche par ref
// 404 = ID périmé → relancer la recherche par ref
if (res.status === 404) {
const searchRes = await fetch(`/api/products/search?ref=${encodeURIComponent(item.ref)}`)
const searchData = await searchRes.json()
@@ -309,10 +346,9 @@ export function useImages() {
)
const uploadAll = useCallback(async () => {
const ready = items.filter((i) => i.status === 'ready')
const ready = items.filter((i) => i.status === 'ready' || i.status === 'converted')
for (const item of ready) {
await uploadOne(item.id)
// Pause de 500ms entre chaque upload pour éviter le rate limit Shopify
await new Promise(r => setTimeout(r, 500))
}
}, [items, uploadOne])
@@ -323,21 +359,12 @@ export function useImages() {
const assignProduct = useCallback(
(id: string, shopifyProductId: string, shopifyProductTitle: string) => {
update(id, { shopifyProductId, shopifyProductTitle, status: 'ready' })
},
[update],
)
const reprocess = useCallback(
(id: string) => {
const item = items.find((i) => i.id === id)
if (!item) return
queueRef.current.enqueue(() =>
runPipeline(item.id, item.originalBlob, item.ref, item.feather, item.rotation, item.alphaThreshold)
)
const newStatus = item?.processedBlob ? 'ready' : 'converted'
update(id, { shopifyProductId, shopifyProductTitle, status: newStatus })
},
[items, runPipeline],
[items, update],
)
return { items, addFiles, setFeather, setAlphaThreshold, rotate, uploadOne, uploadAll, removeItem, assignProduct, reprocess }
return { items, addFiles, setFeather, setAlphaThreshold, rotate, uploadOne, uploadAll, removeItem, assignProduct, reprocess, detour }
}