89 lines
3.7 KiB
Python
89 lines
3.7 KiB
Python
# Copyright (c) 2019-2020, NVIDIA CORPORATION. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import numpy as np
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import os
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import pytest
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import shutil
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import torch
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import kaolin
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from kaolin.utils.testing import tensor_info
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from kaolin.experimental.dash3d.util import meshes_to_binary
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from kaolin.experimental.dash3d.util import point_clouds_to_binary
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@pytest.fixture(scope='module')
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def out_dir():
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# Create temporary output directory
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out_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), '_out')
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os.makedirs(out_dir, exist_ok=True)
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yield out_dir
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shutil.rmtree(out_dir) # Note: comment to keep output directory
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@pytest.fixture(scope='module')
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def meshes():
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vertices0 = np.array([[1.0, 2.0, 3.0],
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[10.0, 20.0, 30.0],
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[2.0, 4.0, 6.0],
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[15.0, 25.0, 35.0]], dtype=np.float32)
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faces0 = np.array([[0, 1, 2],
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[2, 1, 3]], dtype=np.int32)
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vertices1 = np.arange(0, 300).reshape((-1, 3))
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faces1 = np.stack([np.arange(0, 100),
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np.mod(np.arange(0, 100) + 1, 100),
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np.mod(np.arange(0, 100) + 2, 100)]).astype(np.int32).reshape((-1, 3))
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vertices2 = np.random.random((1, 9000)).reshape((-1, 3))
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faces2 = np.stack([np.mod(np.arange(0, 6000), 1000),
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np.ones((6000,)),
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np.random.randint(0, 2999 + 1, (6000,))]).astype(np.int32).reshape((-1, 3))
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return {"faces": [faces0, faces1, faces2],
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"vertices": [vertices0, vertices1, vertices2]}
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@pytest.fixture(scope='module')
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def pointclouds():
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pts0 = np.array([[1.0, 2.0, 3.0],
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[10.0, 20.0, 30.0],
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[2.0, 4.0, 6.0],
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[15.0, 25.0, 35.0]], dtype=np.float32)
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pts1 = np.arange(0, 300).astype(np.float32).reshape((-1, 3))
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pts2 = np.random.random((1, 9000)).astype(np.float32).reshape((-1, 3))
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return {"positions": [pts0, pts1, pts2]}
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class TestBinaryEncoding:
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def test_server_client_binary_compatibility(self, meshes, pointclouds, out_dir):
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# Encode and write mesh0+mesh1 and mesh2 to binary files
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binstr = meshes_to_binary(meshes['vertices'][0:2], meshes['faces'][0:2])
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with open(os.path.join(out_dir, 'meshes0_1.bin'), 'wb') as f:
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f.write(binstr)
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binstr = meshes_to_binary([meshes['vertices'][2]], [meshes['faces'][2]])
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with open(os.path.join(out_dir, 'meshes2.bin'), 'wb') as f:
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f.write(binstr)
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# Encode and write ptcloud0+ptcloud1 and pointcloud2 to binary files
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binstr = point_clouds_to_binary(pointclouds['positions'][0:2])
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with open(os.path.join(out_dir, 'clouds0_1.bin'), 'wb') as f:
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f.write(binstr)
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binstr = point_clouds_to_binary([pointclouds['positions'][2]])
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with open(os.path.join(out_dir, 'clouds2.bin'), 'wb') as f:
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f.write(binstr)
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# Execute javascript test that checks that these are parsed correctly
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js_test = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'test_binary_parse.js')
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os.system('npx mocha {}'.format(js_test)) # TODO: will npx work for everyone?
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