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import os
from options.test_options import TestOptions
from data import CreateRecursiveDataLoader
from models import create_model
from util.visualizer import Visualizer
from util.util import mkdirs
from util import html
from shutil import move, copyfile
import subprocess
from time import sleep
if __name__ == '__main__':
opt = TestOptions().parse()
opt.nThreads = 1 # test code only supports nThreads = 1
opt.batchSize = 1 # test code only supports batchSize = 1
opt.serial_batches = True # no shuffle
opt.no_flip = True # no flip
opt.experiment = opt.start_img.split(".")[0]
render_dir = opt.results_dir + "/" + opt.name + "/exp:" + opt.experiment + "/"
mkdirs(render_dir)
copyfile(opt.start_img, render_dir + "frame_00000.png")
data_loader = CreateRecursiveDataLoader(opt)
dataset = data_loader.load_data()
ds = dataset.dataset
model = create_model(opt)
visualizer = Visualizer(opt)
# create website
web_dir = os.path.join(opt.results_dir, opt.name, '%s_%s' % (opt.phase, opt.which_epoch))
webpage = html.HTML(web_dir, 'Experiment = %s, Phase = %s, Epoch = %s' % (opt.name, opt.phase, opt.which_epoch))
# test
print(dataset.name())
for i, data in enumerate(data_loader):
if i >= opt.how_many:
break
model.set_input(data)
model.test()
visuals = model.get_current_visuals()
img_path = model.get_image_paths()
print('%04d: process image... %s' % (i, img_path))
ims = visualizer.save_images(webpage, visuals, img_path, aspect_ratio=opt.aspect_ratio)
if dataset.name() == 'RecursiveDatasetDataLoader':
last_image = opt.results_dir + opt.name + "/test_latest/images/" + ims[1]
next_image = render_dir + "frame_{:05d}.png".format(i+1)
move(last_image, next_image)
webpage.save()
cmd = ("/usr/bin/ffmpeg", "-i", "frame_%05d.png", "-c:v", "libx264", "-vf", "fps=30", "-pix_fmt", "yuv420p", render_dir + opt.name + "_" + opt.experiment + ".mp4")
process = subprocess.Popen(cmd, stdout=subprocess.PIPE)
output, error = process.communicate()
cmd = ("scp", render_dir + opt.name + "_" + opt.experiment + ".mp4", "jules@asdf.us:asdf/neural/")
process = subprocess.Popen(cmd, stdout=subprocess.PIPE)
output, error = process.communicate()
print("\n")
print("https://asdf.us/neural/" + opt.name + "_" + opt.experiment + ".mp4")
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