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