detect_and_plot_collisions.py

# -*- coding: utf-8 -*-

# Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. (MPG) is
# holder of all proprietary rights on this computer program.
# You can only use this computer program if you have closed
# a license agreement with MPG or you get the right to use the computer
# program from someone who is authorized to grant you that right.
# Any use of the computer program without a valid license is prohibited and
# liable to prosecution.
#
# Copyright©2019 Max-Planck-Gesellschaft zur Förderung
# der Wissenschaften e.V. (MPG). acting on behalf of its Max Planck Institute
# for Intelligent Systems and the Max Planck Institute for Biological
# Cybernetics. All rights reserved.
#
# Contact: ps-license@tuebingen.mpg.de

from __future__ import absolute_import
from __future__ import print_function
from __future__ import division

import sys
import os

import time

import argparse

try:
    input = raw_input
except NameError:
    pass

import torch
import torch.nn as nn
import torch.autograd as autograd

from copy import deepcopy

import numpy as np
import tqdm

import trimesh
import pyrender
from mesh_intersection.bvh_search_tree import BVH


if __name__ == "__main__":

    device = torch.device('cuda')

    parser = argparse.ArgumentParser()
    parser.add_argument('mesh_fn', type=str,
                        help='A mesh file (.obj, .ply, e.t.c.) to be checked' +
                        ' for collisions')
    parser.add_argument('--max_collisions', default=8, type=int,
                        help='The maximum number of bounding box collisions')

    args, _ = parser.parse_known_args()

    mesh_fn = args.mesh_fn
    max_collisions = args.max_collisions

    input_mesh = trimesh.load(mesh_fn)

    print('Number of triangles = ', input_mesh.faces.shape[0])

    vertices = torch.tensor(input_mesh.vertices,
                            dtype=torch.float32, device=device)
    faces = torch.tensor(input_mesh.faces.astype(np.int64),
                         dtype=torch.long,
                         device=device)

    batch_size = 1
    triangles = vertices[faces].unsqueeze(dim=0)

    m = BVH(max_collisions=max_collisions)

    torch.cuda.synchronize()
    start = time.time()
    outputs = m(triangles)
    torch.cuda.synchronize()
    print('Elapsed time', time.time() - start)

    outputs = outputs.detach().cpu().numpy().squeeze()

    collisions = outputs[outputs[:, 0] >= 0, :]
    print(collisions.shape)

    print('Number of collisions = ', collisions.shape[0])
    print('Percentage of collisions (%)',
          collisions.shape[0] / float(triangles.shape[1]) * 100)
    recv_faces = input_mesh.faces[collisions[:, 0]]
    intr_faces = input_mesh.faces[collisions[:, 1]]

    material = pyrender.MetallicRoughnessMaterial(
        metallicFactor=0.0,
        alphaMode='BLEND',
        baseColorFactor=[0.3, 0.3, 0.3, 0.99])
    recv_material = pyrender.MetallicRoughnessMaterial(
        metallicFactor=0.0,
        alphaMode='BLEND',
        baseColorFactor=[0.0, 0.9, 0.0, 1.0])
    intr_material = pyrender.MetallicRoughnessMaterial(
        metallicFactor=0.0,
        alphaMode='BLEND',
        baseColorFactor=[0.9, 0.0, 0.0, 1.0])

    main_mesh = pyrender.Mesh.from_trimesh(input_mesh, material=material)

    recv_mesh = pyrender.Mesh.from_trimesh(
        trimesh.Trimesh(input_mesh.vertices, recv_faces),
        material=recv_material)
    intr_mesh = pyrender.Mesh.from_trimesh(
        trimesh.Trimesh(input_mesh.vertices, intr_faces),
        material=intr_material)

    scene = pyrender.Scene(bg_color=[0.0, 0.0, 0.0, 1.0],
                           ambient_light=(0.3, 0.3, 0.3))
    scene.add(main_mesh)
    scene.add(recv_mesh)
    scene.add(intr_mesh)

    pyrender.Viewer(scene, use_raymond_lighting=True, cull_faces=False)