Birefnet
Integrate
birefnet/v2/video
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/birefnet/v2/video?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/birefnet/v2/video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/birefnet/v2/video", 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/en-GB/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.ru/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "birefnet/v2/video",
"input": {
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
}
}
Call the Birefnet model (birefnet/v2/video) through the Doitong API. Docs for agents: https://doitong.com/en-GB/developers/models/birefnet/v2/video.md
POST https://api.doitong.ru/v1/run/birefnet/v2/video?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
}
If the response status is "queued" or "running", poll GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 until it is "succeeded"; the files are in outputs[].url. POST https://api.doitong.ru/v1/quote/birefnet/v2/video with the same body returns the exact price before the run.
Up to $2.07 per run charged by actual usage, the rest is refunded Run it on this page
Your new API key. It is shown only now and is already in the code and in the API key field below. Keep it secret: never put it in code that runs in a browser.
Your first result goes here
Build a request below and run it with your API key. Outputs are copied to our storage, kept forever or 7 days for free.
Build a request
Controls are generated from the model schema. The code and the price update as you change them.
/run/birefnet/v2/video?wait=20
quote → $2.07
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/birefnet/v2/video?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/birefnet/v2/video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/birefnet/v2/video", 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/video",
"input": {
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
},
"wait_seconds": 20
}
}
}
Run this request
Your key stays in this browser: it is sent only to the Doitong API and saved (localStorage) only if you tick Remember. Get an API key
About Birefnet
Applies BiRefNet segmentation to each frame of a video from `video_url`. Models include Light, Light 2K, Heavy, Matting, Portrait and Dynamic, with operating resolutions up to 2304x2304 (only for the Dynamic model). Output can be X264 mp4, VP9 webm, ProRes 4444 mov or GIF, with `video_quality` and `video_write_mode` settings. A separate mask video can be requested.
Parameters
Send either the canonical name or the native name, not both. Canonical names
modeloptional
operating_resolutionoptional
output_maskoptional
refine_foregroundoptional
video_urlrequired
video
video_output_typeoptional
video_qualityoptional
video_write_modeoptional
File parameters take a public https:// URL, a data: URI up to 10 MB, or the file_url of an upload. Files
Output
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "birefnet/v2/video",
"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": 2070,
"usd": "2.07",
"charged": 2070,
"refunded": 0
},
"input": {
"video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
},
"output": {
"video": {
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
"content_type": "video/mp4",
"file_name": "0-output.mp4",
"file_size": 1843200,
"width": 1024,
"height": 768,
"fps": 1.0,
"duration": 5,
"num_frames": 1
},
"mask_video": {
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
"content_type": "video/mp4",
"file_name": "0-output.mp4",
"file_size": 1843200,
"width": 1024,
"height": 768,
"fps": 1.0,
"duration": 5,
"num_frames": 1
}
},
"outputs": [
{
"type": "video",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
"content_type": "video/mp4",
"file_size": 1843200,
"width": 1280,
"height": 720,
"duration": 5,
"stored": true
}
],
"error": null,
"metrics": {
"inference_seconds": 6.8
},
"urls": {
"self": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Fields of output
- video
- object {url, content_type, file_name, file_size, width, height, fps, duration, num_frames}Video after background removal.
- mask_video
- object {url, content_type, file_name, file_size, width, height, fps, duration, num_frames} | nullMask applied during background removal.
More models: Background Removal
For AI agents: this page as Markdown is at https://doitong.com/en-GB/developers/models/birefnet/v2/video.md. All models and guides: https://doitong.com/developers/llms.txt