FPFH descriptor and Deep Learning Using Tensorflow

[gledsonmelotti]

Hi guys, I'm sorry for the inconvenience. I would like to understand how to use open3D codes with tensorflow. Can anybody help me? An example below:

def fpfh(vector):
    lf = []
    x,bat=vector
    for LF in range(bat):
        Cloud=x[LF]
        pcd = o3d.geometry.PointCloud()
        pcd.points = o3d.utility.Vector3dVector(Cloud)
        #np.asarray(pcd.points)
        voxel_size = 0.05 # means 5cm for the dataset
        radius_normal = voxel_size * 2
        pcd.estimate_normals(o3d.geometry.KDTreeSearchParamHybrid(radius=radius_normal, max_nn=30))
        radius_feature = voxel_size * 5
        pcd_fpfh = o3d.pipelines.registration.compute_fpfh_feature(pcd,o3d.geometry.KDTreeSearchParamHybrid(radius=radius_feature, max_nn=100))
        localfeature = pcd_fpfh.data
        localfeature = StandardScaler().fit_transform(localfeature)
        localfeature = localfeature.T
        lf.append(localfeature)
    xlf=np.array(lf)
    return xlf

[1939938853]

Good to see some open3d deep learning application examples.

Thanks