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.
Her çalıştırma $0.353 maliyete sahip. 10$ ile yaklaşık 28 kez çalıştırabilirsiniz.
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()Programlama diliniz için gerekli paketi kurun.
pip install requestsTüm API istekleri, API anahtarı ile kimlik doğrulama gerektirir. API anahtarınızı Atlas Cloud kontrol panelinden alabilirsiniz.
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}"
}API anahtarınızı asla istemci tarafı kodunda veya herkese açık depolarda ifşa etmeyin. Bunun yerine ortam değişkenleri veya arka uç proxy kullanın.
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())Asenkron bir oluşturma isteği gönderin. API, durumu kontrol etmek ve sonucu almak için kullanabileceğiniz bir tahmin ID'si döndürür.
/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"
}
}İsteğinizin mevcut durumunu kontrol etmek için tahmin uç noktasını sorgulayın.
/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)processingİstek hâlâ işleniyor.completedOluşturma tamamlandı. Çıktılar kullanılabilir.succeededOluşturma başarılı oldu. Çıktılar kullanılabilir.failedOluşturma başarısız oldu. Hata alanını kontrol edin.{
"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"
}
}Dosyaları Atlas Cloud depolama alanına yükleyin ve API isteklerinizde kullanabileceğiniz bir URL alın. Yüklemek için multipart/form-data kullanın.
/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
}
}İstek gövdesinde aşağıdaki parametreler kabul edilir.
{
"model": "bytedance/seed3d-v2.0/image-to-3d",
"image": "example_image",
"subdivision_level": "medium",
"file_format": "glb",
"enable_base64_output": false
}API, oluşturulan çıktı URL'lerini içeren bir tahmin yanıtı döndürür.
{
"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, 400'den fazla AI modelini doğrudan AI kodlama asistanınıza entegre eder. Kurmak için tek bir komut, ardından görüntü, video oluşturmak ve LLM ile sohbet etmek için doğal dil kullanın.
npx skills add AtlasCloudAI/atlas-cloud-skillsAPI anahtarınızı Atlas Cloud kontrol panelinden alın ve ortam değişkeni olarak ayarlayın.
export ATLASCLOUD_API_KEY="your-api-key-here"Kurulduktan sonra, tüm Atlas Cloud modellerine erişmek için AI asistanınızda doğal dil kullanabilirsiniz.
Atlas Cloud MCP Server, IDE'nizi Model Context Protocol aracılığıyla 400'den fazla AI modeline bağlar. Herhangi bir MCP uyumlu istemci ile çalışır.
npx -y atlascloud-mcpAşağıdaki yapılandırmayı IDE'nizin MCP ayarları dosyasına ekleyin.
{
"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