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import sys | |
import os | |
import base64 | |
import torch | |
from PIL import Image | |
import dnnlib | |
import legacy | |
def load_stylegan2(model_path, device): | |
""" | |
Loads the stylegan2 generator. | |
Arguments: | |
model_path (str): Path to model | |
device (str): Device to load model on | |
Returns: | |
G (nn.Module): Stylegan generator | |
w_avg (Tensor): The average style vector in W space | |
""" | |
with dnnlib.util.open_url(model_path) as f: | |
G = legacy.load_network_pkl(f)["G_ema"] | |
w_avg = G.mapping.w_avg.repeat(14, 1) | |
w_avg = w_avg.to(device) | |
G = G.to(device) | |
return G, w_avg | |
def tensor2im(var): | |
""" | |
Converts a tensor image to PIL Image. Taken from the stylegan2-ada-pytorch repo | |
Arguments: | |
var (Tensor): Tensor representing the input image | |
Returns: | |
image (PIL.Image): Image displayed | |
""" | |
var = (var.permute(1, 2, 0) * 127.5 + 127.5).clamp(0, 255).to(torch.uint8) | |
return Image.fromarray(var.cpu().numpy(), "RGB") | |