Waxfashion StyleGAN 🎨

This is a StyleGAN2 model trained to generate African Wax Pattern fashion designs.

Model Details

Model Type: StyleGAN2
Dataset: paceailab/AfricanWaxPatterns_2KDataset
Input: Random seed (latent vector)
Output: 512x512 wax pattern images

Usage 🚀

You can use this model in your projects with:

!git clone https://github.com/researchpace/waxfashion.git
from huggingface_hub import hf_hub_download
import torch
import legacy
import dnnlib
import sys
sys.path.append('/content/waxfashion/stylegan2-ada-pytorch')

# Load model
model_path = hf_hub_download("paceailab/Waxfashion_StyleGAN", "selected_models/styleGAN2ada_Africanwax.pkl")

# Load the pre-trained StyleGAN2 model
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
with dnnlib.util.open_url(model_path) as f:
    G = legacy.load_network_pkl(f)['G_ema'].to(device)  # Load the generator

# Generate and display image
import numpy as np
import PIL.Image

def generate_image(seed=42):
    z = torch.from_numpy(np.random.RandomState(seed).randn(1, G.z_dim)).to(device)
    img = G(z, None)  # Generate image
    img = (img.permute(0, 2, 3, 1) * 127.5 + 128).clamp(0, 255).to(torch.uint8)[0].cpu().numpy()
    return PIL.Image.fromarray(img)

image = generate_image(seed=100)
image.show()