Super Focus 2

A generative model that fixes blur and reconstructs detail in the most stubborn images, providing an alternative solution when traditional sharpening models cannot recover usable results

Model Overview

Super Focus 2 is a generative AI feature that fixes blur and reconstructs detail in the most stubborn images, providing an alternative solution when traditional sharpening models cannot recover usable results.

Key Capabilities

  • Recovers detail from severely blurred or out-of-focus images that other sharpening approaches fail to enhance

  • Uses generative reconstruction to rebuild edges and textures without introducing halos or excessive noise

  • Best suited for difficult, single-image recovery cases where faster sharpening methods do not deliver acceptable results

Model Pricing

Output MP

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64
100

Credits

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Getting Started

Endpoint

chevron-rightEndpoint-Specific Parametershashtag
  • denoise_strength — decimal between 0 and 1, default 0.5

    • Removes noise from the image.

  • face_enhancement — boolean

    • Leverages our face recovery model to enhance faces.

  • face_enhancement_strength — decimal between 0 and 1

    • Sets the strength of the face recovery.

  • face_enhancement_creativity — decimal between 0 and 1

    • Choose realistic or creative face recovery.

  • subject_detection"All", "Foreground", or "Background"

    • Choose where enhancements are applied.

These parameters should be appended as key-value fields in the form-data request bodies (i.e. alongside the model, output_height, and face_enhancement etc. fields). Any parameters not explicitly provided are automatically configured by our auto-parameter model. Extra parameters provided that are not supported are ignored.

Model-Specific Parameters

  • detail — decimal between 0 and 1

    • Increases details. Too much sharpening can create an unrealistic result.

  • focus_boost — decimal between 0.25 and 1

    • Use on very blurry images! Focus boost corrects images that are missing detail by downscaling your image then upscaling the results back to the original size.

Resolution Limits

  • input — 256 MP

  • output — 256 MP

Examples

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