For Professional Single-Image Creation and Editable Layer Delivery
Seedream 5.0 Pro is a model in ByteDance's Seedream series for single-image creation and editing, suitable for product visuals, promotional posters, and concept design. It can generate images from text, as well as perform edits using multiple reference images, and provides transparent-background editing and layer separation. Compared with versions focused on continuous image generation, Pro is better suited for creating, revising, and delivering subsequent design assets around a single work.
Input parameters and result formats vary by service. Use the public API for this model and follow its guide for generation, task retrieval and editing operations.
Specifications and API Features
Creation Method
Text-to-image, reference-image generation and editing; standard generation outputs one image per request
Reference Input
URL or Base64; standard generation and editing support up to 10 reference images
Generation Size
The platform supports 1K, 1.5K, 2K, or compliant WIDTHxHEIGHT pixel values
Files and Results
JPEG / PNG; image URL or b64_json
Layer Separation
One PNG/JPEG input; one base image and up to 16 transparent PNG layers
Editing Controls
Transparent-background conditional editing, watermark toggle; prompt optimization standard / fast
Task Processing
Synchronous response, asynchronous task polling, or result callbacks; group images, streaming, and web search are not supported
The above are the calling specifications for this full model on this platform. Standard generation and layer separation use different input and size rules.
Core Capabilities
Organize references around a single work
Text prompts can independently drive image generation, or be combined with product, character, or style references for editing. Multi-image input is suitable for bringing different assets into the same creative task; when describing them, specify the purpose of each image separately and make clear which subjects, compositions, or colors need to be preserved, avoiding mutually contradictory requirements between references.
Move from flat works to layered editing
Layer splitting converts existing images into a base image and transparent PNG layers, and provides hierarchy, names, and bounding boxes for recomposition on a canvas. It can automatically identify elements, or use prompts to specify splitting targets. It is suitable for post-production adjustments to existing compositions, rather than automatically including layered files with ordinary generation.
Support both asset formats and integration methods
Standard generation can choose JPEG or PNG, and retrieve results as links or Base64, making it easy to integrate with asset libraries and design applications. A single PNG with an existing alpha channel can also be edited with a transparent background. Asynchronous tasks and callbacks allow applications to record tasks first and then receive the completed images.
Use Cases
E-commerce product scene images
Input a product image, style references, and a scene description, specifying the product appearance, placement, lighting, and background requirements to generate a product visual for display or advertising. When further modifications are needed, the result can be used as editing input to focus on adjusting the background or visual direction without having to redescribe all assets.
Promotional posters and content covers
Provide the event theme, main elements, color direction, and layout goals, and use prompts to organize a single promotional image. When choosing a resolution preset, describe horizontal or vertical composition in the text; when there are specific canvas requirements, use pixel dimensions. After delivery, text, logos, and subject details should still be checked before completing the final layout.
Layer organization for existing works
Input a PNG or JPEG poster and enable layer splitting to obtain a base image and independently processable transparent layers. Design tools can recompose the image according to z_index and bounding boxes, then adjust element positions or replace assets. This is suitable for moving flat visuals into a post-production workflow, rather than requiring the model to directly output design project files.
How to choose this model
Choose Pro for single-image editing, Lite for continuous creation
When the deliverable is a product image, cover, or design work that needs to be separated into layers, Pro's single-image, transparent-background editing, and decomposition operations are better suited to the task. If you need to generate a related group of images at once, receive results progressively, or use web search to assist creation, choose Seedream 5.0 Lite; these features cannot be enabled for Pro by adding shared parameters.
Choose based on workflow, not just generation
Seedream 4.5 and 4.0 can still be used for image workflows that support image groups and streaming; Pro adds transparent-background editing and layer decomposition for post-production design. Existing continuous image-generation workflows do not need to switch to Pro solely because its version number is higher. Conversely, when editable elements need to be extracted from a flat image, choosing Pro better meets delivery requirements.
Get started
Distinguish regular creation from layer decomposition
For regular generation, prepare prompt; for editing, you can include image. For decomposition, provide a separate PNG/JPEG; multiple reference images cannot be treated as a single poster to be decomposed.
Complete a single work first
Explicitly specify model=doubao-seedream-5-0-pro-260628 for /seedream/images; start regular creation with size=2K. This model does not use image groups, streaming, or search; for decomposition, then set layer_decomposition=true.
Receive by result type
For single-image tasks, save the image; for decomposition tasks, receive the base image and transparent layers one by one. For asynchronous tasks, save task_id, retrieve results through /seedream/tasks or a callback, and check the alpha channel.
Trial suggestion: layered delivery for a brand poster
Input and goal
Create a tea beverage poster with a transparent glass cup in the center, the title “A Refreshing Cup” in the upper-left corner, space for a description at the bottom, and clear layering among the cup, title, leaves, and background.
Acceptance and next steps
First generate and proofread a single poster, then use the finished image as input for an independent layer decomposition task; check each transparent PNG, base-image completion, and layer hierarchy individually.
Usage Limits
Standard generation with Pro is a single-image task and does not support sequential_image_generation, stream, or tools. Providing multiple reference images in one input does not mean generating multiple related images; when continuous images or online assistance are needed, use a model with the corresponding capabilities.
A transparent background is not a one-click background removal switch for any image: this operation requires inputting a PNG that already has an alpha channel and selecting PNG output. Layer decomposition is a different operation, cannot be used with background at the same time, and should not be mixed with background settings for standard editing.
Layer decomposition requires a single PNG/JPEG. The number of layers depends on the image content, and a maximum of 16 layers is not a fixed delivery quantity. If any layer fails to generate, the entire decomposition fails; after obtaining the result, check the recomposition effect based on the hierarchy and bounding boxes before proceeding with formal design delivery.
Frequently Asked Questions
Can I use the abbreviated name Seedream 5.0 Pro when making calls?
You should pass the full model to POST /seedream/images: doubao-seedream-5-0-pro-260628. Standard generation and editing also require prompt, and assets are submitted through image when editing. Using the full string explicitly selects this version; do not replace the invocation ID with a display name or abbreviation.
Will multiple reference images produce a set of images?
No. Standard generation and editing can accept up to 10 reference images, but the output is still a single image. Reference images are used to guide the subject, style, or composition, and do not represent the number of outputs. To obtain a related image set, choose a Seedream version that supports sequential_image_generation.
How do I set landscape, portrait, and resolution?
For standard generation, you can set size to 1K, 1.5K, or 2K, and describe landscape, portrait, or the target aspect ratio in prompt; you can also use WIDTHxHEIGHT to specify pixel dimensions that meet the requirements. auto is used for layer decomposition and should not be used as a size option for standard Pro generation.
Is a prompt required for layer decomposition?
No. Submit a PNG/JPEG and set layer_decomposition to true for automatic decomposition; add prompt only when you need to focus on specific elements. The result includes a base image, transparent layers, and position information, which can be stacked from bottom to top according to z_index, but this is not equivalent to project files such as PSD.
How can I retrieve generation results without keeping the connection open?
You can set async to true, obtain task_id first, then query the final result through /seedream/tasks; you can also set callback_url to receive completion notifications. Applications should save the task ID to associate requests with images, then read image_url or b64_json after obtaining the result. Do not treat task creation as generation completion.