(batch_data, sigma=0.01, clip=0.05)
return jittered_data
Randomly jitter points. jittering is per point.
        Input:
          BxNx3 array, original batch of point clouds
        Return:
          BxNx3 array, jittered batch of point clouds
Randomly jitter points. jittering is per point.
        Input:
          BxNx3 array, original batch of point clouds
        Return:
          BxNx3 array, jittered batch of point clouds
Randomly jitter points . jittering is per point . Input : BxNx3 array original batch of point clouds Return : BxNx3 array jittered batch of point clouds
def jitter_point_cloud(batch_data, sigma=0.01, clip=0.05):
    """ Randomly jitter points. jittering is per point.
        Input:
          BxNx3 array, original batch of point clouds
        Return:
          BxNx3 array, jittered batch of point clouds
    """
    B, N, C = batch_data.shape
    assert clip > 0
    jittered_data = np.clip(sigma * np.random.randn(B, N, C), -1 * clip, clip)
    jittered_data += batch_data
    return jittered_data
def jitter_point_cloud ( batch_data , sigma = 0.01 , clip = 0.05 ) : B , N , C = batch_data . shape assert clip > 0 jittered_data = np . clip ( sigma * np . random . randn ( B , N , C ) , - 1 * clip , clip ) jittered_data += batch_data return jittered_data