Added Motivation

Author: codinglabsong

README.md

@@ -3,6 +3,9 @@ Aging GAN is an unpaired image-to-image translation project for facial age tran
 
 This repository contains training scripts, helper utilities, inference scripts, and a Gradio app for demo purposes.
 
+## Motivation
+Face‑aging models aren't just "fun filters" on social apps, but address real needs across law enforcement, healthcare, and even entertainment. One of the most important applications is in forensic science and missing‑person investigations. When a child vanishes, every year that passes makes their appearance shift. Age‑progressed images generated by an aging GAN can help police and the public recognize what the child might look like today. Those same techniques assist in cold‑case searches for adults, helping law enforcement update outdated photographs to increase the chances of identification. In healthcare and dermatology, face‑aging networks can even simulate how a patient's skin is likely to evolve under various conditions. Different tasks would require different datasets and architectures, but you would be able to learn how a theory can convert to meaningful application through this project.
+
 ## Features
 - **CycleGAN Architecture** - ResNet‑style "encoder-residual-decoder" generators and PatchGAN discriminators. In addition to adversarial loss, cycle‑consistency loss was used to preserve content/structure. Moreover, identity loss was added to preserve color and style of the original image.
 - **Data Pipeline & Preprocessing** - deterministic train/val/test splits, on-the-fly augmentations, unpaired DataLoader that pairs Young (18–28) and Middle-aged/Old (40+) faces at each batch.