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200_net_D_A.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4bfe393a8dd711365ad6c9187d82e3080ff001b581d7aaddbbe6bcc3780fc3e6
+size 11062960

200_net_D_B.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d2515ac59c215cc82b3e3f6f3ebcf19af2cac66387453fdf6e6462951fa769f8
+size 11062960

200_net_G_A.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f816d00da7dcb8cd98ef4ffce6ae5bef93eae1596de81cf5e893e0199c920c04
+size 45531926

200_net_G_B.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e973a533975fade84d2f45c550952e942b67d24ac570b50e6c2987373180c6f6
+size 45531926

test.py

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+import os
+from options.test_options import TestOptions
+from data import CreateDataLoader
+from models import create_model
+from util.visualizer import save_images
+from util import html
+
+
+if __name__ == '__main__':
+    opt = TestOptions().parse()
+    # hard-code some parameters for test
+    opt.num_threads = 1   # test code only supports num_threads = 1
+    opt.batch_size = 1    # test code only supports batch_size = 1
+    opt.serial_batches = True  # no shuffle
+    opt.no_flip = True    # no flip
+    opt.display_id = -1   # no visdom display
+    data_loader = CreateDataLoader(opt)
+    dataset = data_loader.load_data()
+    model = create_model(opt)
+    model.setup(opt)
+    # create a website
+    web_dir = os.path.join(opt.results_dir, opt.name, '%s_%s' % (opt.phase, opt.epoch))
+    webpage = html.HTML(web_dir, 'Experiment = %s, Phase = %s, Epoch = %s' % (opt.name, opt.phase, opt.epoch))
+    # test with eval mode. This only affects layers like batchnorm and dropout.
+    # pix2pix: we use batchnorm and dropout in the original pix2pix. You can experiment it with and without eval() mode.
+    # CycleGAN: It should not affect CycleGAN as CycleGAN uses instancenorm without dropout.
+    if opt.eval:
+        model.eval()
+    for i, data in enumerate(dataset):
+        if i >= opt.num_test:
+            break
+        model.set_input(data)
+        model.test()
+        visuals = model.get_current_visuals()
+        img_path = model.get_image_paths()
+        if i % 5 == 0:
+            print('processing (%04d)-th image... %s' % (i, img_path))
+        save_images(webpage, visuals, img_path, aspect_ratio=opt.aspect_ratio, width=opt.display_winsize)
+    # save the website
+    webpage.save()