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save vector from optimization #48

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save vector from optimization #48

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10 changes: 9 additions & 1 deletion optimization/run_optimization.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
import argparse
import math
import os
import numpy as np

import torch
import torchvision
Expand Down Expand Up @@ -80,14 +81,20 @@ def main(args):
with torch.no_grad():
img_gen, _ = g_ema([latent], input_is_latent=True, randomize_noise=False)

torchvision.utils.save_image(img_gen, f"results/{str(i).zfill(5)}.png", normalize=True, range=(-1, 1))
torchvision.utils.save_image(img_gen, f"{args.results_dir}/{str(i).zfill(5)}.png", normalize=True, range=(-1, 1))

if(args.save_vector):
np.savez(f'{args.results_dir}/w-{str(i).zfill(5)}.npz', w=latent.unsqueeze(0).detach().cpu().numpy())


if args.mode == "edit":
with torch.no_grad():
img_orig, _ = g_ema([latent_code_init], input_is_latent=True, randomize_noise=False)

final_result = torch.cat([img_orig, img_gen])
else:
if(args.save_vector):
np.savez(f'{args.results_dir}/projected_w.npz', w=latent.unsqueeze(0).detach().cpu().numpy())
final_result = img_gen

return final_result
Expand All @@ -111,6 +118,7 @@ def main(args):
"not provided")
parser.add_argument("--save_intermediate_image_every", type=int, default=20, help="if > 0 then saves intermidate results during the optimization")
parser.add_argument("--results_dir", type=str, default="results")
parser.add_argument('--save_vector', action='store_true')

args = parser.parse_args()

Expand Down