c8b28432a637a780eed96547260722ff3dede57e,niftynet/engine/sampler_selective.py,,create_label_size_map,#Any#Any#,140

Before Change

    data = np.round(data)
    labels = np.unique(data)
    print("Labels are ", labels)
    binary_seg = np.copy(data)
    binary_seg = np.where(binary_seg == value, np.ones_like(data),
                          np.zeros_like(data))
    labelled_data, num_features = ndimage.label(binary_seg)
    print("Labelling features done")
    unique, count = np.unique(labelled_data, return_counts=True)
    count_data = np.copy(labelled_data)
    for u, c in zip(unique, count):

After Change

    unique, count = np.unique(labelled_data, return_counts=True)
    count_data = np.copy(labelled_data)
    for label, size in zip(unique, count):
        if label == 0:
            continue
        count_data = np.where(labelled_data == label,
                              np.ones_like(data) * size,
                              count_data)
    return count_data

Instances