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I can confirm that setting
n_threads=1 after re-building open3d from the current git master branch fixes the reproducibility issue. Weirdly enough, the function also runs faster. Thanks again @griegler for your input.
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Thank you so much for your feedback Gernot. I will do that asap and let you know if it fixes the issue for me.
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IMPORTANT: Please use the following template to report the bug.
Describe the bug The mesh created from a point cloud using the create_from_point_cloud_poisson method is not the same across different calls to the function.
Please run the following Python code assuming a point cloud file
`import sys import open3d as o3d import numpy as np import pylab as plt
ntrials = 10 if len(sys.argv) > 1: ntrials = int(sys.argv)
pcd = o3d.io.read_point_cloud('data.ply')
meshes = [o3d.geometry.TriangleMesh.create_from_point_cloud_poisson(pcd, depth=8, width=0, scale=1.1, linear_fit=False)
for i in range(1 + ntrials)] vertices = np.array([m.vertices for m in meshes]) errors = np.max(np.abs(vertices - vertices), (1, 2))[1:] print('Errors:', errors) plt.plot(range(ntrials), errors, 'o:') plt.title('Poisson reconstruction randomness') plt.xlabel('Trial') plt.ylabel('Deviation wrt reference') plt.show() `
Expected behavior The mesh output by Poisson reconstruction should always be the same.
Environment (please complete the following information):
- Operating system: Ubuntu 18.04.4 LTS
- Python version: Python 3.6.9
- Open3D version: 0.9.0.0
- Is this remote workstation?:no
- How did you install Open3D?: pip
- Compiler version (if built from source):
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