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Clarity Ai Pro Upscaler

Clarity Ai Pro Upscaler

Playground

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Clarity Pro Upscaler is a photorealistic image upscaler from Clarity AI with identity preservation, creative detail control, and up to 16x scaling. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Clarity AI Pro Upscaler

Clarity AI Pro Upscaler upscales images with Clarity AI while exposing a simple target_megapixels control for predictable output sizing. The backend prepares the input and selects the appropriate upstream scaling settings so the final image lands close to the requested megapixel target.


Why Choose This?

  • Predictable output sizing Set the desired output directly with target_megapixels for easier delivery planning and cost control.

  • Simple enhancement workflow Upload an image, choose the target megapixels, optionally adjust creativity, and generate the result.

  • Flexible restoration strength Use creativity to balance stricter source preservation against stronger generated detail.

  • Reliable output delivery Generated images are rehosted to the WaveSpeed CDN for fast preview and download.

  • Modern Clarity AI pipeline Powered by the latest Clarity AI workflow with RunPod-backed execution.


Parameters

ParameterRequiredDescription
imageYesInput image URL or uploaded image.
target_megapixelsNoRequested output size in megapixels. Use 4 MP for quick tests, 8–16 MP for high-quality web or print assets, and larger values for large-format delivery.
creativityNoNegative values stay closer to the source, while positive values add more generated detail.

How to Use

  1. Upload your image — paste a URL or upload the source image.
  2. Choose target megapixels — select the output size that matches your delivery needs.
  3. Adjust creativity (optional) — lower values keep the result stricter to the source, while higher values add more generated detail.
  4. Submit — run the model and download the upscaled image.

Quick Sizing Guide

  • 4 MP — fast testing and lightweight output
  • 8–16 MP — high-quality web, e-commerce, and standard print assets
  • 25 MP+ — large-format delivery and premium output needs

Pricing

Pricing is based on the requested target_megapixels.

  • Rate: $0.03 per target megapixel

Example Costs

Target MegapixelsCost
4 MP$0.12
8 MP$0.24
16 MP$0.48
64 MP$1.92

Billing Rules

  • Pricing scales linearly with target_megapixels
  • Each additional megapixel adds $0.03
  • creativity does not affect pricing

Best Use Cases

  • Photo enhancement — improve resolution while preserving structure and natural detail
  • E-commerce assets — prepare sharper product images for listings, ads, and catalogs
  • Creative delivery — generate larger outputs for campaigns, presentations, and design workflows
  • Print preparation — produce higher-resolution assets for brochures, posters, and other print use
  • AI image cleanup — refine generated images into cleaner, more usable high-resolution outputs

Pro Tips

  • Start with a smaller megapixel target first, then increase only when you need a larger final output.
  • Keep creativity lower when identity, structure, or product accuracy matters most.
  • Increase creativity gradually if you want stronger generated texture or sharper enhancement.
  • Use the cleanest source image available for better detail recovery.

Notes

  • The backend may resize the input before calling Clarity AI so the upstream output stays close to the requested target_megapixels.
  • Clean, high-quality inputs generally produce the best results.
  • Output size is controlled by the requested megapixel target rather than a fixed resolution tier.

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/clarity-ai/pro-upscaler" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "target_megapixels": 4,
    "creativity": 0
}'

# 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
imagestringYes-Input image to upscale.
target_megapixelsnumberNo41 ~ 64Requested output size in megapixels. Range: 1-64 MP.
creativitynumberNo--10.0 ~ 10.0Negative values stay stricter to the source; positive values add more generated detail.

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 (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
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