Super Focus 2

Generative blur recovery for severely blurred images

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	1	4	8	16	24	32	40	50	64	100
Credits	1	1	1	1	2	2	2	3	4	5

Getting Started

Endpoint

• https://api.topazlabs.com/image/v1/sharpen-gen/async

  • model — "Super Focus V2"

Endpoint-Specific Parameters

• denoiseStrength — decimal between 0 and 1, default 0.5

  • Removes noise from the image.

• faceEnhancement — boolean

  • Leverages our face recovery model to enhance faces.

• faceEnhancementStrength — decimal between 0 and 1

  • Sets the strength of the face recovery.

• faceEnhancementCreativity — decimal between 0 and 1

  • Choose realistic or creative face recovery.

• subjectDetection — "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, outputHeight, and faceEnhancement 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.

• focusBoost — 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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