ByteDance Seed3D 2.0 — generates a textured, PBR-shaded 3D model (glb/obj/usd/usdz) from a single input image. Returns a downloadable .zip archive containing the 3D file.
Każde uruchomienie będzie kosztować $0.353. Za $10 możesz uruchomić ten model około 28 razy.
import requests
import time
# Step 1: Start image generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "bytedance/seed3d-v2.0/image-to-3d", # Required. model name
"image": "example_value", # Required. Source image (URL or base64 data URI)
"subdivision_level": "medium", # Subdivision level for the generated 3D mesh. options: high | medium | low
"file_format": "glb", # Output 3D file format. options: glb | obj | usd | usdz
"enable_base64_output": False, # If enabled, the output will be encoded into a BASE64 string instead of a URL
}
generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]
# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
def check_status():
while True:
response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
result = response.json()
if result["data"]["status"] == "completed":
print("Generated image:", result["data"]["outputs"][0])
return result["data"]["outputs"][0]
elif result["data"]["status"] == "failed":
raise Exception(result["data"]["error"] or "Generation failed")
else:
# Still processing, wait 2 seconds
time.sleep(2)
image_url = check_status()Zainstaluj wymagany pakiet dla swojego języka programowania.
pip install requestsWszystkie żądania API wymagają uwierzytelnienia za pomocą klucza API. Klucz API możesz uzyskać z panelu Atlas Cloud.
export ATLASCLOUD_API_KEY="your-api-key-here"import os
API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {API_KEY}"
}Nigdy nie ujawniaj swojego klucza API w kodzie po stronie klienta ani w publicznych repozytoriach. Zamiast tego użyj zmiennych środowiskowych lub proxy backendowego.
import requests
url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "your-model",
"prompt": "A beautiful landscape"
}
response = requests.post(url, headers=headers, json=data)
print(response.json())Wyślij asynchroniczne żądanie generowania. API zwróci identyfikator predykcji, którego możesz użyć do sprawdzania statusu i pobierania wyniku.
/api/v1/model/generateImageimport requests
url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "bytedance/seed3d-v2.0/image-to-3d",
"prompt": "A beautiful landscape with mountains and lake"
}
response = requests.post(url, headers=headers, json=data)
result = response.json()
print(f"Prediction ID: {result['data']['id']}")
print(f"Status: {result['data']['status']}"){
"code": 200,
"data": {
"id": "pred_abc123",
"status": "processing",
"model": "model-name",
"created_at": "2025-01-01T00:00:00Z"
}
}Odpytuj endpoint predykcji, aby sprawdzić bieżący status żądania.
/api/v1/model/prediction/{prediction_id}import requests
import time
prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }
while True:
response = requests.get(url, headers=headers)
result = response.json()
status = result["data"]["status"]
print(f"Status: {status}")
if status in ["completed", "succeeded"]:
output_url = result["data"]["outputs"][0]
print(f"Output URL: {output_url}")
break
elif status == "failed":
print(f"Error: {result['data'].get('error', 'Unknown')}")
break
time.sleep(3)processingŻądanie jest wciąż przetwarzane.completedGenerowanie zakończone. Wyniki są dostępne.succeededGenerowanie powiodło się. Wyniki są dostępne.failedGenerowanie nie powiodło się. Sprawdź pole błędu.{
"data": {
"id": "pred_abc123",
"status": "completed",
"outputs": [
"https://storage.atlascloud.ai/outputs/result.png"
],
"metrics": {
"predict_time": 8.3
},
"created_at": "2025-01-01T00:00:00Z",
"completed_at": "2025-01-01T00:00:10Z"
}
}Prześlij pliki do magazynu Atlas Cloud i uzyskaj URL, którego możesz użyć w swoich żądaniach API. Użyj multipart/form-data do przesyłania.
/api/v1/model/uploadMediaimport requests
url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }
with open("image.png", "rb") as f:
files = {"file": ("image.png", f, "image/png")}
response = requests.post(url, headers=headers, files=files)
result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}"){
"data": {
"download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
"file_name": "image.png",
"content_type": "image/png",
"size": 1024000
}
}Następujące parametry są akceptowane w treści żądania.
{
"model": "bytedance/seed3d-v2.0/image-to-3d",
"image": "example_image",
"subdivision_level": "medium",
"file_format": "glb",
"enable_base64_output": false
}API zwraca odpowiedź predykcji z URL-ami wygenerowanych wyników.
{
"id": "pred_abc123",
"status": "completed",
"model": "model-name",
"outputs": [
"https://storage.atlascloud.ai/outputs/result.png"
],
"metrics": {
"predict_time": 8.3
},
"created_at": "2025-01-01T00:00:00Z",
"completed_at": "2025-01-01T00:00:10Z"
}Atlas Cloud Skills integruje ponad 400 modeli AI bezpośrednio z Twoim asystentem kodowania AI. Jedno polecenie do instalacji, a następnie używaj języka naturalnego do generowania obrazów, filmów i rozmów z LLM.
npx skills add AtlasCloudAI/atlas-cloud-skillsUzyskaj klucz API z panelu Atlas Cloud i ustaw go jako zmienną środowiskową.
export ATLASCLOUD_API_KEY="your-api-key-here"Po zainstalowaniu możesz używać języka naturalnego w swoim asystencie AI, aby uzyskać dostęp do wszystkich modeli Atlas Cloud.
Serwer MCP Atlas Cloud łączy Twoje IDE z ponad 400 modelami AI za pośrednictwem Model Context Protocol. Działa z każdym klientem kompatybilnym z MCP.
npx -y atlascloud-mcpDodaj następującą konfigurację do pliku ustawień MCP w swoim IDE.
{
"mcpServers": {
"atlascloud": {
"command": "npx",
"args": [
"-y",
"atlascloud-mcp"
],
"env": {
"ATLASCLOUD_API_KEY": "your-api-key-here"
}
}
}
}{
"openapi": "3.0.0",
"info": {
"title": "AtlasCloud API",
"version": "1.0.0",
"description": "The AtlasCloud API."
},
"servers": [
{
"url": "https://api.atlascloud.ai"
}
],
"paths": {
"/api/v1/model/generateImage": {
"post": {
"requestBody": {
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/Input"
}
}
},
"required": true
},
"responses": {
"200": {
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/PredictionResponse"
}
}
},
"description": "The request status."
}
},
"x-api-name": "model_run"
}
},
"/api/v1/model/result/{request_id}": {
"get": {
"parameters": [
{
"in": "path",
"name": "request_id",
"required": true,
"schema": {
"description": "Request ID",
"type": "string"
}
}
],
"responses": {
"200": {
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/PredictionResponse"
}
}
},
"description": "Result of the request."
}
},
"x-api-name": "model_result"
}
}
},
"components": {
"schemas": {
"Input": {
"type": "object",
"properties": {
"model": {
"type": "string",
"description": "model name",
"default": "bytedance/seed3d-v2.0/image-to-3d"
},
"image": {
"type": "string",
"description": "Source image (URL or base64 data URI). Constraints: total pixels < 4096x4096, size <= 10 MB, aspect ratio in (0.4, 2.5), formats: jpg, jpeg, png, webp, bmp."
},
"subdivision_level": {
"type": "string",
"description": "Subdivision level for the generated 3D mesh. high=1,000,000 / medium=500,000 / low=100,000 polygon faces.",
"enum": [
"high",
"medium",
"low"
],
"default": "medium"
},
"file_format": {
"type": "string",
"description": "Output 3D file format. The result is delivered as a .zip archive containing a single file in the chosen format.",
"enum": [
"glb",
"obj",
"usd",
"usdz"
],
"default": "glb"
},
"enable_base64_output": {
"type": "boolean",
"description": "If enabled, the output will be encoded into a BASE64 string instead of a URL. This property is only available through the API.",
"default": false,
"disabled": true
}
},
"required": [
"model",
"image"
],
"x-order-properties": [
"model",
"image",
"subdivision_level",
"file_format",
"enable_base64_output"
]
},
"PredictionResponse": {
"type": "object",
"properties": {
"created_at": {
"description": "ISO timestamp of when the request was created (e.g., \"2023-04-01T12:34:56.789Z\").",
"format": "date-time",
"type": "string"
},
"id": {
"description": "Unique identifier for the prediction, the ID of the prediction to get.",
"type": "string"
},
"model": {
"description": "Model ID used for the prediction.",
"type": "string"
},
"outputs": {
"description": "Array containing one URL pointing to the generated 3D file .zip archive (empty when status is not completed). The URL is valid for 24 hours.",
"items": {
"type": "string"
},
"type": "array"
},
"status": {
"description": "Status of the task: created, processing, completed, or failed.",
"type": "string"
},
"urls": {
"description": "Object containing related API endpoints.",
"type": "object"
}
}
}
}
}
}# bytedance/seed3d-v2.0/image-to-3d
> ByteDance Seed3D 2.0 — generates a textured, PBR-shaded 3D model (glb/obj/usd/usdz) from a single input image. Returns a downloadable .zip archive containing the 3D file.
## Overview
- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateImage` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `bytedance/seed3d-v2.0/image-to-3d`
## API Information
This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.
### Input Schema
The API accepts the following input parameters:
- **`model`** (`string`, _required_):
model name
- Default: `"bytedance/seed3d-v2.0/image-to-3d"`
- **`image`** (`string`, _required_):
Source image (URL or base64 data URI). Constraints: total pixels < 4096x4096, size <= 10 MB, aspect ratio in (0.4, 2.5), formats: jpg, jpeg, png, webp, bmp.
- **`subdivision_level`** (`string`, _optional_):
Subdivision level for the generated 3D mesh. high=1,000,000 / medium=500,000 / low=100,000 polygon faces.
- Default: `"medium"`
- Options: "high", "medium", "low"
- **`file_format`** (`string`, _optional_):
Output 3D file format. The result is delivered as a .zip archive containing a single file in the chosen format.
- Default: `"glb"`
- Options: "glb", "obj", "usd", "usdz"
- **`enable_base64_output`** (`boolean`, _optional_):
If enabled, the output will be encoded into a BASE64 string instead of a URL. This property is only available through the API.
- Default: `false`
**Required Parameters Example**:
```json
{
"model": "bytedance/seed3d-v2.0/image-to-3d",
"image": ""
}
```
**Full Example**:
```json
{
"model": "bytedance/seed3d-v2.0/image-to-3d",
"image": "",
"subdivision_level": "medium",
"file_format": "glb",
"enable_base64_output": false
}
```
### Output Schema
The API returns the following output format:
- **`created_at`** (`string`, _optional_):
ISO timestamp of when the request was created (e.g., "2023-04-01T12:34:56.789Z").
- **`id`** (`string`, _optional_):
Unique identifier for the prediction, the ID of the prediction to get.
- **`model`** (`string`, _optional_):
Model ID used for the prediction.
- **`outputs`** (`array[string]`, _optional_):
Array containing one URL pointing to the generated 3D file .zip archive (empty when status is not completed). The URL is valid for 24 hours.
- **`status`** (`string`, _optional_):
Status of the task: created, processing, completed, or failed.
- **`urls`** (`object`, _optional_):
Object containing related API endpoints.
**Example Response**:
```json
{
"created_at": "",
"id": "",
"model": "",
"outputs": [
""
],
"status": "",
"urls": {}
}
```
## Usage Examples
### cURL
```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateImage" \
-H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "bytedance/seed3d-v2.0/image-to-3d",
"image": "",
"subdivision_level": "medium",
"file_format": "glb",
"enable_base64_output": false
}'
# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}
# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
-H "Authorization: Bearer $ATLASCLOUD_API_KEY"
# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```
## Additional Resources
### Documentation
- [Model Playground](https://www.atlascloud.ai/models/bytedance/seed3d-v2.0/image-to-3d)
No 3D output