A comprehensive AI toolkit for upscaling, restoring, and increasing image resolution via high-performance inference models.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install image-upscaling
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install image-upscaling using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Image Upscaling?
The Image Upscaling skill enables developers to integrate state-of-the-art super-resolution models directly into their local development workflows. By leveraging Openclaw Skills, users gain access to professional-grade tools like Topaz Image Upscaler and Real-ESRGAN through a unified CLI interface. This skill is designed to transform low-resolution assets into high-fidelity images suitable for print, web, and professional media production.
Whether you are refining AI-generated art or restoring legacy photographs, this skill provides a seamless bridge to cloud-based inference. It eliminates the need for expensive local hardware while providing the flexibility of a command-line interface, making it an essential component for automated media pipelines and creative coding projects.
Image Upscaling Use Cases
- Scaling up AI-generated images to meet high-resolution print requirements
- Restoring and enhancing old, blurry, or pixelated photographs
- Preparing web assets for high-DPI displays and 4K monitors
- Creating high-resolution thumbnails and preview images from compressed sources
- Building automated pipelines that generate and then immediately upscale media
How Image Upscaling Works
- Install the inference.sh CLI and authenticate your session.
- Select a target upscaling model such as Topaz Image Upscaler or Real-ESRGAN based on the image content.
- Execute the CLI command providing the source image URL or local path as an input parameter.
- The skill processes the image through the selected AI model on high-performance cloud infrastructure.
- Receive a direct link or file path to the enhanced, high-resolution output.
Image Upscaling Setup
To get started with this skill, install the CLI and log in to your account:
curl -fsSL https://cli.inference.sh | sh && infsh login
Once authenticated, you can run the upscaler directly:
infsh app run falai/topaz-image-upscaler --input '{"image_url": "https://your-image.jpg"}'
Image Upscaling Data Schema & Taxonomy
The skill utilizes a structured JSON schema for inputs and outputs to ensure compatibility within the Openclaw Skills framework:
| Attribute | Description |
|---|---|
| image_url | The source URL or path of the image to be processed. |
| app_id | The identifier for the specific upscaling model (e.g., infsh/real-esrgan). |
| output_url | The URL pointing to the final enhanced high-resolution image. |
| model_params | Optional configuration for specific model behaviors like scale factor. |
Image Upscaling Advanced Features
- Multi-agent workflow support: Pipe output from image generation skills directly into the upscaling skill.
- Support for specialized models including FLUX Dev Upscaler and Thera for varying image types.
- Headless CLI execution for integration into CI/CD pipelines and backend automation.
- Automated platform detection and binary verification for secure, cross-platform performance.
SKILL.md
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