AI Image Upscaler: Enlarge Photos Without Losing Quality
Upscale images 2x or 4x in your browser using an AI super-resolution model. No upload needed.
Increase your image resolution using ESRGAN, a neural network trained to reconstruct detail that plain resizing cannot invent. Choose 2x or 4x, upload a photo, and the model runs entirely in your browser on TensorFlow.js. Works on photos, illustrations, and pixel art. No file ever leaves your device.
Standard resizing (bilinear or bicubic interpolation) blurs an image when you scale it up because it has no information about what the missing pixels should look like. AI super-resolution uses a convolutional neural network trained on millions of image pairs to predict plausible high-frequency detail at the target size. The result keeps edges sharp, recovers texture, and avoids the mushy look of plain upscaling.
This tool uses ESRGAN-Slim, a lightweight variant of Enhanced Super-Resolution GAN, running on TensorFlow.js in your browser. The model processes your image in 64-pixel patches with a 2-pixel overlap to avoid seams, which also keeps peak memory usage low and lets the progress bar update as each patch completes. First-run downloads the model (roughly 6-12 MB depending on scale factor) and caches it in your browser, so subsequent runs are faster.
Results are best on photographs, product shots, and illustrations with clean lines. Very low-resolution source images (under 100 px on either side) tend to show the model's limits because there is little signal to amplify. For those cases, run a 2x pass first, inspect the result, then optionally run another pass.
- 1
Choose a scale and upload your image
Select 2x or 4x from the scale menu, then pick an image file from your device. Images wider or taller than 2000 px are rejected to prevent tab crashes.
- 2
Run the upscaler
Click Upscale. On the first run the neural network model downloads and caches in your browser. Processing happens in patches and shows a progress percentage as each tile completes.
- 3
Download the result
When processing finishes, the upscaled image appears alongside the original for comparison. Click Download PNG to save it at the new resolution.
Printing small photos at larger sizes
Recover enough resolution to print a 1 MP camera or screenshot image at A4 without obvious pixelation.
Improving old or compressed images
Sharpen JPEG-compressed or heavily downsized images before publishing them on a website or presentation.
Game asset preparation
Scale up pixel art sprites or low-res textures for use in higher-resolution display contexts.
Privacy-sensitive content
Process medical, legal, or personal images without uploading them to any third-party server.
Does my image get uploaded anywhere?
No. The neural network runs entirely in your browser via TensorFlow.js. Your image never leaves your device.
How is this different from plain image resizing?
Plain resizing (bilinear or bicubic) averages nearby pixels, which blurs edges. AI super-resolution predicts plausible fine detail by pattern-matching against what the model learned during training, so edges stay sharper and textures look more natural.
Why does the first run take a while?
The ESRGAN model weights (around 6-12 MB depending on the scale factor) download on the first run and are cached by your browser. Subsequent runs on the same device skip the download.
Why is there a 2000 px input limit?
At 4x scale a 2000-px image becomes 8000 px, which requires several hundred megabytes of GPU memory. Larger inputs reliably crash browser tabs. Use the Image Resizer tool to bring the image within limits first.
What output format does the tool produce?
The download is always a PNG, which is lossless and preserves any detail the model reconstructs. If you need JPG or WebP, convert the result with the Image Converter tool.