BiRefNet V2 Background Removal
Integreren
birefnet/v2
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/birefnet/v2?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"image": "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/birefnet/v2?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"image": "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/birefnet/v2", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
# 1. Connect once (Claude Code; Cursor, VS Code, Claude Desktop: https://doitong.com/nl/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.com/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "birefnet/v2",
"input": {
"image": "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
}
}
Roep het BiRefNet V2 Background Removal-model (birefnet/v2) aan via de Doitong API. Documentatie voor agents: https://doitong.com/nl/developers/models/birefnet/v2.md
POST https://api.doitong.com/v1/run/birefnet/v2?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"image": "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
}
Als de responsstatus "queued" of "running" is, poll dan GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 totdat deze "succeeded" is; de bestanden staan in outputs[].url. POST https://api.doitong.com/v1/quote/birefnet/v2 met dezelfde body retourneert de exacte prijs vóór de uitvoering.
Deze request: ≈$ 0,002 2 API-tegoed Op deze pagina uitvoeren
Je nieuwe API-sleutel. Deze wordt alleen nu getoond en staat al in de code en in het onderstaande API-sleutelveld. Houd deze geheim: zet deze nooit in code die in een browser wordt uitgevoerd.
Je eerste resultaat komt hier
Bouw hieronder een request en voer die uit met je API-sleutel. Uitvoer wordt naar onze opslag gekopieerd en voor altijd of 7 dagen gratis bewaard.
Een aanvraag samenstellen
Besturingselementen worden gegenereerd op basis van het modelschema. De code en de prijs worden bijgewerkt terwijl je ze wijzigt.
/run/birefnet/v2?wait=20
prijsopgave → $ 0,002
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/birefnet/v2?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"image": "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/birefnet/v2?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"image": "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/birefnet/v2", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "run",
"arguments": {
"model_id": "birefnet/v2",
"input": {
"image": "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
},
"wait_seconds": 20
}
}
}
Deze request uitvoeren
Je sleutel blijft in deze browser: hij wordt alleen naar de Doitong API verzonden en alleen in localStorage opgeslagen als je Onthouden aanvinkt. API-sleutel ophalen
Over BiRefNet V2 Background Removal
BiRefNet V2 scheidt het onderwerp van de achtergrond met meerdere modelvarianten (light, heavy, matting, portrait, dynamic) en werkresoluties tot 2304x2304. Retourneert de vrijstaande uitsnede en optioneel het masker in PNG, WebP of GIF.
Parameters
Stuur de canonieke naam of de oorspronkelijke naam, niet beide. Canonieke namen
modeloptioneel
operating_resolutionoptioneel
output_maskoptioneel
refine_foregroundoptioneel
image_urlverplicht
image
output_formatoptioneel
mask_onlyoptioneel
Bestandsparameters accepteren een openbare https:// URL, een data: URI tot 10 MB of de file_url van een upload. Bestanden
Uitvoer
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "birefnet/v2",
"status": "succeeded",
"created_at": "2026-10-20T12:00:00Z",
"started_at": "2026-10-20T12:00:02Z",
"completed_at": "2026-10-20T12:00:09Z",
"queue_position": null,
"cost": {
"credits": 2,
"usd": "0.002",
"charged": 2,
"refunded": 0
},
"input": {
"image": "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
},
"output": {
"image": {
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_name": "0-output.jpeg",
"file_size": 1843200,
"width": 1024,
"height": 768
},
"mask_image": {
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_name": "0-output.jpeg",
"file_size": 1843200,
"width": 1024,
"height": 768
}
},
"outputs": [
{
"type": "image",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_size": 1843200,
"width": 1024,
"height": 768,
"stored": true
}
],
"error": null,
"metrics": {
"inference_seconds": 6.8
},
"urls": {
"self": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Velden van de uitvoer
- image
- object {url, content_type, file_name, file_size, width, height}Afbeelding na achtergrondverwijdering, of het segmentatiemasker wanneer `mask_only` `True` is.
- mask_image
- object {url, content_type, file_name, file_size, width, height} | nullMasker dat tijdens achtergrondverwijdering is toegepast.
Andere varianten van BiRefNet
Meer modellen: Achtergrond verwijderen
Voor AI-agents: deze pagina als Markdown staat op https://doitong.com/nl/developers/models/birefnet/v2.md. Alle modellen en handleidingen: https://doitong.com/developers/llms.txt