To fix unnatural color blending artifacts in StyleGAN-generated portraits, apply adaptive discriminator augmentation (ADA), fine-tune with a perceptual loss, and use color consistency regularization.
Here is the code snippet you can refer to:

In the above, we are using the following key points:
- Perceptual Loss: Uses a pre-trained VGG-16 network to compare generated and real images at feature levels.
- Pre-trained Model for Evaluation: Extracts mid-level features from VGG-16 to measure color consistency.
- Reference-Based Correction: Compares generated portraits with real images to refine blending.
- Normalization and Resizing: Ensures images are in the correct format for processing.
- Loss Computation: Computes mean squared error (MSE) loss between real and generated feature representations.
Hence, by implementing perceptual loss and adaptive augmentation, we effectively minimize unnatural color blending artifacts in StyleGAN-generated portraits, ensuring more natural and coherent outputs.