Uno
Playground
Try it on WavespeedAI!An AI model that transforms input images into new ones based on text prompts, blending reference visuals with your creative directions.
Features
UNO – Universal In‑Context Diffusion Transformer 📸
A powerful subject-driven image synthesis model (developed by ByteDance Research) enabling both single-subject and multi-subject image generation with high consistency and controllability using diffusion transformers.
Implementation ✨
This model leverages a two-stage progressive cross‑modal alignment strategy, combined with Universal Rotary Position Embedding (UnoPE):
- Stage I: Fine-tune a pretrained T2I (text-to-image) model using generated single-subject in-context data.
- Stage II: Further train on multi-subject paired data to support scenes with multiple specified subjects. :contentReference[oaicite:1]{index=1}
Highlights:
- Built on Diffusion Transformers (DiT) with FLUX.1-dev backbone
- UnoPE maintains subject identity and reduces confusion across multiple subjects :contentReference[oaicite:2]{index=2}
- Input: 1–4 reference images + text prompt
- Output: synthesized image reflecting consistent subject(s) in context
Key Features
- ✅ High-consistency, multi-subject generation—preserves unique subject traits across images :contentReference[oaicite:3]{index=3}
- 🔁 Single → multi subject scaling via staged training
- 🔧 Controllable layout and reference identity handling
- 📐 Handles varying aspect ratios and resolutions (512–704px+) :contentReference[oaicite:4]{index=4}
Predictions Examples 🌟
- Generating images of the same person in different settings
- Placing multiple consistent products or characters in a single scene
- Virtual try-on and identity-preserving e-commerce renders
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/uno" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"images": [
"https://d3gnftk2yhz9lr.wavespeed.ai/media/f82c31a9020c49459ec9e57f26d0a22f/images/1747919962008035794_JwNJFBxu.png",
"https://d1q70pf5vjeyhc.wavespeed.ai/media/images/1753248290087456291_L3upsplh.png",
"https://d1q70pf5vjeyhc.wavespeed.ai/media/images/1753248294014875604_lAPMIGEA.png"
],
"image_size": "square_hd",
"prompt": "A woman wears the dress and holds a bag, in the flowers.",
"num_images": 1,
"num_inference_steps": 28,
"guidance_scale": 3.5,
"output_format": "jpeg",
"enable_safety_checker": true
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"
Parameters
Task Submission Parameters
Request Parameters
Parameter | Type | Required | Default | Range | Description |
---|---|---|---|---|---|
images | array | Yes | https://d3gnftk2yhz9lr.wavespeed.ai/media/f82c31a9020c49459ec9e57f26d0a22f/images/1747919962008035794_JwNJFBxu.pnghttps://d1q70pf5vjeyhc.wavespeed.ai/media/images/1753248290087456291_L3upsplh.pnghttps://d1q70pf5vjeyhc.wavespeed.ai/media/images/1753248294014875604_lAPMIGEA.png | - | URL of images to use while generating the image. |
image_size | string | No | square_hd | - | The aspect ratio of the generated image. |
prompt | string | Yes | - | The prompt to generate an image from. | |
seed | integer | No | - | -1 ~ 2147483647 | The random seed to use for the generation. |
num_images | integer | No | 1 | 1 ~ 4 | The number of images to generate. |
num_inference_steps | integer | No | 28 | 1 ~ 50 | The number of inference steps to perform. |
guidance_scale | number | No | 3.5 | 1 ~ 20 | The guidance scale to use for the generation. |
output_format | string | No | jpeg | - | The format of the output image. |
enable_safety_checker | boolean | No | true | - | If set to true, the safety checker will be enabled. |
Response Parameters
Parameter | Type | Description |
---|---|---|
code | integer | HTTP status code (e.g., 200 for success) |
message | string | Status message (e.g., “success”) |
data.id | string | Unique identifier for the prediction, Task Id |
data.model | string | Model ID used for the prediction |
data.outputs | array | Array of URLs to the generated content (empty when status is not completed ) |
data.urls | object | Object containing related API endpoints |
data.urls.get | string | URL to retrieve the prediction result |
data.has_nsfw_contents | array | Array of boolean values indicating NSFW detection for each output |
data.status | string | Status of the task: created , processing , completed , or failed |
data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
data.error | string | Error message (empty if no error occurred) |
data.timings | object | Object containing timing details |
data.timings.inference | integer | Inference time in milliseconds |
Result Query Parameters
Result Request Parameters
Parameter | Type | Required | Default | Description |
---|---|---|---|---|
id | string | Yes | - | Task ID |
Result Response Parameters
Parameter | Type | Description |
---|---|---|
code | integer | HTTP status code (e.g., 200 for success) |
message | string | Status message (e.g., “success”) |
data | object | The prediction data object containing all details |
data.id | string | Unique identifier for the prediction, the ID of the prediction to get |
data.model | string | Model ID used for the prediction |
data.outputs | array | Array of URLs to the generated content (empty when status is not completed ) |
data.urls | object | Object containing related API endpoints |
data.urls.get | string | URL to retrieve the prediction result |
data.has_nsfw_contents | array | Array of boolean values indicating NSFW detection for each output |
data.status | string | Status of the task: created , processing , completed , or failed |
data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
data.error | string | Error message (empty if no error occurred) |
data.timings | object | Object containing timing details |
data.timings.inference | integer | Inference time in milliseconds |