def sample_B2A(B):
B2A = G_B2A(B, training=False)
B2A2B = G_A2B(B2A, training=False)
return B2A, B2A2B
# run
save_dir = py.join(args.experiment_dir, 'samples_testing', 'A2B')
py.mkdir(save_dir)
i = 0
for A in A_dataset_test:
A2B, A2B2A = sample_A2B(A)
for A_i, A2B_i, A2B2A_i in zip(A, A2B, A2B2A):
img = np.concatenate(
[A_i.numpy(), A2B_i.numpy(),
A2B2A_i.numpy()], axis=1)
im.imwrite(img, py.join(save_dir, py.name_ext(A_img_paths_test[i])))
i += 1
save_dir = py.join(args.experiment_dir, 'samples_testing', 'B2A')
py.mkdir(save_dir)
i = 0
for B in B_dataset_test:
B2A, B2A2B = sample_B2A(B)
for B_i, B2A_i, B2A2B_i in zip(B, B2A, B2A2B):
img = np.concatenate(
[B_i.numpy(), B2A_i.numpy(),
B2A2B_i.numpy()], axis=1)
im.imwrite(img, py.join(save_dir, py.name_ext(B_img_paths_test[i])))
i += 1
def sample_B2A(B):
B2A = G_B2A(B, training=False)
B2A2B = G_A2B(B2A, training=False)
return B2A, B2A2B
# run
save_dir = py.join(args.experiment_dir, 'samples_testing', 'A2B')
py.mkdir(save_dir)
i = 0
for A in A_dataset_test:
A2B, A2B2A = sample_A2B(A)
for A_i, A2B_i, A2B2A_i in zip(A, A2B, A2B2A):
img = np.concatenate(
[A_i.numpy(), A2B_i.numpy(),
A2B2A_i.numpy()], axis=1)
im.imwrite(img, py.join(save_dir, py.name_ext(lve_imgpaths[i])))
i += 1
save_dir = py.join(args.experiment_dir, 'samples_testing', 'B2A')
py.mkdir(save_dir)
i = 0
for B in B_dataset_test:
B2A, B2A2B = sample_B2A(B)
for B_i, B2A_i, B2A2B_i in zip(B, B2A, B2A2B):
img = np.concatenate(
[B_i.numpy(), B2A_i.numpy(),
B2A2B_i.numpy()], axis=1)
im.imwrite(img, py.join(save_dir, py.name_ext(lv_imgpaths[i])))
i += 1
#import pdb;pdb.set_trace()
# run
print('saving leaves')
save_dir = py.join(args.experiment_dir, 'samples_testing', 'Fossils2Leaves')
py.mkdir(save_dir)
i = 0
for A in A_dataset_test:
A2B, A2B2A = sample_A2B(A)
for A_i, A2B_i, A2B2A_i in zip(A, A2B, A2B2A):
img = A2B_i.numpy(
) #np.concatenate([A_i.numpy(), A2B_i.numpy(), A2B2A_i.numpy()], axis=1)
im.imwrite(
img,
py.join(
save_dir, A_img_paths_test[i].split('/')[-2] + '-' +
py.name_ext(A_img_paths_test[i])))
i += 1
print(i)
print('saving fossils')
save_dir = py.join(args.experiment_dir, 'samples_testing', 'Leaves2Fossils')
py.mkdir(save_dir)
i = 0
for B in B_dataset_test:
B2A, B2A2B = sample_B2A(B)
for B_i, B2A_i, B2A2B_i in zip(B, B2A, B2A2B):
img = B2A_i.numpy(
) #np.concatenate([B_i.numpy(), B2A_i.numpy(), B2A2B_i.numpy()], axis=1)
im.imwrite(
img,
py.join(
save_dir, B_img_paths_test[i].split('/')[-2] + '-' +
def sample_A2B(A):
A2B = G_A2B(A, training=False)
A2B2A = G_B2A(A2B, training=False)
return A2B, A2B2A
@tf.function
def sample_B2A(B):
B2A = G_B2A(B, training=False)
B2A2B = G_A2B(B2A, training=False)
return B2A, B2A2B
save_dir = py.join(args.experiment_dir, 'generated_images', 'A2B')
py.mkdir(save_dir)
i = 0
for A in A_dataset_test:
A2B, A2B2A = sample_A2B(A)
for A_i, A2B_i, A2B2A_i in zip(A, A2B, A2B2A):
im.imwrite(A2B_i.numpy(), py.join(save_dir, py.name_ext(A_img_paths_test[i])))
i += 1
save_dir = py.join(args.experiment_dir, 'generated_images', 'B2A')
py.mkdir(save_dir)
i = 0
for B in B_dataset_test:
B2A, B2A2B = sample_B2A(B)
for B_i, B2A_i, B2A2B_i in zip(B, B2A, B2A2B):
im.imwrite(B2A_i.numpy(), py.join(save_dir, py.name_ext(B_img_paths_test[i])))
i += 1