def point_cloud_to_volume_v2()

in wypr/utils/pc_util.py [0:0]

• 27 lines of code
• 10 McCabe index (conditional complexity)

def point_cloud_to_volume_v2(points, vsize, radius=1.0, num_sample=128):
    """ input is Nx3 points
        output is vsize*vsize*vsize*num_sample*3
        assumes points are in range [-radius, radius]
        samples num_sample points in each voxel, if there are less than
        num_sample points, replicate the points
        Added on Feb 19
    """
    vol = np.zeros((vsize,vsize,vsize,num_sample,3))
    voxel = 2*radius/float(vsize)
    locations = (points + radius)/voxel
    locations = locations.astype(int)
    loc2pc = {}
    for n in range(points.shape[0]):
        loc = tuple(locations[n,:])
        if loc not in loc2pc:
            loc2pc[loc] = []
        loc2pc[loc].append(points[n,:])

    for i in range(vsize):
        for j in range(vsize):
            for k in range(vsize):
                if (i,j,k) not in loc2pc:
                    vol[i,j,k,:,:] = np.zeros((num_sample,3))
                else:
                    pc = loc2pc[(i,j,k)] # a list of (3,) arrays
                    pc = np.vstack(pc) # kx3
                    # Sample/pad to num_sample points
                    if pc.shape[0]>num_sample:
                        pc = random_sampling(pc, num_sample, False)
                    elif pc.shape[0]<num_sample:
                        pc = np.lib.pad(pc, ((0,num_sample-pc.shape[0]),(0,0)), 'edge')
                    # Normalize
                    pc_center = (np.array([i,j,k])+0.5)*voxel - radius
                    pc = (pc - pc_center) / voxel # shift and scale
                    vol[i,j,k,:,:] = pc 
    return vol