test_AFN.py

import time
from options.testAFN_options import TestOptions
from data.data_loader import CreateDataLoader
from models.models import create_model
from util.visualizer import Visualizer
import os
from util import html


opt = TestOptions().parse()
opt.dataset_mode = 'AFN'
opt.model = 'AFN'
opt.isTrain=False
opt.isPretrain = False
opt.phase = 'test'
data_loader = CreateDataLoader(opt)
dataset = data_loader.load_data()
dataset_size = len(data_loader)

print('#test images = %d' % dataset_size)

model = create_model(opt)
visualizer = Visualizer(opt)
total_steps = 0

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))

for i, data in enumerate(dataset):
    if i >= opt.how_many:
        break
    model.set_input(data)
    model.test()
    visuals = model.get_current_visuals()
    img_path = model.get_image_paths()
    print('process image... %s' % img_path)
    visualizer.save_images(webpage, visuals, img_path)

webpage.save()