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A Deep Convolutional GAN trained on an anime face dataset to generate stylistically consistent character face variations from latent seeds, designed for rapid creative exploration workflows.

Project details
A DCGAN pipeline that generates anime-style faces from deterministic latent seeds for rapid iteration, review, and shortlisting in early character design phases.
Seed-based deterministic generation (reproducible outputs).
Rapid diversity via latent sampling.
Latent space interpolation for controlled morphing between archetypes.
Batch generation for stakeholder review loops.
Preprocess → sample latent z ~ N(0,1) → Generator (transposed conv + BN + ReLU, tanh out) → Discriminator (strided conv + LeakyReLU) → adversarial training (Adam) → export generator checkpoint.
Local GPU inference for fast iteration
Docker packaging for reproducible environments
Batch generation API integration into internal tools
Optional cloud GPU deployment for distributed teams