64 lines
2.2 KiB
Python
64 lines
2.2 KiB
Python
from __future__ import print_function
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import argparse
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import random
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import torch
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import torch.nn as nn
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import torch.nn.parallel
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import torch.backends.cudnn as cudnn
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import torch.optim as optim
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import torch.utils.data
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import torchvision.datasets as dset
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import torchvision.transforms as transforms
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import torchvision.utils as vutils
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from torch.autograd import Variable
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import os
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import json
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import models.dcgan as dcgan
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import models.mlp as mlp
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if __name__=="__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument('-c', '--config', required=True, type=str, help='path to generator config .json file')
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parser.add_argument('-w', '--weights', required=True, type=str, help='path to generator weights .pth file')
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parser.add_argument('-o', '--output_dir', required=True, type=str, help="path to to output directory")
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parser.add_argument('-n', '--nimages', required=True, type=int, help="number of images to generate", default=1)
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parser.add_argument('--cuda', action='store_true', help='enables cuda')
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opt = parser.parse_args()
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with open(opt.config, 'r') as gencfg:
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generator_config = json.loads(gencfg.read())
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imageSize = generator_config["imageSize"]
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nz = generator_config["nz"]
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nc = generator_config["nc"]
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ngf = generator_config["ngf"]
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noBN = generator_config["noBN"]
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ngpu = generator_config["ngpu"]
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mlp_G = generator_config["mlp_G"]
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n_extra_layers = generator_config["n_extra_layers"]
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if noBN:
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netG = dcgan.DCGAN_G_nobn(imageSize, nz, nc, ngf, ngpu, n_extra_layers)
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elif mlp_G:
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netG = mlp.MLP_G(imageSize, nz, nc, ngf, ngpu)
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else:
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netG = dcgan.DCGAN_G(imageSize, nz, nc, ngf, ngpu, n_extra_layers)
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# load weights
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netG.load_state_dict(torch.load(opt.weights))
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# initialize noise
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fixed_noise = torch.FloatTensor(opt.nimages, nz, 1, 1).normal_(0, 1)
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if opt.cuda:
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netG.cuda()
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fixed_noise = fixed_noise.cuda()
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fake = netG(fixed_noise)
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fake.data = fake.data.mul(0.5).add(0.5)
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for i in range(opt.nimages):
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vutils.save_image(fake.data[i, ...].reshape((1, nc, imageSize, imageSize)), os.path.join(opt.output_dir, "generated_%02d.png"%i))
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