Home/Explore/Tripo3D/P2/Image To 3d

Tripo P2 Image-to-3D API

tripo3d/p2/image-to-3d

Tripo3D P2 Image-to-3D turns a single image into a 3D model with Tripo's P2 model with native quad topology (up to 50,000 triangles or 25,000 quads) for games and real-time pipelines. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Image to 3D
Input

Drag & drop or click to upload

preview

Idle

3D

$1.32per run

ExamplesView all

3D
3D
3D
3D
3D

Related Models

README

Tripo3D P2 Image-to-3D

Tripo3D P2 Image-to-3D generates a 3D model from a single image, with optional textures and PBR materials. Adjust the face count and choose triangle or quad output.

Why Choose This?

  • Geometry and materials — Generate geometry alone or include textures and PBR materials.
  • Texture choices — Choose standard, detailed, extreme, or fast texturing.
  • Mesh options — Adjust the face count and choose triangle or quad output.

Parameters

ParameterRequiredDescription
imageYesImage of the object (PNG, JPEG or WebP).
textureNoGenerate texture maps. Turn off (with pbr) for an untextured model at a lower price. Default: true.
pbrNoGenerate PBR materials (base color, metallic, roughness, normal). Turning it on also turns on texture. Default: true.
texture_qualityNoTexture quality: standard, detailed, extreme (8k), or fast (same texture size as standard). Options: standard, detailed, extreme, fast. Default: standard.
texture_versionNoTexture version. fast quality uses v3.5-20260815. Options: v3.0-20250812, v3.5-20260815. Default: v3.0-20250812.
delightNoRemove the lighting baked into the source before texturing (texture model v3.5-20260815 only). Default: true.
quadNoOutput a native quad mesh (FBX). Default: false.
face_limitNoMaximum number of faces: 48 to 50,000 triangles, or 48 to 25,000 quads. Omit for adaptive; 150+ for simple objects, 250+ for complex ones.
texture_alignmentNoWhat the texture follows: the source image colors or the generated geometry. Options: original_image, geometry. Default: original_image.
orientationNoalign_image rotates the model to the source image viewpoint (textured models only). Options: default, align_image. Default: default.
enable_image_autofixNoRequest input-image correction before generation. Default: false.
auto_sizeNoScale the model to real-world size in meters. Needs a textured model. Default: false.
export_uvNoUnwrap UVs during generation. Default: true.
model_seedNoOptional seed for geometry generation.
texture_seedNoOptional seed for texture generation.

How to Use

  1. Upload an image of the object.
  2. Choose geometry and texture settings.
  3. Adjust optional mesh settings.
  4. Submit the request and download the generated model.

Pricing

ConfigurationPrice per request
Geometry only$1.20
With standard or fast textures$1.32
With detailed textures$1.44
With extreme (8k) textures$1.56

Quad output does not add a separate charge.

For geometry-only output, turn off both texture and pbr. Enabling pbr also enables textures.

Notes

  • Turn off both texture and pbr for an untextured model.
  • fast uses the same texture size and price as standard and selects texture version v3.5-20260815.
  • delight affects texturing only with texture version v3.5-20260815; older texture versions ignore it.
  • Texture quality settings do not add a charge when textures are not generated.
  • auto_size estimates real-world scale and requires textured output.
Note:This website uses AI models provided by third parties. Documentation prices are for reference and may be outdated. The Generate button shows an estimate; the final task charge prevails.

P2 Image To 3d API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/tripo3d/p2/image-to-3d with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for P2 Image To 3d below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "texture": true,
    "pbr": true,
    "texture_quality": "standard",
    "texture_version": "v3.0-20250812",
    "delight": true,
    "quad": false,
    "texture_alignment": "original_image",
    "orientation": "default",
    "enable_image_autofix": false,
    "auto_size": false,
    "export_uv": true
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/tripo3d/p2/image-to-3d" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d "$REQUEST_BODY")

TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
    -H "Authorization: Bearer $WAVESPEED_API_KEY")
  RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$STATUS" in
    completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout|deleted) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    *) sleep 2 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/tripo3d/p2/image-to-3d";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');

async function requestJson(url, options = {}) {
  const response = await fetch(url, options);
  if (!response.ok) throw new Error(await response.text());
  return response.json();
}

// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
        "texture": true,
        "pbr": true,
        "texture_quality": "standard",
        "texture_version": "v3.0-20250812",
        "delight": true,
        "quad": false,
        "texture_alignment": "original_image",
        "orientation": "default",
        "enable_image_autofix": false,
        "auto_size": false,
        "export_uv": true
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;

// 2. Poll until the prediction finishes.
while (true) {
  const resultBody = await requestJson(resultUrl, {
    headers: { "Authorization": `Bearer ${apiKey}` },
  });
  const result = resultBody.data ?? resultBody;
  if (result.status === "completed") {
    console.log(result.outputs);
    break;
  }
  if (["failed", "cancelled", "timeout", "deleted"].includes(result.status)) throw new Error(JSON.stringify(result));
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
import json
import os
import time
from urllib.request import Request, urlopen

api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "texture": True,
    "pbr": True,
    "texture_quality": "standard",
    "texture_version": "v3.0-20250812",
    "delight": True,
    "quad": False,
    "texture_alignment": "original_image",
    "orientation": "default",
    "enable_image_autofix": False,
    "auto_size": False,
    "export_uv": True
}

def request_json(url, data=None):
    request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
    with urlopen(request) as response:
        return json.load(response)

# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/tripo3d/p2/image-to-3d", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
    raise RuntimeError("Submission response did not contain a prediction id")
result_url = f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"

# 2. Poll until the prediction finishes.
while True:
    result_body = request_json(result_url)
    result = result_body.get("data", result_body)
    status = result.get("status")
    if status == "completed":
        print(result.get("outputs", []))
        break
    if status in {"failed", "cancelled", "timeout", "deleted"}:
        raise RuntimeError(result)
    time.sleep(2)

P2 Image To 3d API — Frequently asked questions

What is the P2 Image To 3d API?

P2 Image To 3d is a Tripo3D model for 3D asset generation from images, exposed as a REST API on WaveSpeedAI. Tripo3D P2 Image-to-3D turns a single image into a 3D model with Tripo's P2 model with native quad topology (up to 50,000 triangles or 25,000 quads) for games and real-time pipelines. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the P2 Image To 3d API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates Python, JavaScript, and cURL examples for submitting requests and polling results. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/tripo3d/tripo3d-p2-image-to-3d.

How much does P2 Image To 3d cost per run or per second?

P2 Image To 3d starts at $1.32 per run or per second. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does P2 Image To 3d accept?

Key inputs: `image`, `auto_size`, `delight`, `enable_image_autofix`, `export_uv`, `face_limit`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/tripo3d/tripo3d-p2-image-to-3d.

How do I get started with the P2 Image To 3d API?

Sign up for a free WaveSpeedAI account to claim starter credits, copy your API key from /accesskey, then call the endpoint shown in the API tab of the playground. The playground also auto-generates a code sample in Python, JavaScript, or cURL for the parameters you've set.

Can I use P2 Image To 3d outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Tripo3D). Check the provider's applicable terms and WaveSpeedAI's Terms of Service before commercial use.

llms.txt — tripo3d/p2/image-to-3d for AI agents and LLMs