Pixal3d
Integruoti
pixal3d
# 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/pixal3d?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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/pixal3d?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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/pixal3d", 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/lt/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": "pixal3d",
"input": {
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
}
Iškvieskite Pixal3d modelį (pixal3d) per Doitong API. Dokumentacija agentams: https://doitong.com/lt/developers/models/pixal3d.md
POST https://api.doitong.ru/v1/run/pixal3d?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
Jei atsakymo būsena yra "queued" arba "running", siųskite GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 užklausas, kol būsena taps "succeeded"; failai pateikiami outputs[].url. POST https://api.doitong.ru/v1/quote/pixal3d su tuo pačiu turiniu grąžina tikslią kainą prieš paleidimą.
Ši užklausa: 0,30 $ 300 API kreditų · ≈ 31,97 ₽ Paleisti šiame puslapyje
Jūsų naujas API raktas. Jis rodomas tik dabar ir jau įrašytas kode bei toliau esančiame API rakto lauke. Saugokite jį paslaptyje: niekada nedėkite jo į kodą, kuris vykdomas naršyklėje.
Čia bus pirmasis jūsų rezultatas
Sukurkite užklausą toliau ir paleiskite ją naudodami savo API raktą. Išvestys nukopijuojamos į mūsų saugyklą ir saugomos neribotą laiką arba 7 dienos nemokamai.
Sukurti užklausą
Valdikliai sugeneruojami pagal modelio schemą. Keisdami juos atnaujinsite kodą ir kainą.
/run/pixal3d?wait=20
kaina → 0,30 $
# 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/pixal3d?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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/pixal3d?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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/pixal3d", 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": "pixal3d",
"input": {
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
},
"wait_seconds": 20
}
}
}
Vykdyti šią užklausą
Jūsų raktas lieka šioje naršyklėje: jis siunčiamas tik į Doitong API ir išsaugomas (localStorage) tik pažymėjus Prisiminti. Gauti API raktą
Apie Pixal3d
Priima vieną vaizdą ir grąžina GLB modelį bei naudotą sėklą. Struktūros, formos ir tekstūros etapai turi atskirus nukreipimo, perkeitimo mastelio, žingsnių skaičiaus ir triukšmo grafiko nustatymus. Išvesties `resolution` yra 1024 arba 1536, `texture_size` – 1024, 2048 arba 4096, o `decimation_target` nustato viršūnių skaičių nuo 5000 iki 1586021. `remesh` sukuria topologiją iš naujo.
Parametrai
Siųskite arba kanoninį, arba savąjį pavadinimą, bet ne abu. Kanoniniai pavadinimai
image_urlprivaloma
image
seedneprivalomas
resolutionneprivalomas
ss_guidance_strengthneprivalomas
ss_guidance_rescaleneprivalomas
ss_sampling_stepsneprivalomas
ss_rescale_tneprivalomas
shape_slat_guidance_strengthneprivalomas
shape_slat_guidance_rescaleneprivalomas
shape_slat_sampling_stepsneprivalomas
shape_slat_rescale_tneprivalomas
tex_slat_guidance_strengthneprivalomas
tex_slat_guidance_rescaleneprivalomas
tex_slat_sampling_stepsneprivalomas
tex_slat_rescale_tneprivalomas
mesh_scaleneprivalomas
max_num_tokensneprivalomas
decimation_targetneprivalomas
texture_sizeneprivalomas
remeshneprivalomas
enable_safety_checkerneprivalomas
Failų parametrams reikia viešo https:// URL, ne didesnio nei 10 MB data: URI arba įkelto failo file_url. Failai
Išvestis
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "pixal3d",
"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": 300,
"usd": "0.30",
"charged": 300,
"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
},
"seed": 42
},
"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"
}
}
Išvesties laukai
- model_glb
- object {url, content_type, file_name, file_size}GLB formatu sugeneruotas 3D modelis.
- seed
- integerFaktiškai panaudota pradžios reikšmė.
Daugiau modelių: Vaizdas į 3D
AI agentams: šis puslapis Markdown formatu pateikiamas adresu https://doitong.com/lt/developers/models/pixal3d.md. Visi modeliai ir vadovai: https://doitong.com/developers/llms.txt