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Address black + isort fbsource linter warnings

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Summary: Address black + isort fbsource linter warnings from D20558374 (previous diff)

Reviewed By: nikhilaravi

Differential Revision: D20558373

fbshipit-source-id: d3607de4a01fb24c0d5269634563a7914bddf1c8
This commit is contained in:
Patrick Labatut
2020-03-29 14:46:33 -07:00
committed by Facebook GitHub Bot
parent eb512ffde3
commit d57daa6f85
110 changed files with 705 additions and 1850 deletions
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1
pytorch3d/io/__init__.py
View File

@@ -4,4 +4,5 @@
from .obj_io import load_obj, load_objs_as_meshes, save_obj
from .ply_io import load_ply, save_ply
__all__ = [k for k in globals().keys() if not k.startswith("_")]

27
pytorch3d/io/obj_io.py
View File

@@ -2,16 +2,16 @@
"""This module implements utility functions for loading and saving meshes."""
import numpy as np
import os
import pathlib
import warnings
from collections import namedtuple
from typing import List, Optional
import numpy as np
import torch
from fvcore.common.file_io import PathManager
from PIL import Image
from pytorch3d.structures import Meshes, Textures, join_meshes
@@ -51,9 +51,7 @@ def _read_image(file_name: str, format=None):
# Faces & Aux type returned from load_obj function.
_Faces = namedtuple("Faces", "verts_idx normals_idx textures_idx materials_idx")
_Aux = namedtuple(
"Properties", "normals verts_uvs material_colors texture_images"
)
_Aux = namedtuple("Properties", "normals verts_uvs material_colors texture_images")
def _format_faces_indices(faces_indices, max_index):
@@ -247,9 +245,7 @@ def load_objs_as_meshes(files: list, device=None, load_textures: bool = True):
image = list(tex_maps.values())[0].to(device)[None]
tex = Textures(verts_uvs=verts_uvs, faces_uvs=faces_uvs, maps=image)
mesh = Meshes(
verts=[verts], faces=[faces.verts_idx.to(device)], textures=tex
)
mesh = Meshes(verts=[verts], faces=[faces.verts_idx.to(device)], textures=tex)
mesh_list.append(mesh)
if len(mesh_list) == 1:
return mesh_list[0]
@@ -308,9 +304,7 @@ def _parse_face(
# Subdivide faces with more than 3 vertices. See comments of the
# load_obj function for more details.
for i in range(len(face_verts) - 2):
faces_verts_idx.append(
(face_verts[0], face_verts[i + 1], face_verts[i + 2])
)
faces_verts_idx.append((face_verts[0], face_verts[i + 1], face_verts[i + 2]))
if len(face_normals) > 0:
faces_normals_idx.append(
(face_normals[0], face_normals[i + 1], face_normals[i + 2])
@@ -367,8 +361,7 @@ def _load(f_obj, data_dir, load_textures=True):
tx = [float(x) for x in line.split()[1:3]]
if len(tx) != 2:
raise ValueError(
"Texture %s does not have 2 values. Line: %s"
% (str(tx), str(line))
"Texture %s does not have 2 values. Line: %s" % (str(tx), str(line))
)
verts_uvs.append(tx)
elif line.startswith("vn "):
@@ -397,17 +390,13 @@ def _load(f_obj, data_dir, load_textures=True):
# Repeat for normals and textures if present.
if len(faces_normals_idx) > 0:
faces_normals_idx = _format_faces_indices(
faces_normals_idx, normals.shape[0]
)
faces_normals_idx = _format_faces_indices(faces_normals_idx, normals.shape[0])
if len(faces_textures_idx) > 0:
faces_textures_idx = _format_faces_indices(
faces_textures_idx, verts_uvs.shape[0]
)
if len(faces_materials_idx) > 0:
faces_materials_idx = torch.tensor(
faces_materials_idx, dtype=torch.int64
)
faces_materials_idx = torch.tensor(faces_materials_idx, dtype=torch.int64)
# Load materials
material_colors, texture_images = None, None

49
pytorch3d/io/ply_io.py
View File

@@ -4,15 +4,17 @@
"""This module implements utility functions for loading and saving meshes."""
import numpy as np
import pathlib
import struct
import sys
import warnings
from collections import namedtuple
from typing import Optional, Tuple
import numpy as np
import torch
_PlyTypeData = namedtuple("_PlyTypeData", "size struct_char np_type")
_PLY_TYPES = {
@@ -257,11 +259,7 @@ def _try_read_ply_constant_list_ascii(f, definition: _PlyElementType):
"ignore", message=".* Empty input file.*", category=UserWarning
)
data = np.loadtxt(
f,
dtype=np_type,
comments=None,
ndmin=2,
max_rows=definition.count,
f, dtype=np_type, comments=None, ndmin=2, max_rows=definition.count
)
except ValueError:
f.seek(start_point)
@@ -301,9 +299,7 @@ def _parse_heterogenous_property_ascii(datum, line_iter, property: _Property):
length = int(value)
except ValueError:
raise ValueError("A list length was not a number.")
list_value = np.zeros(
length, dtype=_PLY_TYPES[property.data_type].np_type
)
list_value = np.zeros(length, dtype=_PLY_TYPES[property.data_type].np_type)
for i in range(length):
inner_value = next(line_iter, None)
if inner_value is None:
@@ -404,8 +400,7 @@ def _read_ply_element_struct(f, definition: _PlyElementType, endian_str: str):
values. There is one column for each property.
"""
format = "".join(
_PLY_TYPES[property.data_type].struct_char
for property in definition.properties
_PLY_TYPES[property.data_type].struct_char for property in definition.properties
)
format = endian_str + format
pattern = struct.Struct(format)
@@ -414,10 +409,7 @@ def _read_ply_element_struct(f, definition: _PlyElementType, endian_str: str):
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)
]
data = [pattern.unpack_from(bytes_data, i * size) for i in range(definition.count)]
return data
@@ -475,9 +467,7 @@ def _try_read_ply_constant_list_binary(
return output
def _read_ply_element_binary(
f, definition: _PlyElementType, big_endian: bool
) -> list:
def _read_ply_element_binary(f, definition: _PlyElementType, big_endian: bool) -> list:
"""
Decode all instances of a single element from a binary .ply file.
@@ -515,9 +505,7 @@ def _read_ply_element_binary(
data = []
for _i in range(definition.count):
datum = []
for property, property_struct in zip(
definition.properties, property_structs
):
for property, property_struct in zip(definition.properties, property_structs):
size = property_struct.size
initial_data = f.read(size)
if len(initial_data) != size:
@@ -656,28 +644,19 @@ def load_ply(f):
if face is None:
raise ValueError("The ply file has no face element.")
if (
not isinstance(vertex, np.ndarray)
or vertex.ndim != 2
or vertex.shape[1] != 3
):
if not isinstance(vertex, np.ndarray) or vertex.ndim != 2 or vertex.shape[1] != 3:
raise ValueError("Invalid vertices in file.")
verts = torch.tensor(vertex, 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
):
if len(face_head.properties) != 1 or face_head.properties[0].list_size_type is None:
raise ValueError("Unexpected form of faces data.")
# face_head.properties[0].name is usually "vertex_index" or "vertex_indices"
# but we don't need to enforce this.
if isinstance(face, np.ndarray) and face.ndim == 2:
if face.shape[1] < 3:
raise ValueError("Faces must have at least 3 vertices.")
face_arrays = [
face[:, [0, i + 1, i + 2]] for i in range(face.shape[1] - 2)
]
face_arrays = [face[:, [0, i + 1, i + 2]] for i in range(face.shape[1] - 2)]
faces = torch.tensor(np.vstack(face_arrays), dtype=torch.int64)
else:
face_list = []
@@ -687,9 +666,7 @@ def load_ply(f):
if face_item.shape[0] < 3:
raise ValueError("Faces must have at least 3 vertices.")
for i in range(face_item.shape[0] - 2):
face_list.append(
[face_item[0], face_item[i + 1], face_item[i + 2]]
)
face_list.append([face_item[0], face_item[i + 1], face_item[i + 2]])
faces = torch.tensor(face_list, dtype=torch.int64)
return verts, faces