Pixal3d
I-integrate
pixal3d
# 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/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.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/pixal3d?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.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/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/fil/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": "pixal3d",
"input": {
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
}
Tawagin ang modelong Pixal3d (pixal3d) sa pamamagitan ng Doitong API. Dokumentasyon para sa mga agent: https://doitong.com/fil/developers/models/pixal3d.md
POST https://api.doitong.com/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"
}
Kung ang response status ay "queued" o "running", i-poll ang GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 hanggang maging "succeeded"; nasa outputs[].url ang mga file. Ang POST https://api.doitong.com/v1/quote/pixal3d na may parehong body ay nagbabalik ng eksaktong presyo bago patakbuhin.
Kahilingang ito: $0.30 300 kredito ng API Patakbuhin ito sa page na ito
Ang bago mong API key. Ipinapakita lang ito ngayon at nasa code at sa field ng API key sa ibaba na. Panatilihin itong sikreto: huwag kailanman ilagay sa code na tumatakbo sa browser.
Dito mapupunta ang iyong unang resulta
Bumuo ng kahilingan sa ibaba at patakbuhin ito gamit ang iyong API key. Kinokopya ang mga output sa aming storage, na pinananatili nang walang hanggan o 7 araw nang libre.
Bumuo ng kahilingan
Ang mga control ay binubuo mula sa schema ng modelo. Nagbabago ang code at presyo habang ina-adjust mo ang mga ito.
/run/pixal3d?wait=20
presyo → $0.30
# 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/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.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/pixal3d?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.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/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
}
}
}
Patakbuhin ang kahilingang ito
Nananatili ang iyong key sa browser na ito: ipinapadala lamang ito sa Doitong API at sine-save (localStorage) lamang kung pipiliin mo ang Tandaan. Kumuha ng API key
Tungkol sa Pixal3d
Tumatanggap ng isang larawan at nagbabalik ng GLB modelo kasama ang ginamit na seed. May kanya-kanyang guidance, rescale, step-count at noise-schedule setting ang mga yugto ng structure, shape at texture. Ang output na `resolution` ay 1024 o 1536, ang `texture_size` ay 1024, 2048 o 4096, at itinatakda ng `decimation_target` ang bilang ng vertex mula 5000 hanggang 1586021. Binubuo muli ng `remesh` ang topology.
Mga parameter
Ipadala ang canonical na pangalan o ang native na pangalan, hindi pareho. Mga canonical na pangalan
image_urlkinakailangan
image
seedopsyonal
resolutionopsyonal
ss_guidance_strengthopsyonal
ss_guidance_rescaleopsyonal
ss_sampling_stepsopsyonal
ss_rescale_topsyonal
shape_slat_guidance_strengthopsyonal
shape_slat_guidance_rescaleopsyonal
shape_slat_sampling_stepsopsyonal
shape_slat_rescale_topsyonal
tex_slat_guidance_strengthopsyonal
tex_slat_guidance_rescaleopsyonal
tex_slat_sampling_stepsopsyonal
tex_slat_rescale_topsyonal
mesh_scaleopsyonal
max_num_tokensopsyonal
decimation_targetopsyonal
texture_sizeopsyonal
remeshopsyonal
enable_safety_checkeropsyonal
Tumatanggap ang mga parameter ng file ng pampublikong https:// URL, data: URI na hanggang 10 MB, o file_url ng isang upload. Mga file
Output
{
"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.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Mga field ng output
- model_glb
- object {url, content_type, file_name, file_size}3D modelo na nabuo sa GLB format.
- seed
- integerAktuwal na ginamit na seed value.
Higit pang modelo: Larawan patungong 3D
Para sa mga AI agent: nasa Markdown ang pahinang ito sa https://doitong.com/fil/developers/models/pixal3d.md. Lahat ng modelo at gabay: https://doitong.com/developers/llms.txt