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Pruna Ai P Image Edit

Pruna Ai P Image Edit

Playground

Try it on WavespeedAI!

Pruna AI P-Image Edit is a fast AI image editing model that edits and transforms images based on text instructions and reference images. Ready-to-use REST inference API for photo retouching, creative edits, product image updates, background changes, marketing assets, and AI image editing workflows with simple integration, no coldstarts, and affordable pricing.

Features

Pruna AI P-Image Edit

Pruna AI P-Image Edit transforms one or more reference images using natural-language editing instructions. It is designed for image modification workflows such as outfit changes, style transfer, object replacement, visual refinement, and other prompt-guided image edits.


Why Choose This?

  • Prompt-driven image editing Edit images by describing exactly what you want to change in natural language.

  • Multi-image reference support Upload one or more images to guide the edit, making it easier to preserve identity, style, or visual consistency.

  • Flexible aspect ratio control Choose the output aspect ratio that best fits your use case.

  • Multiple output formats Export the edited image in a supported format such as png.

  • Seed support for reproducibility Use seed to get more consistent results across repeated edits.

  • Simple fixed pricing Each edit run uses a straightforward per-image price.


Parameters

ParameterRequiredDescription
promptYesText instruction describing the desired edit.
imagesYesOne or more reference images used for the edit.
aspect_ratioNoOutput aspect ratio for the edited image.
output_formatNoOutput image format, such as png.
seedNoRandom seed for reproducibility. Use the same seed to get more consistent results.

How to Use

  1. Upload your reference images — provide one or more images you want to use for the edit.
  2. Write your prompt — describe what should change and what should stay consistent.
  3. Choose aspect ratio (optional) — select the output ratio that matches your target use case.
  4. Choose output format (optional) — select the format that best fits your workflow.
  5. Set a seed (optional) — use a fixed seed for more reproducible results.
  6. Submit — run the model and download the edited image.

Example Prompt

Change the figure 1 man’s suit to the clothes in figure 2.


Pricing

Just $0.01 per image.


Best Use Cases

  • Outfit and apparel changes — Replace clothing or accessories while preserving the subject.
  • Style transfer — Apply the look or styling of one image to another.
  • Visual refinement — Improve or adjust details using prompt-based instructions.
  • Character consistency edits — Modify appearance while keeping identity and composition stable.
  • Creative image adaptation — Rework an existing image into a new variation for marketing, design, or social content.
  • Reference-guided editing — Use multiple images when you need stronger control over the desired result.

Pro Tips

  • Be specific about what should change and what should remain unchanged.
  • If using multiple images, make sure each image clearly supports the edit you want.
  • Mention identity, clothing, background, or composition explicitly when consistency matters.
  • Use the same seed when you want to iterate on an edit with more consistent outputs.
  • Keep prompts short and direct for simple edits, and add more detail only when necessary.

Notes

  • Both prompt and images are required.
  • images can include one or more reference images.
  • seed helps with reproducibility but may not guarantee identical results in every case.
  • Pricing is fixed at $0.01 per image.

  • Pruna AI P-Image Text-to-Image — Generate new images directly from natural-language prompts.
  • Other Pruna AI image generation and image editing models may be useful when you need different quality, speed, or workflow trade-offs.

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/pruna-ai/p-image/edit" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "aspect_ratio": "match_input_image",
    "output_format": "png",
    "seed": -1,
    "enable_sync_mode": false,
    "enable_base64_output": false
}'

# 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

ParameterTypeRequiredDefaultRangeDescription
promptstringYes-Edit instruction.
imagesarrayYes[]1 ~ 5 itemsReference image URLs. Upload 1 to 5 images.
aspect_ratiostringNomatch_input_imagematch_input_image, 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3Aspect ratio of the generated image.
output_formatstringNopngpng, jpeg, webpOutput image format.
seedintegerNo-1-1 ~ 2147483647Random seed. -1 means random.
enable_sync_modebooleanNofalse-If set to true, the function will wait for the result to be generated and uploaded before returning the response. It allows you to get the result directly in the response. This property is only available through the API.
enable_base64_outputbooleanNofalse-If enabled, the output will be encoded into a BASE64 string instead of a URL. This property is only available through the API.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayArray of URLs to the generated content (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Request Parameters

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction, the ID of the prediction to get
data.modelstringModel ID used for the prediction
data.outputsstringArray of URLs to the generated content.
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
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