PROJECT_STATUS.md

Project Status

VintageGAN is currently an academic research prototype.

Current State

• The target user experience is preset/slider-based vintage filtering.
• The technical goal is controllable conditional image-to-image synthesis.
• The default training profile is local_256 for RTX 3050 4GB class GPUs.
• Cloud profiles are available for 384px and 512px experimentation.

Ready

• Procedural target generation for six vintage defect controls.
• Conditional generator/discriminator scaffolding.
• Explicit preset vectors in configs/presets.yaml.
• Local/cloud config profiles in configs/training_config.yaml.
• Inference API/CLI contract with optional metadata JSON.

Needs Real Validation

• Clean environment installation.
• End-to-end smoke training.
• Real trained checkpoints.
• Real metrics generated from saved experiment artifacts.
• Dataset source/license documentation.
• Detector-backed consistency loss experiments.

Not Claimed

• Production readiness.
• Publication readiness.
• Academic-grade results.
• Real FID/SSIM/PSNR numbers.
• Bundled trained checkpoints.

This file should be updated only from verified runs, not from intended targets.