Esempio n. 1
0
def process_mesh(
  cv:CloudVolume,
  label:int,
  mesh: Mesh,
  num_lod:int = 1,
  draco_compression_level:int = 1,
) -> Tuple[MultiLevelPrecomputedMeshManifest, Mesh]:

  mesh.vertices /= cv.meta.resolution(cv.mesh.meta.mip)

  grid_origin = np.floor(np.min(mesh.vertices, axis=0))
  chunk_shape = np.ceil(np.max(mesh.vertices, axis=0) - grid_origin)

  manifest = MultiLevelPrecomputedMeshManifest(
    segment_id=label,
    chunk_shape=chunk_shape,
    grid_origin=grid_origin, 
    num_lods=int(num_lod), 
    lod_scales=[ 1 ] * int(num_lod),
    vertex_offsets=[[0,0,0]],
    num_fragments_per_lod=[1], 
    fragment_positions=[[[0,0,0]]], 
    fragment_offsets=[0], # needs to be set when we have the final value
  )

  vqb = int(cv.mesh.meta.info["vertex_quantization_bits"])
  mesh.vertices = to_stored_model_space(
    mesh.vertices, manifest, 
    lod=0, 
    vertex_quantization_bits=vqb,
    frag=0
  )

  quantization_range = np.max(mesh.vertices, axis=0) - np.min(mesh.vertices, axis=0)
  quantization_range = np.max(quantization_range)

  # mesh.vertices must be integer type or mesh will display
  # distored in neuroglancer.
  mesh = DracoPy.encode(
    mesh.vertices, mesh.faces, 
    quantization_bits=vqb,
    compression_level=draco_compression_level,
    quantization_range=quantization_range,
    quantization_origin=np.min(mesh.vertices, axis=0),
    create_metadata=True,
  )
  manifest.fragment_offsets = [ len(mesh) ]

  return (manifest, mesh)
Esempio n. 2
0
def test_duplicate_vertices():
    verts = np.array(
        [
            [0, 0, 0],
            [0, 1, 0],
            [1, 0, 0],
            [1, 1, 0],
            [2, 0, 0],
            [2, 1, 0],
            [3, 0, 0],
            [3, 1, 0],
            [3, 0, 0],
            [4, 0, 0],
            [4, 1, 0],
            [4, 0, 0],  # duplicate in x direction
            [5, 0, 0],
            [5, 1, 0],
            [5, 0, 0],
            [6, 0, 0],
            [6, 1, 0],
            [6, 1, 2],
            [7, 0, 0],
            [7, 1, 0],
            [4, 0, 0]
        ],
        dtype=np.float32)

    faces = np.array(
        [[0, 1, 2], [2, 3, 4], [4, 5, 6], [7, 8, 9], [9, 10, 11], [10, 11, 12],
         [12, 13, 14], [14, 15, 16], [15, 16, 17], [15, 18, 19], [18, 19, 20]],
        dtype=np.uint32)

    mesh = Mesh(verts, faces, segid=666)

    def deduplicate(mesh, x, offset_x=0):
        return mesh.deduplicate_chunk_boundaries(
            (x, 100, 100),
            is_draco=False,
            offset=(offset_x, -1, -1)  # so y=0,z=0 isn't a chunk boundary
        )

    # test that triple 4 isn't affected
    mesh2 = deduplicate(mesh, x=4)
    assert not np.all(mesh.vertices == mesh2.vertices)
    assert mesh2.vertices.shape[0] == mesh.vertices.shape[0]

    # pop off the last 4
    mesh.vertices = mesh.vertices[:-1]
    mesh.faces = mesh.faces[:-1]

    # test that 4 is now affected
    mesh2 = deduplicate(mesh, x=4)
    assert not np.all(mesh.vertices == mesh2.vertices)
    assert mesh2.vertices.shape[0] == mesh.vertices.shape[0] - 1

    mesh2 = deduplicate(mesh, x=3)
    assert not np.all(mesh.vertices == mesh2.vertices)
    assert mesh2.vertices.shape[0] == mesh.vertices.shape[0] - 1

    mesh2 = deduplicate(mesh, x=4, offset_x=-1)
    assert not np.all(mesh.vertices == mesh2.vertices)
    assert mesh2.vertices.shape[0] == mesh.vertices.shape[0] - 1

    mesh2 = deduplicate(mesh, x=5)
    assert not np.all(mesh.vertices == mesh2.vertices)
    assert mesh2.vertices.shape[0] == mesh.vertices.shape[0] - 1

    mesh2 = deduplicate(mesh, x=1)
    assert not np.all(mesh.vertices == mesh2.vertices)
    assert mesh2.vertices.shape[0] == mesh.vertices.shape[0] - 3