以下代码段的高效实现

时间:2018-10-12 05:34:32

标签: python-3.x numpy computer-vision

我有一个计算3-D体积平均深度的函数。有没有一种方法可以使代码的执行时间更高效。体积具有以下形状。

volume = np.zeros((100, 240, 180))

该体积可以包含不同体素上的数字1,目的是使用体积中所有占用单元格的加权平均值来找到平均深度(平均Z坐标)。

def calc_mean_depth(volume):
        '''

        Calculate the mean depth of the volume. Only voxels which contain a value are considered for the mean depth

        Parameters:
        -----------
        volume: (100x240x180) numpy array
         Input 3-D volume which may contain value of 1 in its voxels
        Return: 
        -------
        mean_depth :<float>
        mean depth calculated
        '''
        depth_weight = 0
        tot = 0
        for z in range(volume.shape[0]):
            vol_slice = volume[z, :, :] # take one x-y plane
            weight = vol_slice[vol_slice>0].size  # get number of values greater than zero
            tot += weight   #  This counter is used to serve as the denominator
            depth_weight += weight * z   # the depth plane into number of cells in it greater than 0.
        if tot==0:
            return 0
        else:
            mean_depth = depth_weight/tot
            return mean_depth

1 个答案:

答案 0 :(得分:0)

这应该有效。使用count_nonzero进行求和并在最后进行平均。

def calc_mean_depth(volume):
    w = np.count_nonzero(volume, axis = (1,2))
    if w.sum() == 0:
        return 0
    else
        return (np.arange(w.size) * w).sum() / w.sum()