def get_fid(fakes, model, npz, device, batch_size=1, use_tqdm=True):
m1, s1 = npz['mu'], npz['sigma']
fakes = torch.cat(fakes, dim=0)
fakes = util.tensor2im(fakes).astype(float)
m2, s2 = _compute_statistics_of_ims(fakes, model, batch_size, 2048,
device, use_tqdm=use_tqdm)
return float(calculate_frechet_distance(m1, s1, m2, s2))
def get_fid_new(reals, fakes, model, device, batch_size=1, use_tqdm=True):
reals = torch.cat(reals, dim=0)
reals = util.tensor2im(reals).astype(float)
fakes = torch.cat(fakes, dim=0)
fakes = util.tensor2im(fakes).astype(float)
m1, s1 = _compute_statistics_of_ims(reals,
model,
batch_size,
2048,
device,
use_tqdm=use_tqdm,
median=False)
m2, s2 = _compute_statistics_of_ims(fakes,
model,
batch_size,
2048,
device,
use_tqdm=use_tqdm,
median=False)
fid_mean = float(calculate_frechet_distance(m1, s1, m2, s2, median=False))
m1, s1 = _compute_statistics_of_ims(reals,
model,
batch_size,
2048,
device,
use_tqdm=use_tqdm,
median=True)
m2, s2 = _compute_statistics_of_ims(fakes,
model,
batch_size,
2048,
device,
use_tqdm=use_tqdm,
median=True)
fid_median = float(calculate_frechet_distance(m1, s1, m2, s2, median=True))
return fid_mean, fid_median