(self, model, data, device)
return sampled_data
Sample p1 point cloud using FPS.
Sample p1 point cloud using FPS.
Sample p1 point cloud using FPS .
def non_learned_sampling(self, model, data, device):
        """Sample p1 point cloud using FPS."""
        p0, p1, igt = data
        p0 = p0.to(device)  # template
        p1 = p1.to(device)  # source

        p1_samp = model.sampler(p1)
        if self.NUM_SAMPLED_CLOUDS == 1:
            sampled_data = (p0, p1_samp, igt)
        elif self.NUM_SAMPLED_CLOUDS == 2:  # Sample template point cloud as well
            p0_samp = model.sampler(p0)
            sampled_data = (p0_samp, p1_samp, igt)

        return sampled_data
def non_learned_sampling ( self , model , data , device ) : p0 , p1 , igt = data p0 = p0 . to ( device ) # template p1 = p1 . to ( device ) # source p1_samp = model . sampler ( p1 ) if self . NUM_SAMPLED_CLOUDS == 1 : sampled_data = ( p0 , p1_samp , igt ) elif self . NUM_SAMPLED_CLOUDS == 2 : # Sample template point cloud as well p0_samp = model . sampler ( p0 ) sampled_data = ( p0_samp , p1_samp , igt ) return sampled_data