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AI for Artists
/Technical Parameters
/Quality Control

Quality Control

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Quality Control

Various technical options help ensure the highest possible quality in your generated images. These settings affect the final rendering, refinement, and enhancement of AI-created visuals.

  • Denoising Strength: Controls how much an image changes during img2img generation (0.0-1.0).
  • Noise Schedule: Advanced parameter affecting how noise is managed during the diffusion process.
  • VAE Selection: Different Variational Autoencoders affect color reproduction and final rendering quality.
  • Upscaling Methods: Techniques to increase resolution while preserving or enhancing details.
  • Face Restoration: Specialized algorithms to improve facial features in portraits.
  • Artifact Removal: Processes to eliminate unwanted visual glitches or errors.
  • Color Correction: Adjustments to ensure accurate and appealing color reproduction.

Quality settings often need adjustment based on subject matter. For instance, face restoration can dramatically improve portrait quality but might create uncanny results on stylized characters. Similarly, different VAEs excel at different types of content—some preserve vibrant colors better while others excel at realistic textures. Building an understanding of these quality controls allows artists to optimize their workflow for specific types of projects.