# Upscayl — Free Open-Source AI Image Upscaler

> A cross-platform desktop application that uses AI models to upscale and enhance images locally without sending data to the cloud.

## Install

Save as a script file and run:

# Upscayl — Free Open-Source AI Image Upscaler

## Quick Use
```bash
# Linux (Flatpak)
flatpak install flathub org.upscayl.Upscayl

# macOS
brew install --cask upscayl

# Windows — download the installer from GitHub Releases
# Then: open Upscayl, drop an image, pick a model, click Upscale
```

## Introduction
Upscayl is a free, open-source desktop application that upscales images using AI super-resolution models. It runs entirely on your local machine using Vulkan-based GPU acceleration, so your images never leave your device. Upscayl supports Linux, macOS, and Windows.

## What Upscayl Does
- Upscales images by 2x, 3x, or 4x using AI super-resolution models
- Processes single images or entire folders in batch mode
- Runs inference locally using Real-ESRGAN and other NCNN-based models
- Provides a before-and-after comparison slider for quality review
- Exports results in PNG, JPG, or WebP formats

## Architecture Overview
Upscayl is built with Electron for the desktop shell and uses Real-ESRGAN-ncnn-vulkan as the inference backend. The Vulkan-based compute pipeline runs on most GPUs across vendors (NVIDIA, AMD, Intel) without requiring CUDA. The application spawns the upscaling binary as a child process, streaming progress updates back to the UI.

## Self-Hosting & Configuration
- Install from Flatpak, Homebrew, or the GitHub Releases page
- Select from built-in models or load custom NCNN models
- Configure output format, scale factor, and compression quality
- Set a default output directory for processed images
- Adjust GPU thread count for performance tuning on multi-GPU systems

## Key Features
- No cloud dependency — all processing happens on-device
- Vulkan backend works across NVIDIA, AMD, and Intel GPUs
- Batch upscaling for processing entire directories at once
- Support for custom models in NCNN format
- Built-in comparison view to inspect upscale quality

## Comparison with Similar Tools
- **Topaz Gigapixel AI** — commercial and paid; Upscayl is completely free and open source
- **waifu2x** — older model architecture; Upscayl uses newer Real-ESRGAN models with better results
- **Real-ESRGAN CLI** — command-line only; Upscayl wraps it in a user-friendly desktop GUI
- **ChaiNNer** — node-based image processing; Upscayl is simpler for one-click upscaling

## FAQ
**Q: Does Upscayl require a dedicated GPU?**
A: A Vulkan-compatible GPU is strongly recommended. CPU-only mode exists but is very slow.

**Q: What image formats does Upscayl support?**
A: Input supports PNG, JPG, WebP, and AVIF. Output can be PNG, JPG, or WebP.

**Q: Can I add custom AI models?**
A: Yes. Place NCNN-format model files in the custom models directory and they appear in the model selector.

**Q: How large can input images be?**
A: It depends on GPU VRAM. For images larger than 4K, Upscayl automatically tiles the image to fit available memory.

## Sources
- https://github.com/upscayl/upscayl
- https://upscayl.org

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Source: https://tokrepo.com/en/workflows/asset-56b0779f
Author: Script Depot