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visualize.py
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visualize.py
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import argparse
import torch
from torchvision.utils import make_grid
from tqdm import tqdm
import data_loader.data_loaders as module_data
import model.loss as module_loss
import model.metric as module_metric
import model.model as module_arch
from parse_config import ConfigParser
import os
import numpy as np
from skvideo.io import vwrite
def gif(filename, image_list):
fname, _ = os.path.splitext(filename)
filename = fname + '.mp4'
np_images = []
for m in image_list:
np_images.append(m.permute(1, 2, 0).numpy() * 255)
vwrite(filename, np_images, verbosity=0)
return
def main(config, resume, seconds, filename):
# build model architecture
model = config.initialize('arch', module_arch)
checkpoint = torch.load(resume)
state_dict = checkpoint['state_dict']
if config['n_gpu'] > 1:
model = torch.nn.DataParallel(model)
model.load_state_dict(state_dict)
# prepare model for testing
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
model = model.to(device)
model.eval()
batch_size = 16
hidden_dim = config['arch']['args']['hidden_dim']
start_code = torch.randn(batch_size, hidden_dim).to(device)
end_code = torch.randn(batch_size, hidden_dim).to(device)
fps = 24
total_steps = int(fps * seconds)
output_list = []
with torch.no_grad():
for i in torch.linspace(0, 1, total_steps):
code = i * end_code + (1 - i) * start_code
output = model(z=code).sigmoid().cpu()
output_list.append(make_grid(output, nrow=4))
gif(filename, output_list)
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='PyTorch Template')
parser.add_argument('filename', type=str)
parser.add_argument('--seed', type=int, default=0)
parser.add_argument('-t', default=5, type=float)
parser.add_argument('-r', '--resume', default=None, type=str,
help='path to latest checkpoint (default: None)')
parser.add_argument('-d', '--device', default=None, type=str,
help='indices of GPUs to enable (default: all)')
args = parser.parse_args()
config = ConfigParser(parser)
torch.manual_seed(args.seed)
main(config, args.resume, args.t, args.filename)