indoor3d_util.py 文件源码

def room2blocks_plus_normalized(data_label, num_point, block_size, stride,
                                random_sample, sample_num, sample_aug):
    """ room2block, with input filename and RGB preprocessing.
        for each block centralize XYZ, add normalized XYZ as 678 channels
    """
    data = data_label[:,0:6]
    data[:,3:6] /= 255.0
    label = data_label[:,-1].astype(np.uint8)
    max_room_x = max(data[:,0])
    max_room_y = max(data[:,1])
    max_room_z = max(data[:,2])

    data_batch, label_batch = room2blocks(data, label, num_point, block_size, stride,
                                          random_sample, sample_num, sample_aug)
    new_data_batch = np.zeros((data_batch.shape[0], num_point, 9))
    for b in range(data_batch.shape[0]):
        new_data_batch[b, :, 6] = data_batch[b, :, 0]/max_room_x
        new_data_batch[b, :, 7] = data_batch[b, :, 1]/max_room_y
        new_data_batch[b, :, 8] = data_batch[b, :, 2]/max_room_z
        minx = min(data_batch[b, :, 0])
        miny = min(data_batch[b, :, 1])
        data_batch[b, :, 0] -= (minx+block_size/2)
        data_batch[b, :, 1] -= (miny+block_size/2)
    new_data_batch[:, :, 0:6] = data_batch
    return new_data_batch, label_batch