Read heterogenous nonlist PLY properties as arrays

Summary:
In the original implementation, I had considered PLY properties where there are mixed types of elements in a property to be rare and basically unimportant, so the implementation is very naive.

If we want to support pointcloud PLY files, we need to handle at least the subcase where there are no lists efficiently because this seems to be very common there.

Reviewed By: nikhilaravi, gkioxari

Differential Revision: D22573315

fbshipit-source-id: db6f29446d4e555a2e2b37d38c8e4450d061465b

pytorch3d/io/ply_io.py

@@ -4,6 +4,7 @@
 
 
 """This module implements utility functions for loading and saving meshes."""
+import itertools
 import struct
 import sys
 import warnings
@@ -232,13 +233,20 @@ def _read_ply_fixed_size_element_ascii(f, definition: _PlyElementType):
     Given an element which has no lists and one type, read the
     corresponding data.
 
+    For example
+
+        element vertex 8
+        property float x
+        property float y
+        property float z
+
     Args:
         f: file-like object being read.
         definition: The element object which describes what we are reading.
 
     Returns:
-        2D numpy array corresponding to the data. The rows are the different
-        values. There is one column for each property.
+        1-element list containing a 2D numpy array corresponding to the data.
+        The rows are the different values. There is one column for each property.
     """
     np_type = _PLY_TYPES[definition.properties[0].data_type].np_type
     old_offset = f.tell()
@@ -251,11 +259,62 @@ def _read_ply_fixed_size_element_ascii(f, definition: _PlyElementType):
         )
     if not len(data):  # np.loadtxt() seeks even on empty data
         f.seek(old_offset)
-    if definition.count and data.shape[1] != len(definition.properties):
+    if data.shape[1] != len(definition.properties):
         raise ValueError("Inconsistent data for %s." % definition.name)
     if data.shape[0] != definition.count:
         raise ValueError("Not enough data for %s." % definition.name)
-    return data
+    return [data]
+
+
+def _read_ply_nolist_element_ascii(f, definition: _PlyElementType):
+    """
+    Given an element which has no lists and multiple types, read the
+    corresponding data, by loading all the data as float64 and converting
+    the relevant parts later.
+
+    For example, given
+
+        element vertex 8
+        property float x
+        property float y
+        property float z
+        property uchar red
+        property uchar green
+        property uchar blue
+
+    the output will have two arrays, the first containing (x,y,z)
+    and the second (red,green,blue).
+
+    Args:
+        f: file-like object being read.
+        definition: The element object which describes what we are reading.
+
+    Returns:
+        List of 2D numpy arrays corresponding to the data.
+    """
+    old_offset = f.tell()
+    with warnings.catch_warnings():
+        warnings.filterwarnings(
+            "ignore", message=".* Empty input file.*", category=UserWarning
+        )
+        data = np.loadtxt(
+            f, dtype=np.float64, comments=None, ndmin=2, max_rows=definition.count
+        )
+    if not len(data):  # np.loadtxt() seeks even on empty data
+        f.seek(old_offset)
+    if data.shape[1] != len(definition.properties):
+        raise ValueError("Inconsistent data for %s." % definition.name)
+    if data.shape[0] != definition.count:
+        raise ValueError("Not enough data for %s." % definition.name)
+    pieces = []
+    offset = 0
+    for dtype, it in itertools.groupby(p.data_type for p in definition.properties):
+        count = sum(1 for _ in it)
+        end_offset = offset + count
+        piece = data[:, offset:end_offset].astype(_PLY_TYPES[dtype].np_type)
+        pieces.append(piece)
+        offset = end_offset
+    return pieces
 
 
 def _try_read_ply_constant_list_ascii(f, definition: _PlyElementType):
@@ -264,6 +323,28 @@ def _try_read_ply_constant_list_ascii(f, definition: _PlyElementType):
     corresponding data assuming every value has the same length.
     If the data is ragged, return None and leave f undisturbed.
 
+    For example, if the element is
+
+        element face 2
+        property list uchar int vertex_index
+
+    and the data is
+
+        4 0 1 2 3
+        4 7 6 5 4
+
+    then the function will return
+
+        [[0, 1, 2, 3],
+         [7, 6, 5, 4]]
+
+    but if the data is
+
+        4 0 1 2 3
+        3 6 5 4
+
+    then the function will return None.
+
     Args:
         f: file-like object being read.
         definition: The element object which describes what we are reading.
@@ -349,8 +430,12 @@ def _read_ply_element_ascii(f, definition: _PlyElementType):
         each occurence of the element, and the inner lists have one value per
         property.
     """
+    if not definition.count:
+        return []
     if definition.is_constant_type_fixed_size():
         return _read_ply_fixed_size_element_ascii(f, definition)
+    if definition.is_fixed_size():
+        return _read_ply_nolist_element_ascii(f, definition)
     if definition.try_constant_list():
         data = _try_read_ply_constant_list_ascii(f, definition)
         if data is not None:
@@ -372,75 +457,123 @@ def _read_ply_element_ascii(f, definition: _PlyElementType):
     return data
 
 
+def _read_raw_array(f, aim: str, length: int, dtype=np.uint8, dtype_size=1):
+    """
+    Read [length] elements from a file.
+
+    Args:
+        f: file object
+        aim: name of target for error message
+        length: number of elements
+        dtype: numpy type
+        dtype_size: number of bytes per element.
+
+    Returns:
+        new numpy array
+    """
+
+    if isinstance(f, BytesIO):
+        # np.fromfile is faster but won't work on a BytesIO
+        needed_bytes = length * dtype_size
+        bytes_data = bytearray(needed_bytes)
+        n_bytes_read = f.readinto(bytes_data)
+        if n_bytes_read != needed_bytes:
+            raise ValueError("Not enough data for %s." % aim)
+        data = np.frombuffer(bytes_data, dtype=dtype)
+    else:
+        data = np.fromfile(f, dtype=dtype, count=length)
+        if data.shape[0] != length:
+            raise ValueError("Not enough data for %s." % aim)
+    return data
+
+
 def _read_ply_fixed_size_element_binary(
     f, definition: _PlyElementType, big_endian: bool
 ):
     """
     Given an element which has no lists and one type, read the
     corresponding data.
 
+    For example
+
+        element vertex 8
+        property float x
+        property float y
+        property float z
+
+
     Args:
         f: file-like object being read.
         definition: The element object which describes what we are reading.
         big_endian: (bool) whether the document is encoded as big endian.
 
     Returns:
-        2D numpy array corresponding to the data. The rows are the different
-        values. There is one column for each property.
+        1-element list containing a 2D numpy array corresponding to the data.
+        The rows are the different values. There is one column for each property.
     """
     ply_type = _PLY_TYPES[definition.properties[0].data_type]
     np_type = ply_type.np_type
     type_size = ply_type.size
     needed_length = definition.count * len(definition.properties)
-    if isinstance(f, BytesIO):
-        # np.fromfile is faster but won't work on a BytesIO
-        needed_bytes = needed_length * type_size
-        bytes_data = bytearray(needed_bytes)
-        n_bytes_read = f.readinto(bytes_data)
-        if n_bytes_read != needed_bytes:
-            raise ValueError("Not enough data for %s." % definition.name)
-        data = np.frombuffer(bytes_data, dtype=np_type)
-    else:
-        data = np.fromfile(f, dtype=np_type, count=needed_length)
-        if data.shape[0] != needed_length:
-            raise ValueError("Not enough data for %s." % definition.name)
+    data = _read_raw_array(f, definition.name, needed_length, np_type, type_size)
 
     if (sys.byteorder == "big") != big_endian:
         data = data.byteswap()
-    return data.reshape(definition.count, len(definition.properties))
+    return [data.reshape(definition.count, len(definition.properties))]
 
 
-def _read_ply_element_struct(f, definition: _PlyElementType, endian_str: str):
+def _read_ply_element_binary_nolists(f, definition: _PlyElementType, big_endian: bool):
     """
-    Given an element which has no lists, read the corresponding data. Uses the
-    struct library.
+    Given an element which has no lists, read the corresponding data as tuple
+    of numpy arrays, one for each set of adjacent columns with the same type.
+
+    For example, given
+
+        element vertex 8
+        property float x
+        property float y
+        property float z
+        property uchar red
+        property uchar green
+        property uchar blue
 
-    Note: It looks like struct would also support lists where
-    type=size_type=char, but it is hard to know how much data to read in that
-    case.
+    the output will have two arrays, the first containing (x,y,z)
+    and the second (red,green,blue).
 
     Args:
         f: file-like object being read.
         definition: The element object which describes what we are reading.
-        endian_str: ">" or "<" according to whether the document is big or
-                    little endian.
+        big_endian: (bool) whether the document is encoded as big endian.
 
     Returns:
-        2D numpy array corresponding to the data. The rows are the different
-        values. There is one column for each property.
+        List of 2D numpy arrays corresponding to the data. The rows are the different
+        values.
     """
-    format = "".join(
-        _PLY_TYPES[property.data_type].struct_char for property in definition.properties
-    )
-    format = endian_str + format
-    pattern = struct.Struct(format)
-    size = pattern.size
+    size = sum(_PLY_TYPES[prop.data_type].size for prop in definition.properties)
     needed_bytes = size * definition.count
-    bytes_data = f.read(needed_bytes)
-    if len(bytes_data) != needed_bytes:
-        raise ValueError("Not enough data for %s." % definition.name)
-    data = [pattern.unpack_from(bytes_data, i * size) for i in range(definition.count)]
-    return data
+    data = _read_raw_array(f, definition.name, needed_bytes).reshape(-1, size)
+    offset = 0
+    pieces = []
+    for dtype, it in itertools.groupby(p.data_type for p in definition.properties):
+        count = sum(1 for _ in it)
+        bytes_each = count * _PLY_TYPES[dtype].size
+        end_offset = offset + bytes_each
+
+        # what we want to do is
+        # piece = data[:, offset:end_offset].view(_PLY_TYPES[dtype].np_type)
+        # but it fails in the general case
+        # because of https://github.com/numpy/numpy/issues/9496.
+        piece = np.lib.stride_tricks.as_strided(
+            data[:1, offset:end_offset].view(_PLY_TYPES[dtype].np_type),
+            shape=(definition.count, count),
+            strides=(data.strides[0], _PLY_TYPES[dtype].size),
+        )
+
+        if (sys.byteorder == "big") != big_endian:
+            piece = piece.byteswap()
+        pieces.append(piece)
+        offset = end_offset
+    return pieces
 
 
 def _try_read_ply_constant_list_binary(
@@ -451,6 +584,28 @@ def _try_read_ply_constant_list_binary(
     corresponding data assuming every value has the same length.
     If the data is ragged, return None and leave f undisturbed.
 
+    For example, if the element is
+
+        element face 2
+        property list uchar int vertex_index
+
+    and the data is
+
+        4 0 1 2 3
+        4 7 6 5 4
+
+    then the function will return
+
+        [[0, 1, 2, 3],
+         [7, 6, 5, 4]]
+
+    but if the data is
+
+        4 0 1 2 3
+        3 6 5 4
+
+    then the function will return None.
+
     Args:
         f: file-like object being read.
         definition: The element object which describes what we are reading.
@@ -460,8 +615,6 @@ def _try_read_ply_constant_list_binary(
         If every element has the same size, 2D numpy array corresponding to the
         data. The rows are the different values. Otherwise None.
     """
-    if definition.count == 0:
-        return []
     property = definition.properties[0]
     endian_str = ">" if big_endian else "<"
     length_format = endian_str + _PLY_TYPES[property.list_size_type].struct_char
@@ -515,18 +668,20 @@ def _read_ply_element_binary(f, definition: _PlyElementType, big_endian: bool) -
         each occurence of the element, and the inner lists have one value per
         property.
     """
-    endian_str = ">" if big_endian else "<"
+    if not definition.count:
+        return []
 
     if definition.is_constant_type_fixed_size():
         return _read_ply_fixed_size_element_binary(f, definition, big_endian)
     if definition.is_fixed_size():
-        return _read_ply_element_struct(f, definition, endian_str)
+        return _read_ply_element_binary_nolists(f, definition, big_endian)
     if definition.try_constant_list():
         data = _try_read_ply_constant_list_binary(f, definition, big_endian)
         if data is not None:
             return data
 
     # We failed to read the element as a lump, must process each line manually.
+    endian_str = ">" if big_endian else "<"
     property_structs = []
     for property in definition.properties:
         initial_type = property.list_size_type or property.data_type
@@ -606,6 +761,7 @@ def _load_ply_raw(f, path_manager: PathManager) -> Tuple[_PlyHeader, dict]:
         elements: A dictionary of element names to values. If an element is
                   regular, in the sense of having no lists or being one
                   uniformly-sized list, then the value will be a 2D numpy array.
+                  If it has no lists but more than one type, it will be a list of arrays.
                   If not, it is a list of the relevant property values.
     """
     with _open_file(f, path_manager, "rb") as f:
@@ -670,11 +826,20 @@ def load_ply(f, path_manager: Optional[PathManager] = None):
     if face is None:
         raise ValueError("The ply file has no face element.")
 
-    if len(vertex) and (
-        not isinstance(vertex, np.ndarray) or vertex.ndim != 2 or vertex.shape[1] != 3
-    ):
+    if not isinstance(vertex, list) or len(vertex) > 1:
         raise ValueError("Invalid vertices in file.")
-    verts = _make_tensor(vertex, cols=3, dtype=torch.float32)
+
+    if len(vertex):
+        vertex0 = vertex[0]
+        if len(vertex0) and (
+            not isinstance(vertex0, np.ndarray)
+            or vertex0.ndim != 2
+            or vertex0.shape[1] != 3
+        ):
+            raise ValueError("Invalid vertices in file.")
+    else:
+        vertex0 = []
+    verts = _make_tensor(vertex0, cols=3, dtype=torch.float32)
 
     face_head = next(head for head in header.elements if head.name == "face")
     if len(face_head.properties) != 1 or face_head.properties[0].list_size_type is None: