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real-esrgan

Real Esrgan - Face Enhancer

Real Esrgan improves facial features and details in images, delivering crisp and realistic results.

Avg Run Time: 16.000s

Model Slug: real-esrgan

Category: Image to Image

Input

Enter an URL or choose a file from your computer.

Advanced Controls
Sign Up to Run

Output

Example Result

Preview and download your result.

Preview
The total cost depends on how long the model runs. It costs $0.000247 per second. Based on an average runtime of 16 seconds, each run costs about $0.003960. With a $1 budget, you can run the model around 252 times.

Create a Prediction

Send a POST request to create a new prediction. This will return a prediction ID that you'll use to check the result. The request should include your model inputs and API key.

Get Prediction Result

Poll the prediction endpoint with the prediction ID until the result is ready. The API uses long-polling, so you'll need to repeatedly check until you receive a success status.

Table of Contents
Overview
Technical Specifications
Key Considerations
Tips & Tricks
Capabilities
What Can I Use It For?
Things to Be Aware Of
Limitations

Overview

GFPGAN (Generative Facial Prior) is a powerful AI model designed to restore faces in images, particularly for repairing old, damaged, or low-quality photographs. Leveraging cutting-edge deep learning technology, GFPGAN reconstructs facial details with high accuracy while maintaining natural aesthetics.

Technical Specifications

  • Model Architecture:
    • Built on GAN architecture with pre-trained facial prior integration.
    • Refined loss functions to balance restoration and fidelity.
  • Input Requirements:
    • Resolution: Recommended input is up to 512x512 for optimal performance.
  • Output Features:
    • Restored images maintain original context and backgrounds.
    • Faces are enhanced with reconstructed features.

Key Considerations

Over-Restoration:

  • In some cases, the restored face might deviate slightly from the original.

Context Preservation:

  • Non-facial regions are minimally processed. Ensure the background meets the desired quality before input.

Data Preprocessing: Ensure that input images are properly aligned and cropped to focus on facial regions for optimal restoration results.

Tips & Tricks

Pre-Processing:

  • Crop images to focus on faces for better results.

Upscaling:

  • Combine GFPGAN with super-resolution tools like Real-ESRGAN for higher-quality results.
  • Parameter Settings:
    • Scale: Use a scale factor (e.g., 2 or 4) to control the upsampling level during restoration.
    • Version: Select the appropriate model version based on your quality requirements and system capabilities.

Capabilities

Face Restoration:

  • Repairs old, blurry, or degraded photographs with precision.

Detail Enhancement:

  • Reconstructs eyes, lips, and skin textures while preserving natural aesthetics.

Real-Time Performance:

  • Processes images quickly, even for complex restorations.

Integration:

  • Easily integrates with workflows for photo editing, animation, and digital art.

What Can I Use It For?

Photo Restoration:

  • Revive old family photos or historical archives with clear, enhanced faces.

Content Creation:

  • Enhance facial features in digital art, animations, or social media posts.

AI-Assisted Editing:

  • Use GFPGAN as part of a broader image editing pipeline.

Things to Be Aware Of

Restore Historical Photos:

  • Repair damaged or faded portraits with remarkable clarity.

Upscale Low-Quality Images:

  • Combine with tools like Real-ESRGAN for full-resolution restoration.

Test on Artistic Styles:

  • Experiment with restoring faces in paintings or digital artwork.

Batch Process Family Albums:

  • Restore multiple images simultaneously to save time.

Custom Model Training:

  • Fine-tune GFPGAN for specific restoration tasks or artistic styles.

Limitations

Non-Facial Regions:

  • Backgrounds and non-facial details are not significantly enhanced.

Extreme Damage:

  • Severely damaged faces may require additional manual editing.

Artistic Output:

  • In some cases, the restored faces might look slightly stylized or synthetic.


Output Format: PNG

Pricing Detail

This model runs at a cost of $0.000247 per second.

The average execution time is 16 seconds, but this may vary depending on your input data.

The average cost per run is $0.003960

Pricing Type: Execution Time

Cost Per Second means the total cost is calculated based on how long the model runs. Instead of paying a fixed fee per run, you are charged for every second the model is actively processing. This pricing method provides flexibility, especially for models with variable execution times, because you only pay for the actual time used.

Real Esrgan - Face Enhancer | AI Model | Eachlabs