test.py

import time
from options.test_options import TestOptions
from data.data_loader import CreateDataLoader
from util.visualizer import Visualizer

from models.models import create_model
from data import create_dataset
from pdb import set_trace as st
from util import html
import os

opt = TestOptions().parse()

dataset = create_dataset(opt)  # create a dataset given opt.dataset_mode and other options
dataset_size = len(dataset)    # get the number of images in the dataset.
print('The number of training images = %d' % dataset_size)


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

# data_loader = CreateDataLoader(opt)
# dataset = data_loader.load_data()
model = create_model(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
id=0
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()
    visualizer.save_images(webpage, visuals, img_path, id)
    id = id+1
    print('process image... %s' % img_path)
    print(id)

webpage.save()