Sam 3 · 3D Body
Integra
sam-3/3d-body
# 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/sam-3/3d-body?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.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/sam-3/3d-body?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/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-3/3d-body", 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/it/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": "sam-3/3d-body",
"input": {
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
}
Chiama il modello Sam 3 · 3D Body (sam-3/3d-body) tramite Doitong API. Documentazione per gli agenti: https://doitong.com/it/developers/models/sam-3/3d-body.md
POST https://api.doitong.com/v1/run/sam-3/3d-body?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
Se lo stato della risposta è "queued" o "running", interroga GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 finché non diventa "succeeded"; i file si trovano in outputs[].url. POST https://api.doitong.com/v1/quote/sam-3/3d-body con lo stesso body restituisce il prezzo esatto prima dell'esecuzione.
Questa richiesta: ≈0,02 $ 20 crediti API Esegui in questa pagina
La tua nuova chiave API. Viene mostrata solo ora ed è già presente nel codice e nel campo della chiave API qui sotto. Mantienila segreta: non inserirla mai nel codice eseguito in un browser.
Il tuo primo risultato apparirà qui
Crea una richiesta qui sotto ed eseguila con la tua chiave API. Gli output vengono copiati nella nostra archiviazione, conservati per sempre oppure 7 giorni gratuitamente.
Crea una richiesta
I controlli vengono generati dallo schema del modello. Il codice e il prezzo si aggiornano mentre li modifichi.
/run/sam-3/3d-body?wait=20
preventivo → 0,02 $
# 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/sam-3/3d-body?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.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/sam-3/3d-body?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/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-3/3d-body", 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-3/3d-body",
"input": {
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
},
"wait_seconds": 20
}
}
}
Esegui questa richiesta
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Informazioni su Sam 3 · 3D Body
Crea mesh 3D dei corpi delle persone presenti in un'immagine. Le persone vengono rilevate automaticamente oppure puoi passare una maschera binaria in `mask_url` (bianco per la persona). I controlli gestiscono l'esportazione .ply per persona, i marcatori dei punti chiave 3D nel GLB e l'intero set di parametri MHR nei metadati. Restituisce un GLB, mesh, metadati e un'immagine di visualizzazione.
Parametri
Invia il nome canonico oppure il nome nativo, non entrambi. Nomi canonici
image_urlobbligatorio
image
mask_urlfacoltativo
mask
export_meshesfacoltativo
include_3d_keypointsfacoltativo
include_mhr_paramsfacoltativo
I parametri file accettano un URL pubblico https://, un URI data: fino a 10 MB oppure il file_url di un caricamento. File
Output
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "sam-3/3d-body",
"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": 20,
"usd": "0.02",
"charged": 20,
"refunded": 0
},
"input": {
"image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
},
"output": {
"model_glb": {
"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
},
"visualization": {
"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
},
"meshes": [
{
"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": {
"num_people": 1,
"people": [
{
"person_id": 1,
"bbox": [],
"focal_length": 1.0,
"pred_cam_t": [],
"keypoints_2d": [],
"keypoints_3d": [],
"shape_params": [],
"body_pose_params": [],
"hand_pose_params": [],
"global_rot": [],
"pred_global_rots": [],
"scale_params": [],
"expr_params": [],
"pred_joint_coords": [],
"mhr_model_params": [],
"pred_pose_raw": []
}
],
"keypoint_names": [
"string"
]
}
},
"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.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Campi dell'output
- model_glb
- object {url, content_type, file_name, file_size}Mesh del corpo 3D in formato GLB, con eventuali marker dei punti chiave 3D.
- visualization
- object {url, content_type, file_name, file_size}Visualizzazione composita con immagine originale, punti chiave, mesh e vista laterale.
- meshes
- array of object {url, content_type, file_name, file_size} | nullFile mesh .ply separati per ogni persona rilevata, restituiti quando export_meshes è True.
- metadata
- object {num_people, people, keypoint_names}Metadati strutturati contenenti parametri della fotocamera e punti chiave.
Altre varianti di Sam3
Altri modelli: Da immagine a 3D
Per gli agenti AI: questa pagina in Markdown è disponibile all'indirizzo https://doitong.com/it/developers/models/sam-3/3d-body.md. Tutti i modelli e le guide: https://doitong.com/developers/llms.txt