Sam 3 · Image RLE
Integrasikan
sam-3/image-rle
# 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/sam-3/image-rle?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/sam-3/image-rle?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/sam-3/image-rle", 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/id/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": "sam-3/image-rle",
"input": {
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
}
Panggil model Sam 3 · Image RLE (sam-3/image-rle) melalui Doitong API. Dokumentasi untuk agen: https://doitong.com/id/developers/models/sam-3/image-rle.md
POST https://api.doitong.ru/v1/run/sam-3/image-rle?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
Jika status respons adalah "queued" atau "running", lakukan polling GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 hingga statusnya menjadi "succeeded"; file terdapat di outputs[].url. POST https://api.doitong.ru/v1/quote/sam-3/image-rle dengan body yang sama mengembalikan harga pasti sebelum dijalankan.
Permintaan ini: ≈$0,005 5 kredit API · ≈ ₽0,53 Jalankan di halaman ini
Kunci API baru Anda. Ini hanya ditampilkan sekarang dan sudah dimasukkan ke dalam kode serta kolom kunci API di bawah. Simpan secara rahasia: jangan pernah menaruhnya di kode yang berjalan di browser.
Hasil pertama Anda akan muncul di sini
Buat permintaan di bawah ini dan jalankan dengan kunci API Anda. Output disalin ke penyimpanan kami, disimpan selamanya atau 7 hari gratis.
Buat permintaan
Kontrol dibuat dari skema model. Kode dan harga diperbarui saat Anda mengubahnya.
/run/sam-3/image-rle?wait=20
estimasi harga → $0,005
# 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/sam-3/image-rle?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/sam-3/image-rle?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/sam-3/image-rle", 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": "sam-3/image-rle",
"input": {
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
},
"wait_seconds": 20
}
}
}
Jalankan permintaan ini
Key Anda tetap berada di browser ini: key hanya dikirim ke Doitong API dan disimpan (localStorage) hanya jika Anda mencentang Ingat. Dapatkan kunci API
Tentang Sam 3 · Image RLE
Menjalankan segmentasi SAM 3 pada gambar menggunakan `prompt` teks, titik, atau kotak, lalu mengembalikan mask sebagai data run-length encoding (RLE). Berguna saat Anda memerlukan data mask ringkas untuk pascapemrosesan. Mendukung `return_multiple_masks` dengan `max_masks` dari 1 hingga 32, serta skor dan kotak opsional.
Parameter
Kirim nama kanonis atau nama asli, bukan keduanya. Nama kanonis
image_urlwajib
image
promptopsional
text_promptopsional
point_promptsopsional
point_prompts[].xopsional
point_prompts[].yopsional
point_prompts[].labelopsional
point_prompts[].object_idopsional
point_prompts[].frame_indexopsional
box_promptsopsional
box_prompts[].x_minopsional
box_prompts[].y_minopsional
box_prompts[].x_maxopsional
box_prompts[].y_maxopsional
box_prompts[].object_idopsional
box_prompts[].frame_indexopsional
apply_maskopsional
output_formatopsional
return_multiple_masksopsional
max_masksopsional
include_scoresopsional
include_boxesopsional
Parameter file menerima URL publik https://, URI data: hingga 10 MB, atau file_url dari unggahan. File
Output
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "sam-3/image-rle",
"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": 5,
"usd": "0.005",
"charged": 5,
"refunded": 0
},
"input": {
"image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
},
"output": {
"rle": "string",
"boundingbox_frames_zip": {
"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
},
"metadata": [
{
"index": 1,
"score": 1.0,
"box": [
1.0
]
}
],
"scores": [
1.0
],
"boxes": [
[
1.0
]
]
},
"outputs": [
{
"type": "file",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_size": 1843200,
"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"
}
}
Field output
- rle
- string | array of stringMask yang direpresentasikan menggunakan run-length encoding.
- boundingbox_frames_zip
- object {url, content_type, file_name, file_size} | nullArsip ZIP overlay kotak pembatas untuk setiap bingkai.
- metadata
- array of object {index, score, box} | nullMetadata untuk setiap mask, disertakan saat respons berisi beberapa RLE.
- scores
- array of number | nullSkor keyakinan untuk setiap mask, diberikan jika diminta.
- boxes
- array of array of number | nullKotak ternormalisasi untuk setiap mask, dinyatakan sebagai [cx, cy, w, h], jika diminta.
Varian Sam3 lainnya
Model lainnya: Pengeditan Gambar
Untuk agen AI: halaman ini dalam Markdown tersedia di https://doitong.com/id/developers/models/sam-3/image-rle.md. Semua model dan panduan: https://doitong.com/developers/llms.txt






