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Clarity Ai Crystal Upscaler

Clarity Ai Crystal Upscaler

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Clarity AI Crystal Upscaler boosts image resolution with AI upscaling and adjustable detail for portraits and landscapes. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Clarity AI Crystal Upscaler

Clarity AI Crystal Upscaler enhances and enlarges images with a megapixel-based output target and adjustable creativity control. It is designed for photo restoration, product image enhancement, print preparation, archival cleanup, and other workflows where you want a sharper, larger final image with predictable output sizing.


Why Choose This?

  • Megapixel-based output control
    Choose the target output size directly in megapixels for more predictable delivery planning.

  • Clean high-resolution enhancement
    Improve sharpness, detail, and overall clarity for photos, scans, product visuals, and creative assets.

  • Creativity adjustment
    Use creativity to balance strict source preservation against more generated detail.

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

  • Production-ready API
    Suitable for restoration, publishing, e-commerce, design, and large-format image workflows.


Parameters

ParameterRequiredDescription
imageYesInput image to upscale.
target_megapixelsNoRequested output size in megapixels. Range: 1–1500 MP. Default: 4.
creativityNoNegative values stay stricter to the source; positive values add more generated detail. Range: 0 to 10. Default: 0.

How to Use

  1. Upload your image — provide the source image you want to enhance.
  2. Choose target megapixels — select the output size that best matches your delivery needs.
  3. Adjust creativity (optional) — keep it lower for more faithful restoration, or raise it for stronger generated detail.
  4. Submit — run the model and download the upscaled image.

Example Use Case

Upscale a product photo for print and marketing use while preserving clean edges, surface texture, and overall realism.


Pricing

Pricing is based on the selected target_megapixels tier.

Target MegapixelsCost
<= 4 MP$0.05
> 4 MP and <= 16 MP$0.20
> 16 MP and <= 36 MP$0.80
> 36 MP and <= 100 MP$1.60
> 100 MP and <= 400 MP$6.40
> 400 MP$24.00

Billing Rules

  • Pricing depends on the selected target_megapixels
  • Cost uses fixed megapixel tiers rather than scaling linearly
  • Crossing into a higher megapixel tier moves the request to the next price bracket
  • creativity does not affect pricing

Best Use Cases

  • Photo upscaling — Improve clarity and output size for photography and scanned images.
  • Product image enhancement — Prepare sharper visuals for listings, ads, and catalogs.
  • Print preparation — Generate larger files for posters, signage, and premium print work.
  • Archival restoration — Improve older or lower-resolution source images for reuse.
  • Creative asset production — Produce larger, cleaner visuals for design and publishing workflows.

Pro Tips

  • Start with a lower megapixel target first, then increase only if you need a larger final output.
  • Keep creativity near 0 when you want a more natural, source-faithful result.
  • Lower creativity when preserving structure, faces, logos, or product accuracy matters most.
  • Raise creativity gradually when you want stronger generated texture or enhancement.
  • Use the cleanest source image available for better detail recovery.

Notes

  • image is required.
  • target_megapixels supports values from 1 to 1500.
  • creativity ranges from 0 to 10.
  • Pricing depends only on the selected megapixel tier.
  • Higher megapixel targets may be more suitable for print, presentation, or premium delivery workflows.

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/crystal-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 ~ 1500Requested output size in megapixels. Range: 1-1500 MP.
creativitynumberNo-0.0 ~ 10.0Controls generated detail strength. Crystal supports values from 0 to 10; higher 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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