An issue in voxel.py

[aric0103]

Hi, I found a bug in the function voxalize that leads to incorrect results. I checked the value of np.sum(pixel) before return which should be equal to the number of points in the frame, but it is always smaller than it. So I guess some points are not correctly taken into account. I checked the code line by line, and I found line 78 does not work well when the point is close to the maximum boundary(in one of x, y, z dimension). Could you please fix this issue?

[lucagessi]

I think that you are right. I think that the function always lose 3 points, which are the point related to maximum of x, y and z axis. In the better hypothesis if only one point is the fairest it will lose only one.
A part from this the implementation of the function is really slow. I have write a function that, for a particular cloud from 6 seconds of elaboration it goes down to 20 ms.
I leave below some lines:

# Generate index of points axis
# based on axis resolution
# If x is minimum - x min equals 0! It should be OK
x_i = np.int16( np.round((x-x_min) / x_res) )
y_i = np.int16( np.round((y-y_min) / y_res) )
z_i = np.int16( np.round((z-z_min) / z_res) )
for i in range(y.shape[0]):
    # print(f"Indices{x_i[i]},{y_i[i]},{z_i[i]}")
    if( x_i[i] < x_max and y_i[i] < y_max and z_i[i] < z_max ):
        pixel[x_i[i],y_i[i],z_i[i]] = pixel[x_i[i],y_i[i],z_i[i]] + 1
return pixel

It should work fine and it's less code.