Exemplo n.º 1
0
def inference_augment_t_filter(images, size):
    # augment on temporal domain
    split_dim = 2  # split the temporal domain and rearrange them to repeat time domain
    input_image_list = split_eeg.split_eeg_signal_axes(images, split_dim=split_dim)  # 2 represents temporal domain
    input_image_length = len(input_image_list)
    augment, _ = concat_eeg.conv_eeg_signal_time(input_image_list, np.arange(0, input_image_length), size, 2)
    _print_tensor_size(augment)

    return augment
Exemplo n.º 2
0
def inference_augment_t_filter(images, size):
    # augment on temporal domain
    split_dim = 2  # split the temporal domain and rearrange them to repeat time domain
    input_image_list = split_eeg.split_eeg_signal_axes(
        images, split_dim=split_dim)  # 2 represents temporal domain
    input_image_length = len(input_image_list)
    augment, _ = concat_eeg.conv_eeg_signal_time(
        input_image_list, np.arange(0, input_image_length), size, 2)
    _print_tensor_size(augment)

    return augment
Exemplo n.º 3
0
def inference_augment_s_rep_t_filter(images):
    # augment on spatial domain
    augment = deconv_augment_s_filter(images)

    # augment on temporal domain
    split_dim = 2  # split the temporal domain and rearrange them to repeat time domain
    input_image_list = split_eeg.split_eeg_signal_axes(augment, split_dim=split_dim)  # 2 represents temporal domain
    input_image_length = len(input_image_list)
    augment, _ = concat_eeg.conv_eeg_signal_time(
        input_image_list, np.arange(0, input_image_length), KERNEL_SIZE, 2, is_rep=True
    )
    _print_tensor_size(augment)

    return augment
Exemplo n.º 4
0
def inference_augment_s_rep_t_filter(images):
    # augment on spatial domain
    augment = inference_augment_s_filter(images)

    # augment on temporal domain
    split_dim = 2   # split the temporal domain and rearrange them to repeat time domain
    input_image_list = split_eeg.split_eeg_signal_axes(augment,
                                                       split_dim=split_dim)  # 2 represents temporal domain
    input_image_length = len(input_image_list)
    augment, _ = concat_eeg.conv_eeg_signal_time(input_image_list,
                                                 np.arange(0, input_image_length),
                                                 KERNEL_SIZE, 2, is_rep=True)
    _print_tensor_size(augment)

    return augment