423A35C7/pytorch3d
1
0
Fork 0
mirror of https://github.com/facebookresearch/pytorch3d.git synced 2025-12-25 08:40:35 +08:00
Code Issues Packages Projects Releases Wiki Activity

Address black + isort fbsource linter warnings

Browse Source 
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
Download Patch File Download Diff File Expand all files Collapse all files

70
pytorch3d/structures/meshes.py
View File

@@ -1,6 +1,7 @@
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
from typing import List
import torch
from . import utils as struct_utils
@@ -314,14 +315,11 @@ class Meshes(object):
if isinstance(verts, list) and isinstance(faces, list):
self._verts_list = verts
self._faces_list = [
f[f.gt(-1).all(1)].to(torch.int64) if len(f) > 0 else f
for f in faces
f[f.gt(-1).all(1)].to(torch.int64) if len(f) > 0 else f for f in faces
]
self._N = len(self._verts_list)
self.device = torch.device("cpu")
self.valid = torch.zeros(
(self._N,), dtype=torch.bool, device=self.device
)
self.valid = torch.zeros((self._N,), dtype=torch.bool, device=self.device)
if self._N > 0:
self.device = self._verts_list[0].device
self._num_verts_per_mesh = torch.tensor(
@@ -348,18 +346,14 @@ class Meshes(object):
elif torch.is_tensor(verts) and torch.is_tensor(faces):
if verts.size(2) != 3 and faces.size(2) != 3:
raise ValueError(
"Verts and Faces tensors have incorrect dimensions."
)
raise ValueError("Verts and Faces tensors have incorrect dimensions.")
self._verts_padded = verts
self._faces_padded = faces.to(torch.int64)
self._N = self._verts_padded.shape[0]
self._V = self._verts_padded.shape[1]
self.device = self._verts_padded.device
self.valid = torch.zeros(
(self._N,), dtype=torch.bool, device=self.device
)
self.valid = torch.zeros((self._N,), dtype=torch.bool, device=self.device)
if self._N > 0:
# Check that padded faces - which have value -1 - are at the
# end of the tensors
@@ -400,12 +394,8 @@ class Meshes(object):
# Set the num verts/faces on the textures if present.
if self.textures is not None:
self.textures._num_faces_per_mesh = (
self._num_faces_per_mesh.tolist()
)
self.textures._num_verts_per_mesh = (
self._num_verts_per_mesh.tolist()
)
self.textures._num_faces_per_mesh = self._num_faces_per_mesh.tolist()
self.textures._num_verts_per_mesh = self._num_verts_per_mesh.tolist()
def __len__(self):
return self._N
@@ -665,8 +655,7 @@ class Meshes(object):
self._verts_padded_to_packed_idx = torch.cat(
[
torch.arange(v, dtype=torch.int64, device=self.device)
+ i * self._V
torch.arange(v, dtype=torch.int64, device=self.device) + i * self._V
for (i, v) in enumerate(self._num_verts_per_mesh)
],
dim=0,
@@ -706,15 +695,10 @@ class Meshes(object):
tensor of normals of shape (N, max(V_n), 3).
"""
if self.isempty():
return torch.zeros(
(self._N, 0, 3), dtype=torch.float32, device=self.device
)
return torch.zeros((self._N, 0, 3), dtype=torch.float32, device=self.device)
verts_normals_list = self.verts_normals_list()
return struct_utils.list_to_padded(
verts_normals_list,
(self._V, 3),
pad_value=0.0,
equisized=self.equisized,
verts_normals_list, (self._V, 3), pad_value=0.0, equisized=self.equisized
)
def faces_normals_packed(self):
@@ -750,15 +734,10 @@ class Meshes(object):
tensor of normals of shape (N, max(F_n), 3).
"""
if self.isempty():
return torch.zeros(
(self._N, 0, 3), dtype=torch.float32, device=self.device
)
return torch.zeros((self._N, 0, 3), dtype=torch.float32, device=self.device)
faces_normals_list = self.faces_normals_list()
return struct_utils.list_to_padded(
faces_normals_list,
(self._F, 3),
pad_value=0.0,
equisized=self.equisized,
faces_normals_list, (self._F, 3), pad_value=0.0, equisized=self.equisized
)
def faces_areas_packed(self):
@@ -797,9 +776,7 @@ class Meshes(object):
return
faces_packed = self.faces_packed()
verts_packed = self.verts_packed()
face_areas, face_normals = mesh_face_areas_normals(
verts_packed, faces_packed
)
face_areas, face_normals = mesh_face_areas_normals(verts_packed, faces_packed)
self._faces_areas_packed = face_areas
self._faces_normals_packed = face_normals
@@ -813,9 +790,7 @@ class Meshes(object):
refresh: Set to True to force recomputation of vertex normals.
Default: False.
"""
if not (
refresh or any(v is None for v in [self._verts_normals_packed])
):
if not (refresh or any(v is None for v in [self._verts_normals_packed])):
return
if self.isempty():
@@ -867,8 +842,7 @@ class Meshes(object):
Computes the padded version of meshes from verts_list and faces_list.
"""
if not (
refresh
or any(v is None for v in [self._verts_padded, self._faces_padded])
refresh or any(v is None for v in [self._verts_padded, self._faces_padded])
):
return
@@ -887,16 +861,10 @@ class Meshes(object):
)
else:
self._faces_padded = struct_utils.list_to_padded(
faces_list,
(self._F, 3),
pad_value=-1.0,
equisized=self.equisized,
faces_list, (self._F, 3), pad_value=-1.0, equisized=self.equisized
)
self._verts_padded = struct_utils.list_to_padded(
verts_list,
(self._V, 3),
pad_value=0.0,
equisized=self.equisized,
verts_list, (self._V, 3), pad_value=0.0, equisized=self.equisized
)
# TODO(nikhilar) Improve performance of _compute_packed.
@@ -1055,9 +1023,7 @@ class Meshes(object):
face_to_edge = inverse_idxs[face_to_edge]
self._faces_packed_to_edges_packed = face_to_edge
num_edges_per_mesh = torch.zeros(
self._N, dtype=torch.int32, device=self.device
)
num_edges_per_mesh = torch.zeros(self._N, dtype=torch.int32, device=self.device)
ones = torch.ones(1, dtype=torch.int32, device=self.device).expand(
self._edges_packed_to_mesh_idx.shape
)