You need to generate synthetic images of different breeds of dogs Which model would you use VAE or GAN

Question

Can you tell me if you need to generate synthetic images of different breeds of dogs. Which model would you use, VAE or GAN?

Answer 1

To generate high-quality synthetic images of different dog breeds, GANs (Generative Adversarial Networks) are the best choice over VAEs, as they produce more realistic and high-resolution images by leveraging adversarial training.

Here is the code snippet you can refer to:

In the above code we are using the following key approaches:

• Uses a Deep Convolutional GAN (DCGAN):

  • Generator: Upsamples noise to generate 64x64 RGB images.
  • Discriminator: Distinguishes real dog images from fake ones.

• Employs Tanh Activation in the Generator:

  • Normalizes pixel values for better image quality.

• LeakyReLU for Discriminator Stability:

  • Prevents mode collapse by stabilizing gradient updates.

• Training on Dog Images Dataset (e.g., Stanford Dogs Dataset):

  • Fine-tune the model on a labeled dataset of different breeds for breed-specific generation.

Hence, GANs outperform VAEs for generating synthetic dog images due to their ability to produce sharper, high-resolution, and more realistic outputs.