Orchid GAN
This page is a work in progress! OrchidGAN is a StyleGAN2-ADA model fine-tuned to generate Cattleya orchid flowers. It produces realistic synthetic blooms and supports interpretable visualizations like seed sampling, latent interpolation, and style mixing to explore a learned floral “morphospace.”
Interactive sampler
Browse pre-generated OrchidGAN samples (seeds 0–499).
Latent interpolation
Smooth transitions between two seeds.
seed 18 → seed 42
Style mixing
Rows control global structure; columns control fine details.
Morphospace (PCA)
Each point is a seed projected from latent z into 2D via PCA. Click a point to view its sample.
Morphospace (UMAP)
Each point is a seed projected from latent z into 2D via UMAP. Click a point to view its sample.
Latent Space Arithmetic
Discover interpretable directions in latent space. Adjust sliders to see how moving along these directions transforms the orchid.
How it works: We find direction vectors by averaging seeds with similar traits. Moving along these directions reveals what the model learned about flower morphology.
Attribution: This project builds on the StyleGAN2-ADA framework developed by NVIDIA. Initial model weights were pretrained on a publicly available flowers dataset and subsequently fine-tuned on a curated collection of Cattleya orchid images. Training images are not redistributed.