Merge pull request #2215 from mikedh/release/rr

Release: UV Fix

.github/workflows/release.yml

@@ -28,7 +28,7 @@ jobs:
     strategy:
       matrix:
         python-version: ["3.7", "3.8", "3.9", "3.10", "3.11"]
-        os: [ubuntu-latest, macos-latest, windows-latest]
+        os: [ubuntu-latest, macos-13, windows-latest]
         exclude:
             # windows runners have gotten flaky
           - os: windows-latest

.github/workflows/test.yml

@@ -26,7 +26,7 @@ jobs:
     strategy:
       matrix:
         python-version: ["3.7", "3.11"]
-        os: [ubuntu-latest, windows-latest, macos-latest]
+        os: [ubuntu-latest, windows-latest, macos-13]
     steps:
     - uses: actions/checkout@v3
     - name: Set up Python ${{ matrix.python-version }}

examples/voxel.py

@@ -24,7 +24,7 @@ def show(chair_mesh, chair_voxels, colors=(1, 1, 1, 0.3)):
     trimesh.util.attach_to_log()
 
     base_name = "chair_model"
-    chair_mesh = trimesh.load(os.path.join(dir_models, "%s.obj" % base_name))
+    chair_mesh = trimesh.load(os.path.join(dir_models, f"{base_name}.obj"))
     if isinstance(chair_mesh, trimesh.scene.Scene):
         chair_mesh = trimesh.util.concatenate(
             [
@@ -33,7 +33,7 @@ def show(chair_mesh, chair_voxels, colors=(1, 1, 1, 0.3)):
             ]
         )
 
-    binvox_path = os.path.join(dir_models, "%s.binvox" % base_name)
+    binvox_path = os.path.join(dir_models, f"{base_name}.binvox")
     chair_voxels = trimesh.load(binvox_path)
 
     chair_voxels = v.VoxelGrid(chair_voxels.encoding.dense, chair_voxels.transform)
@@ -62,10 +62,10 @@ def show(chair_mesh, chair_voxels, colors=(1, 1, 1, 0.3)):
     transform = np.eye(4)
     transform[:3] += np.random.normal(size=(3, 4)) * 0.2
     transformed_chair_mesh = chair_mesh.copy().apply_transform(transform)
-    log.debug("original transform volume: %s" % str(chair_voxels.element_volume))
+    log.debug(f"original transform volume: {chair_voxels.element_volume!s}")
 
     chair_voxels.apply_transform(transform)
-    log.debug("warped transform volume:   %s" % str(chair_voxels.element_volume))
+    log.debug(f"warped transform volume:   {chair_voxels.element_volume!s}")
     log.debug("blue: transformed voxels")
     log.debug("Transformation is lazy, and each voxel is no longer a cube.")
     show(transformed_chair_mesh, chair_voxels, colors=(0, 0, 1, 0.3))

pyproject.toml

@@ -5,7 +5,7 @@ requires = ["setuptools >= 61.0", "wheel"]
 [project]
 name = "trimesh"
 requires-python = ">=3.7"
-version = "4.3.1"
+version = "4.3.2"
 authors = [{name = "Michael Dawson-Haggerty", email = "[email protected]"}]
 license = {file = "LICENSE.md"}
 description = "Import, export, process, analyze and view triangular meshes."

tests/test_texture.py

@@ -206,6 +206,36 @@ def test_uv_none(self):
         c = m.copy()
         assert c.visual.uv is None
 
+    def test_pbr_nouv_export(self):
+        # Test that we can properly save and load a pbr material without uv and texture image.
+        material = g.trimesh.visual.material.PBRMaterial(
+            metallicFactor=0.3,
+            roughnessFactor=0.5,
+            baseColorFactor=(0, 255, 0, 255),
+            name="abc",
+        )
+        mesh = g.trimesh.Trimesh(
+            vertices=[[0, 0, 0], [0, 0, 1], [0, 1, 1]],
+            faces=[[0, 1, 2]],
+            process=False,
+            visual=g.trimesh.visual.TextureVisuals(material=material),
+        )
+        scene = g.trimesh.Scene()
+        scene.add_geometry(mesh, geom_name="geom")
+        with g.TemporaryDirectory() as d:
+            # exports by path allow files to be written
+            path = g.os.path.join(d, "tmp.glb")
+            scene.export(path)
+
+            # try reloading
+            r = g.trimesh.load(path)
+            # make sure material survived
+            assert r.geometry["geom"].visual.material.metallicFactor == 0.3
+            assert r.geometry["geom"].visual.material.roughnessFactor == 0.5
+            assert (
+                r.geometry["geom"].visual.material.baseColorFactor == [0, 255, 0, 255]
+            ).all()
+
     def test_pbr_export(self):
         # try loading a textured box
         m = next(iter(g.get_mesh("BoxTextured.glb").geometry.values()))

trimesh/base.py

@@ -189,7 +189,7 @@ def __init__(
         if isinstance(metadata, dict):
             self.metadata.update(metadata)
         elif metadata is not None:
-            raise ValueError("metadata should be a dict or None, got %s" % str(metadata))
+            raise ValueError(f"metadata should be a dict or None, got {metadata!s}")
 
         # store per-face and per-vertex attributes which will
         # be updated when an update_faces call is made

trimesh/exchange/binvox.py

@@ -144,7 +144,7 @@ def binvox_bytes(rle_data, shape, translate=(0, 0, 0), scale=1):
       Suitable for writing to binary file
     """
     if rle_data.dtype != np.uint8:
-        raise ValueError("rle_data.dtype must be np.uint8, got %s" % rle_data.dtype)
+        raise ValueError(f"rle_data.dtype must be np.uint8, got {rle_data.dtype}")
 
     header = binvox_header(shape, translate, scale).encode()
     return header + rle_data.tobytes()
@@ -228,7 +228,7 @@ def load_binvox(file_obj, resolver=None, axis_order="xzy", file_type=None):
       Loaded voxel data
     """
     if file_type is not None and file_type != "binvox":
-        raise ValueError("file_type must be None or binvox, got %s" % file_type)
+        raise ValueError(f"file_type must be None or binvox, got {file_type}")
     data = parse_binvox(file_obj, writeable=True)
     return voxel_from_binvox(
         rle_data=data.rle_data,
@@ -553,15 +553,15 @@ def voxelize_mesh(mesh, binvoxer=None, export_type="off", **binvoxer_kwargs):
     `VoxelGrid` object resulting.
     """
     if not isinstance(mesh, Trimesh):
-        raise ValueError("mesh must be Trimesh instance, got %s" % str(mesh))
+        raise ValueError(f"mesh must be Trimesh instance, got {mesh!s}")
     if binvoxer is None:
         binvoxer = Binvoxer(**binvoxer_kwargs)
     elif len(binvoxer_kwargs) > 0:
         raise ValueError("Cannot provide binvoxer and binvoxer_kwargs")
     if binvoxer.file_type != "binvox":
         raise ValueError('Only "binvox" binvoxer `file_type` currently supported')
     with TemporaryDirectory() as folder:
-        model_path = os.path.join(folder, "model.%s" % export_type)
+        model_path = os.path.join(folder, f"model.{export_type}")
         with open(model_path, "wb") as fp:
             mesh.export(fp, file_type=export_type)
         out_path = binvoxer(model_path)

trimesh/exchange/gltf.py

@@ -920,8 +920,8 @@ def _append_mesh(
             # add the reference for UV coordinates
             current["primitives"][0]["attributes"]["TEXCOORD_0"] = acc_uv
 
-            # only reference the material if we had UV coordinates
-            current["primitives"][0]["material"] = current_material
+        # reference the material
+        current["primitives"][0]["material"] = current_material
 
     if include_normals or (
         include_normals is None and "vertex_normals" in mesh._cache.cache

trimesh/exchange/load.py

@@ -137,7 +137,7 @@ def load(
                 # this prevents the exception from being super opaque
                 load_path()
             else:
-                raise ValueError("File type: %s not supported" % file_type)
+                raise ValueError(f"File type: {file_type} not supported")
     finally:
         # close any opened files even if we crashed out
         if opened:

trimesh/exchange/threedxml.py

@@ -85,7 +85,7 @@ def load_3DXML(file_obj, *args, **kwargs):
             if texture is not None:
                 tex_file, tex_id = texture.attrib["Value"].split(":")[-1].split("#")
                 rep_image = as_etree[tex_file].find(
-                    "{*}CATRepImage/{*}CATRepresentationImage[@id='%s']" % tex_id
+                    f"{{*}}CATRepImage/{{*}}CATRepresentationImage[@id='{tex_id}']"
                 )
                 if rep_image is not None:
                     image_file = rep_image.get("associatedFile", "").split(":")[-1]
@@ -167,7 +167,7 @@ def get_rgba(color):
 
         if part_file not in as_etree and part_file in archive:
             # the data is stored in some binary format
-            util.log.warning("unable to load Rep %r" % part_file)
+            util.log.warning(f"unable to load Rep {part_file!r}")
             # data = archive[part_file]
             continue
 

trimesh/interfaces/blender.py

@@ -103,8 +103,8 @@ def unwrap(
 
     # get the template from our resources folder
     template = resources.get_string("templates/blender_unwrap.py.template")
-    script = template.replace("$ANGLE_LIMIT", "%.6f" % angle_limit).replace(
-        "$ISLAND_MARGIN", "%.6f" % island_margin
+    script = template.replace("$ANGLE_LIMIT", f"{angle_limit:.6f}").replace(
+        "$ISLAND_MARGIN", f"{island_margin:.6f}"
     )
 
     with MeshScript(meshes=[mesh], script=script, exchange="obj", debug=debug) as blend:

trimesh/path/raster.py

@@ -46,7 +46,12 @@ def rasterize(path, pitch=None, origin=None, resolution=None, fill=True, width=N
     """
 
     if pitch is None:
-        pitch = path.extents.max() / 2048
+        if resolution is not None:
+            resolution = np.array(resolution, dtype=np.int64)
+            # establish pitch from passed resolution
+            pitch = (path.extents / (resolution + 2)).max()
+        else:
+            pitch = path.extents.max() / 2048
 
     if origin is None:
         origin = path.bounds[0] - (pitch * 2.0)

trimesh/registration.py

@@ -148,7 +148,12 @@ def key_points(m, count):
 
         # run first pass ICP
         matrix, _junk, cost = icp(
-            a=points, b=search, initial=a_to_b, max_iterations=int(icp_first), scale=scale
+            a=points,
+            b=search,
+            initial=a_to_b,
+            max_iterations=int(icp_first),
+            scale=scale,
+            **kwargs,
         )
 
         # save transform and costs from ICP
@@ -162,6 +167,7 @@ def key_points(m, count):
         initial=transforms[np.argmin(costs)],
         max_iterations=int(icp_final),
         scale=scale,
+        **kwargs,
     )
 
     # convert to per- point distance average

trimesh/transformations.py

@@ -753,7 +753,7 @@ def shear_from_matrix(matrix):
 
     i = np.where(abs(np.real(w) - 1.0) < 1e-4)[0]
     if len(i) < 2:
-        raise ValueError("no two linear independent eigenvectors found %s" % w)
+        raise ValueError(f"no two linear independent eigenvectors found {w}")
     V = np.real(V[:, i]).squeeze().T
     lenorm = -1.0
     for i0, i1 in ((0, 1), (0, 2), (1, 2)):

trimesh/triangles.py

@@ -336,7 +336,7 @@ def windings_aligned(triangles, normals_compare):
     triangles = np.asanyarray(triangles, dtype=np.float64)
     if not util.is_shape(triangles, (-1, 3, 3), allow_zeros=True):
         raise ValueError(
-            "triangles must have shape (n, 3, 3), got %s" % str(triangles.shape)
+            f"triangles must have shape (n, 3, 3), got {triangles.shape!s}"
         )
     normals_compare = np.asanyarray(normals_compare, dtype=np.float64)
 

trimesh/util.py

@@ -2258,9 +2258,9 @@ def __getitem__(self, key):
 
     def __setitem__(self, key, value):
         if not isinstance(key, str):
-            raise ValueError("key must be a string, got %s" % str(key))
+            raise ValueError(f"key must be a string, got {key!s}")
         if key in self:
-            raise KeyError("Cannot set new value to existing key %s" % key)
+            raise KeyError(f"Cannot set new value to existing key {key}")
         if not callable(value):
             raise ValueError("Cannot set value which is not callable.")
         self._dict[key] = value

trimesh/voxel/base.py

@@ -39,7 +39,7 @@ def __init__(self, encoding, transform=None, metadata=None):
         if isinstance(metadata, dict):
             self.metadata.update(metadata)
         elif metadata is not None:
-            raise ValueError("metadata should be a dict or None, got %s" % str(metadata))
+            raise ValueError(f"metadata should be a dict or None, got {metadata!s}")
 
     def __hash__(self):
         """
@@ -66,13 +66,13 @@ def encoding(self, encoding):
         if isinstance(encoding, np.ndarray):
             encoding = DenseEncoding(encoding)
         elif not isinstance(encoding, Encoding):
-            raise ValueError("encoding must be an Encoding, got %s" % str(encoding))
+            raise ValueError(f"encoding must be an Encoding, got {encoding!s}")
         if len(encoding.shape) != 3:
             raise ValueError(
-                "encoding must be rank 3, got shape %s" % str(encoding.shape)
+                f"encoding must be rank 3, got shape {encoding.shape!s}"
             )
         if encoding.dtype != bool:
-            raise ValueError("encoding must be binary, got %s" % encoding.dtype)
+            raise ValueError(f"encoding must be binary, got {encoding.dtype}")
         self._data["encoding"] = encoding
 
     @property

trimesh/voxel/encoding.py

@@ -288,7 +288,7 @@ def __init__(self, indices, values, shape=None):
         data["values"] = values
         indices = data["indices"]
         if len(indices.shape) != 2:
-            raise ValueError("indices must be 2D, got shaped %s" % str(indices.shape))
+            raise ValueError(f"indices must be 2D, got shaped {indices.shape!s}")
         if data["values"].shape != (indices.shape[0],):
             raise ValueError(
                 "values and indices shapes inconsistent: {} and {}".format(
@@ -511,7 +511,7 @@ def size(self):
 
     def _flip(self, axes):
         if axes != (0,):
-            raise ValueError("encoding is 1D - cannot flip on axis %s" % str(axes))
+            raise ValueError(f"encoding is 1D - cannot flip on axis {axes!s}")
         return RunLengthEncoding(runlength.rle_reverse(self._data))
 
     @caching.cache_decorator
@@ -616,7 +616,7 @@ def size(self):
 
     def _flip(self, axes):
         if axes != (0,):
-            raise ValueError("encoding is 1D - cannot flip on axis %s" % str(axes))
+            raise ValueError(f"encoding is 1D - cannot flip on axis {axes!s}")
         return BinaryRunLengthEncoding(runlength.brle_reverse(self._data))
 
     @property
@@ -816,7 +816,7 @@ class TransposedEncoding(LazyIndexMap):
     def __init__(self, base_encoding, perm):
         if not isinstance(base_encoding, Encoding):
             raise ValueError(
-                "base_encoding must be an Encoding, got %s" % str(base_encoding)
+                f"base_encoding must be an Encoding, got {base_encoding!s}"
             )
         if len(base_encoding.shape) != len(perm):
             raise ValueError(
@@ -826,7 +826,7 @@ def __init__(self, base_encoding, perm):
         super().__init__(base_encoding)
         perm = np.array(perm, dtype=np.int64)
         if not all(i in perm for i in range(base_encoding.ndims)):
-            raise ValueError("perm %s is not a valid permutation" % str(perm))
+            raise ValueError(f"perm {perm!s} is not a valid permutation")
         inv_perm = np.empty_like(perm)
         inv_perm[perm] = np.arange(base_encoding.ndims)
         self._perm = perm
@@ -896,7 +896,7 @@ def __init__(self, encoding, axes):
         axes = tuple(a + ndims if a < 0 else a for a in axes)
         self._axes = tuple(sorted(axes))
         if len(set(self._axes)) != len(self._axes):
-            raise ValueError("Axes cannot contain duplicates, got %s" % str(self._axes))
+            raise ValueError(f"Axes cannot contain duplicates, got {self._axes!s}")
         super().__init__(encoding)
         if not all(0 <= a < self._data.ndims for a in axes):
             raise ValueError(

trimesh/voxel/morphology.py

@@ -23,7 +23,7 @@ def _dense(encoding, rank=None):
         dense = encoding.dense
     else:
         raise ValueError(
-            "encoding must be np.ndarray or Encoding, got %s" % str(encoding)
+            f"encoding must be np.ndarray or Encoding, got {encoding!s}"
         )
     if rank:
         _assert_rank(dense, rank)
@@ -37,7 +37,7 @@ def _sparse_indices(encoding, rank=None):
         sparse_indices = encoding.sparse_indices
     else:
         raise ValueError(
-            "encoding must be np.ndarray or Encoding, got %s" % str(encoding)
+            f"encoding must be np.ndarray or Encoding, got {encoding!s}"
         )
 
     _assert_sparse_rank(sparse_indices, 3)
@@ -51,7 +51,7 @@ def _assert_rank(value, rank):
 
 def _assert_sparse_rank(value, rank=None):
     if len(value.shape) != 2:
-        raise ValueError("sparse_indices must be rank 2, got shape %s" % str(value.shape))
+        raise ValueError(f"sparse_indices must be rank 2, got shape {value.shape!s}")
     if rank is not None:
         if value.shape[-1] != rank:
             raise ValueError(

trimesh/voxel/runlength.py

@@ -231,7 +231,7 @@ def brle_to_dense(brle_data, vals=None):
     else:
         vals = np.asarray(vals)
         if vals.shape != (2,):
-            raise ValueError("vals.shape must be (2,), got %s" % (vals.shape))
+            raise ValueError(f"vals.shape must be (2,), got {vals.shape}")
     ft = np.repeat(_ft[np.newaxis, :], (len(brle_data) + 1) // 2, axis=0).flatten()
     return np.repeat(ft[: len(brle_data)], brle_data).flatten()