## Basic model info - Model name: bytedance/bytedance seedream-5.0-pro - Model description: Flagship Seedream 5.0 Pro model with deep-thinking prompt understanding, supporting high quality text-to-image generation and multi-reference image editing. - Endpoint name: layerize ## Model schema The model schema is defined in the OpenAPI schema: [OpenAPI Schema](https://oapi.sunra.ai/main/bytedance/seedream-5.0-pro/latest.json) ### Model input schema The model input schema is: ```json { "description": "Input model for decomposing an image into editable layers using Seedream 5.0 Pro.", "properties": { "prompt": { "default": "", "description": "Optional instructions describing which elements to separate. When empty, the model automatically separates the major elements. Normalized left top right bottom tags may be used for precise coordinate targeting.", "title": "Prompt", "type": "string", "x-sr-order": 201 }, "enable_safety_checker": { "default": true, "description": "If set to true, the safety checker will be enabled.", "title": "Enable Safety Checker", "type": "boolean", "x-sr-order": 501 }, "enhance_prompt_mode": { "default": "standard", "description": "Prompt optimization mode. standard prioritizes image quality; fast reduces generation time.", "enum": [ "standard", "fast" ], "title": "Enhance Prompt Mode", "type": "string", "x-sr-order": 402 }, "image": { "anyOf": [ { "format": "uri", "maxLength": 2083, "minLength": 1, "type": "string" }, { "type": "string" } ], "description": "URL of the image to decompose into a base image and independently editable layers. The image must contain between 512x512 and 6000x6000 total pixels, have an aspect ratio between 1/16 and 16, and be no larger than 30 MB.", "title": "Image", "x-sr-order": 301 }, "resolution": { "default": "auto", "description": "Resolution tier for the output base image and layers. auto adapts to the input image while preserving each element's aspect ratio.", "enum": [ "auto", "1K", "1.5K", "2K" ], "title": "Resolution", "type": "string", "x-sr-order": 401 } }, "required": [ "image" ], "title": "LayerizeInput", "type": "object" } ``` ### Model output schema The model output schema is: ```json { "anyOf": [ { "properties": { "images": { "items": { "properties": { "content_type": { "description": "The mime type of the file.", "title": "Content Type", "type": "string" }, "file_name": { "description": "The name of the file. It will be auto-generated if not provided.", "title": "File Name", "type": "string" }, "file_size": { "description": "The size of the file in bytes.", "title": "File Size", "type": "integer" }, "url": { "description": "The URL where the file can be downloaded from.", "title": "Url", "type": "string" } }, "required": [ "content_type", "file_name", "file_size", "url" ], "title": "SunraFile", "type": "object" }, "title": "Images", "type": "array" } }, "required": [ "images" ], "title": "ImagesOutput", "type": "object" }, { "description": "Layerize output, extended with usage field for post-calculated billing.", "properties": { "layers": { "description": "The base image followed by up to 16 separated transparent-PNG layers, ordered by increasing z_index.", "items": { "description": "A generated base image or separated transparent-PNG layer.", "properties": { "bounding_box": { "anyOf": [ { "description": "Layer bounds in the output base image coordinate system.", "properties": { "absolute": { "description": "[left, top, right, bottom] pixel coordinates in the output base image coordinate system.", "items": { "type": "integer" }, "maxItems": 4, "minItems": 4, "title": "Absolute", "type": "array" }, "normalized": { "description": "[left, top, right, bottom] coordinates normalized to the integer range [0, 1000].", "items": { "type": "integer" }, "maxItems": 4, "minItems": 4, "title": "Normalized", "type": "array" } }, "required": [ "absolute", "normalized" ], "title": "LayerBoundingBox", "type": "object" }, { "type": "null" } ], "description": "The layer's position in the base image coordinate system. Omitted for the base image." }, "description": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "description": "Model-generated description of the layer. Omitted for the base image.", "title": "Description" }, "image": { "properties": { "content_type": { "description": "The mime type of the file.", "title": "Content Type", "type": "string" }, "file_name": { "description": "The name of the file. It will be auto-generated if not provided.", "title": "File Name", "type": "string" }, "file_size": { "description": "The size of the file in bytes.", "title": "File Size", "type": "integer" }, "url": { "description": "The URL where the file can be downloaded from.", "title": "Url", "type": "string" } }, "required": [ "content_type", "file_name", "file_size", "url" ], "title": "SunraFile", "type": "object" }, "name": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "description": "Model-generated label for the layer. Omitted for the base image.", "title": "Name" }, "z_index": { "description": "Stacking order from bottom to top. The base image always has z_index 0.", "maximum": 16, "minimum": 0, "title": "Z Index", "type": "integer" } }, "required": [ "image", "z_index" ], "title": "ImageLayer", "type": "object" }, "title": "Layers", "type": "array" }, "units": { "description": "Billable units: number of generated layers, counted double when the base image exceeds 1536x1536 total pixels.", "title": "Units", "type": "number" } }, "required": [ "layers", "units" ], "title": "LayerizeOutput", "type": "object" } ], "title": "Response Get Request Result Requests Request Id Get" } ``` ## Example inputs and outputs Use the following example inputs and outputs to understand the model. ### Input example ```json { "prompt": "", "enable_safety_checker": true, "enhance_prompt_mode": "standard", "image": "", "resolution": "auto" } ``` ### Output example ```json { } ``` ## Model code examples ### JavaScript ```javascript import { sunra } from "@sunra/client"; const result = await sunra.subscribe("bytedance/seedream-5.0-pro/layerize", { input: { prompt: '', image: '', resolution: 'auto', enhance_prompt_mode: 'standard', enable_safety_checker: true }, logs: true, onQueueUpdate: (update) => { console.log(`Status Update: ${update.status}, Request ID: ${update.request_id}`); }, }); console.log(result.data); console.log(result.requestId); ``` ### Python ```python import sunra_client result = sunra_client.subscribe( "bytedance/seedream-5.0-pro/layerize", arguments={ "prompt": "", "image": "", "resolution": "auto", "enhance_prompt_mode": "standard", "enable_safety_checker": True }, with_logs=True, on_enqueue=print, on_queue_update=print, ) print(result) ``` ### Java ```java import ai.sunra.client.*; import java.util.Map; import com.google.gson.JsonObject; var client = SunraClient.withEnvCredentials(); var response = client.subscribe( "bytedance/seedream-5.0-pro/layerize", SubscribeOptions.builder() .input(Map.of( "prompt", "", "image", "", "resolution", "auto", "enhance_prompt_mode", "standard", "enable_safety_checker", true)) .resultType(JsonObject.class) .onQueueUpdate(update -> System.out.printf( "\nStatus Update: %s, Request ID: %s%n", update.getStatus(), update.getRequestId() )) .logs(true) .build() ); System.out.println("Completed!"); System.out.println(response.getData()); ``` ### Kotlin ```kotlin import ai.sunra.client.kt.* import com.google.gson.JsonObject val client = createSunraClient() val response = client.subscribe( endpointId = "bytedance/seedream-5.0-pro/layerize", input = mapOf( "prompt" to "", "image" to "", "resolution" to "auto", "enhance_prompt_mode" to "standard", "enable_safety_checker" to true), options = ai.sunra.client.kt.SubscribeOptions(logs = true), onUpdate = { update -> println("\nStatus Update: ${update.status}, Request ID: ${update.requestId}") } ) println("Completed!") println(response.data) ``` ### Curl ```bash curl --request POST \ --url https://api.sunra.ai/v1/queue/bytedance/seedream-5.0-pro/layerize \ --header "Authorization: Key $SUNRA_KEY" \ --header "Content-Type: application/json" \ --data '{"prompt":"","image":"","resolution":"auto","enhance_prompt_mode":"standard","enable_safety_checker":true}' ``` ## Model readme >