AI Image Upscaler
Neural network super resolution that adds realistic detail
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How It Works
Our AI upscaler uses Swin2SR, a state-of-the-art neural network model designed for image super resolution. Unlike traditional upscaling that just interpolates pixels, Swin2SR actually generates new detail based on patterns learned from millions of images.
The model runs entirely in your browser using Transformers.js and WebGPU/WebAssembly. On first use, the AI model (~7MB) is downloaded and cached for future sessions.
What is Super Resolution? Super resolution is an AI technique that upscales images while adding realistic detail that wasn't in the original. The neural network has learned from vast image datasets what details typically exist at higher resolutions—like texture in skin, fabric patterns, or fine edges—and synthesizes these into your upscaled image.
Experimental Feature: Browser-based AI upscaling has limited quality compared to native desktop tools like Real-ESRGAN. For critical work, consider using dedicated software for the highest quality results.
Key Features
🧠 AI-Powered
Neural network generates realistic detail, not just interpolated pixels.
📈 4x Upscaling
Enlarge images by 4x in each dimension (16x total pixels).
🔒 Private Processing
AI model runs in your browser. Images never leave your device.
💾 Cached Model
Model downloads once and is cached for instant future use.
Best Use Cases
- Old Photos: Enhance low-resolution scans of old photographs
- Small Web Images: Upscale images downloaded from websites
- Thumbnails: Enlarge thumbnail images to usable sizes
- Screenshots: Increase resolution of screen captures
- Social Media Saves: Enhance compressed images from social platforms
AI Resize vs Standard Resize
Our tools offer two approaches to upscaling:
- AI Resize (this tool): Uses neural networks to generate new detail. Best for extreme upscaling where you want the AI to "fill in" missing information. Results may not be pixel-accurate but look more natural.
- Standard Resize: Uses Lanczos interpolation to preserve existing detail precisely. Best for moderate scaling where accuracy matters more than added detail.
Technical Details
The tool uses:
- Model: Swin2SR-realworld-sr-x4-64-bsrgan-psnr (optimized for real-world photos)
- Framework: Transformers.js by Hugging Face
- Acceleration: WebGPU (if available) or WebAssembly fallback
- Model Size: ~7MB (downloaded and cached on first use)
Processing Time
Processing time varies based on your device and image size:
- Small images (under 256px): 5-15 seconds
- Medium images (256-512px): 15-45 seconds
- Larger images: May take several minutes or fail on limited devices
For best results, start with smaller source images. The AI works best on images under 512px in their largest dimension.
Tips for Best Results
- Start with reasonably sharp source images—AI can't fix motion blur
- Smaller source images often work better than large ones
- Photos of faces and natural scenes tend to upscale well
- Text and sharp graphics may show artifacts—use standard resize instead
- Use a modern browser with WebGPU support for faster processing
Limitations
- Browser-based processing is slower than native applications
- Very large images may exceed browser memory limits
- Results are good but not as refined as desktop tools like Real-ESRGAN
- Generated detail is "hallucinated" by the AI—not recovered original data
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