03e8525394683bb5da7668330cd910c87c7d4501,data_augmentation.py,,rand_intensity_normalisation,#Any#Any#,77

Before Change

def rand_intensity_normalisation(img, irs_model):
    rand_bin = np.random.randint(0, 20)
    img = irs_model.transform(img, thr=rand_bin)
    img = (img - np.mean(img)) / np.std(img)
    return img


def __enumerate_step_points(starting, ending, win_size, step_size):

After Change

def rand_intensity_normalisation(img, irs_model):
    rand_bin = np.random.randint(0, 20)
    for mod_i in range(img.shape[-1]):
        img[:,:,:,mod_i] = irs_model.transform(img[:,:,:,mod_i], thr=rand_bin)
        img[:,:,:,mod_i] = (img[:,:,:,mod_i] - np.mean(img[:,:,:,mod_i])) / np.std(img[:,:,:,mod_i])
    return img


def __enumerate_step_points(starting, ending, win_size, step_size):

Instances