Overview
Bria’s Image Generation API provides builders with a flexible and controllable way to generate high-quality visuals from textual prompts or reference images.
It supports various resolutions, aspect ratios, and generation speeds, enabling scalable and efficient production of photos, illustrations, and vector graphics for commercial use.
Advanced Customization and Access:
As part of Bria’s Source Code & Weights product, developers seeking deeper customization can access Bria’s source-available GenAI models via Hugging Face.
This allows full control over fine-tuning, pipeline creation, and integration into proprietary workflows—empowering AI teams to develop and optimize their own generative AI solutions.
Some of the APIs below support various guidance methods to provide greater control over generation. These methods enable to guide the generation using not only a textual prompt, but also visuals.
The following APIs support guidance methods:
/text-to-image/base/text-to-image/fast/text-to-vector/base/text-to-vector/fast
ControlNets:
A set of methods that allow conditioning the model on additional inputs, providing detailed control over image generation.
- controlnet_canny: Uses edge information from the input image to guide generation based on structural outlines.
- controlnet_depth: Derives depth information to influence spatial arrangement in the generated image.
- controlnet_recoloring: Uses a grayscale version of the input image to guide recoloring while preserving geometry.
- controlnet_color_grid: Extracts a 16x16 color grid from the input image to guide the color scheme of the generated image.
You can specify up to two ControlNet guidance methods in a single request. Each method requires an accompanying image and a scale parameter to determine its impact on the generation inference.
When using multiple ControlNets, all input images must have the same aspect ratio, which will determine the aspect ratio of the generated results.
To use ControlNets, include the following parameters in your request:
guidance_method_X: Specify the guidance method (where X is 1, 2). If the parameterguidance_method_2is used,guidance_method_1must also be used. If you want to use only one method, useguidance_method_1.guidance_method_X_scale: Set the impact of the guidance (0.0 to 1.0).guidance_method_X_image_file: Provide the base64-encoded input image.
| Guidance Method | Prompt | Scale | Input Image | Guidance Image | Output Image |
|---|---|---|---|---|---|
| ControlNet Canny | An exotic colorful shell on the beach | 1.0 |  |  |  |
| ControlNet Depth | A dog, exploring an alien planet | 0.8 |  |  |  |
| ControlNet Recoloring | A vibrant photo of a woman | 1.00 |  |  |  |
| ControlNet Color Grid | A dynamic fantasy illustration of an erupting volcano | 0.7 |  |  |  |
Image Prompt Adapter:
This method offers two modes:
- regular: Uses the image’s content, style elements, and color palette to guide generation.
- style_only: Uses the image’s high-level style elements and color palette to influence the generated output.
To use Image Prompt Adapter as guidance, include the following parameters in your request:
image_prompt_mode: Specify how the input image influences the generation.image_prompt_scale: Set the impact of the provided image on the generated result (0.0 to 1.0).image_prompt_file: Provide the base64-encoded image file to be used as guidance.
or
image_prompt_urls: Provide a list of URLs pointing to publicly accessible images to be used as guidance.
| Guidance Method | Prompt | Mode | Scale | Guidance Image | Output Image |
|---|---|---|---|---|---|
| Image Prompt Adapter | A drawing of a lion laid on a table. | regular | 0.85 |  |  |
| Image Prompt Adapter | A drawing of a bird. | style | 1 |  |  |
https://engine.prod.bria-api.com/v1/