Starlight Sharp

Fast local restoration with sharper detail for clean, progressive video

Model Overview

Starlight Sharp is a diffusion-based video enhancement model optimized for local or cloud processing. It is designed to sharpen low-res blurry videos and improve clarity on small faces.

Starlight Sharp is used for restoration, detail recovery and compression cleanup. Unlike Mini, Starlight Sharp assumes a progressive input and does not perform automatic deinterlacing.

Key Capabilities

• Local first diffusion-based restoration optimized for speed and sharp detail

• Restores clarity in degraded or low resolution footage

• Best suited for progressive or pre-deinterlaced sources in local desktop workflow

Pricing

Frames Per Credit — 1080p	Frames Per Credit — 4k
~26	~12

For more accurate estimates we recommend checking out our Credit Calculator.

Getting Started

Endpoint

• https://api.topazlabs.com/video/

  • model — "wonder-1"

Model-Specific Parameters

• start_idx — integer, default 0

• end_idx — decimal, default 1000000.0

• upscaling_factor — decimal, default 1.0

• low_sharpness — boolean, default false

• keep_original — boolean, default false

• ffmpeg_encoding — string, optional

• wm_path — string, optional

• ffmpeg_preproc_filters — string, default ""

Examples

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