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Restore an old photo
GFPGAN

GFPGAN

Enhance and restore old photos and AI-generated faces

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What is GFPGAN ?

GFPGAN is a cutting-edge AI-based tool designed specifically for restoring and enhancing old photos as well as improving AI-generated faces. It leverages advanced deep learning techniques to bring new life to degraded or low-quality images, making them sharper, clearer, and more visually appealing.

Features

• Enhance Old Photos: Revitalize faded, blurry, or damaged photos to their former glory. • Restore AI-Generated Faces: Improve the quality and realism of faces generated by AI models. • Noise Reduction: Effectively remove noise and artifacts from images. • Sharpness and Clarity: Automatically adjust and enhance image sharpness for crisper results. • Color Correction: Balance and improve color tones to make images look more natural. • User-Friendly: Designed for both novice users and professionals.

How to use GFPGAN ?

  1. Prepare Your Image: Upload or select the old photo or AI-generated image you want to enhance.
  2. Select the Model: Choose the appropriate GFPGAN model based on your image type (e.g., general photo or face-focused).
  3. Run the Model: Process the image using GFPGAN. The tool will automatically enhance and restore it.
  4. Review and Adjust: Preview the results and make any necessary adjustments to settings or parameters.
  5. Save the Output: Download the restored image once you’re satisfied with the result.

Frequently Asked Questions

1. What file formats does GFPGAN support?
GFPGAN supports common image formats like JPEG, PNG, and BMP. Ensure your input image is in one of these formats for optimal processing.

2. How do I get the best results when using GFPGAN?
For best results, use high-quality input images and experiment with different models or parameters offered by GFPGAN to suit your needs.

3. Can GFPGAN fix heavily damaged photos?
Yes, GFPGAN is capable of restoring heavily damaged photos, but outcomes may vary depending on the extent of the damage. For severely degraded images, results may be more approximate.

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