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API za uklanjanje pozadine za developere

Integrirajte naprednu AI tehnologiju uklanjanja pozadine u svoje aplikacije s našim robusnim i fleksibilnim API-jem.

Nabavite API ključ

Jednostavna integracija

Implementirajte uklanjanje pozadine u svojoj aplikaciji sa samo nekoliko linija koda. Naš dobro dokumentiran API i SDK-ovi za popularne jezike čine integraciju laganom.

Prilagođeni izlaz za raznolike aplikacije

Prilagodite proces uklanjanja pozadine svojim potrebama. Prilagodite parametre, izvezite u različitim formatima, pa čak i zamijenite pozadine programski.

Performanse razine poduzeća

Izgrađeno za skaliranje i brzinu. Naš API obrađuje milijune zahtjeva dnevno s niskom latencijom, osiguravajući da vaše aplikacije ostanu odzivne čak i pod velikim opterećenjem.

Otključajte nove značajke u svojim aplikacijama

Osnažite svoje korisnike naprednim mogućnostima uređivanja slika. Od e-trgovinskih platformi do aplikacija društvenih medija, mogućnosti su beskrajne s našim API-jem za uklanjanje pozadine.

Preporučeni alati za programere

Kako je mali developerski tim isporučio funkciju za isijecanje profilnih fotografija u jednom sprintu

Četveročlani developerski tim koji gradi hobby marketplace aplikaciju trebao je funkciju profilne fotografije koja telefonsku fotografiju korisnika pretvara u čist avatar bez pozivanja vanjskog provajdera za uređivanje fotografija ili servera.

Tim je uključio editorov in-browser isječak u postojeći tok učitavanja kao klijent-side korak. Korisnik bira fotografiju, model se izvršava u JavaScript-u, isječak se pojavljuje za nekoliko sekundi, a finalni PNG se učitava direktno u njihov S3 bucket. Bez API troškova, bez serverskog skaliranja, bez problema sa privatnošću.

Funkcija je puštena na kraju sprinta, obradila je 14.000 avatara u prvom mjesecu bez dodatnih infrastrukturnih troškova. Račun za infrastrukturu tima je čak malo opao jer više nisu plaćali third-party API po učitavanju.

"We needed an avatar cropper that didn't add a server-side service or a paid API. Wiring the in-browser cutout into our upload flow took one sprint and shipped at zero marginal cost per user. The platform team noticed our request graph didn't change."
Glavni inženjer Hobby-marketplace iOS app
"I'm the only engineer and I needed a profile-photo step that didn't pull in a third-party SDK we'd have to babysit forever. A client-side cutout meant I shipped the feature, then forgot about it. No keys to rotate, no rate limits, no support tickets six months later."
Osnivač, B2C aplikacija Two-person team, B2B niche
"Bundling a heavyweight SDK into a starter template makes the whole project feel bloated. The browser-side approach means contributors can fork the template and not need to set up a third-party account. Adoption of the photo step is up since I switched."
Full-stack developer Headless commerce starter

Picks that fit a developer workflow

Common questions for developers

Is there a stable API for the in-browser cutout, or do I need to embed the editor iframe?

The editor exposes a small JavaScript surface that you can call from your own page once the model is loaded. The cutout returns a Blob you own, so you can pipe it directly to your existing upload pipeline. The model loader handles caching across sessions via the Cache API, so the second visit is fast. There is no iframe required and no postMessage handshake, the function is invokable like any other client-side image operation.

What's the cold-start cost of the model on a first-time visitor?

First-load fetches the WASM runtime and the model weights, which together are roughly 30 MB on the wire. A modern broadband connection gets that in two or three seconds; a slow mobile network closer to ten. Subsequent visits hit the Cache API and start instantly. For latency-sensitive apps, a preload hint in the HTML head warms the cache before the user reaches the photo step. Server-assisted fallback is available for devices that can't run the model locally.

Are there usage limits or quotas if I integrate this into a commercial product?

The browser-side pipeline runs on the user's device, so there is no per-request quota and no rate limit to negotiate. Server-assisted fallback for the rare device that cannot run the model locally has its own quota documented separately. For high-volume commercial integrations the recommendation is to handle the local-cutout path as the default and surface server fallback only on capability detection failure, which keeps cost predictable as you scale.

Ship a photo feature without adding a service

Wire the in-browser cutout into your existing upload component, keep the file on the user's device, and pipe the result straight to your storage.

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