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issue2 #4

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zyy1234q opened this issue Jul 9, 2024 · 9 comments
Open

issue2 #4

zyy1234q opened this issue Jul 9, 2024 · 9 comments

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@zyy1234q
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zyy1234q commented Jul 9, 2024

I noticed that you use 0.03cm voxels to downsample, and your comparison method is 0.05cm voxels downsample, is this an unfair comparison?

@Jiang-HB
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Jiang-HB commented Jul 9, 2024

We also use voxel-size with 0.05m to pre-process the data. Please refer to the misc/cal_fcgf.py and misc/cal_fpfh.py for more details.

@zyy1234q
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zyy1234q commented Jul 9, 2024 via email

@Jiang-HB
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Jiang-HB commented Jul 9, 2024

Is it possible to increase the number of nodes from 5000 to 8000 or 10000? A smaller number of nodes could indeed degrade the final performance.

@zyy1234q
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zyy1234q commented Jul 9, 2024 via email

@Jiang-HB
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Jiang-HB commented Jul 9, 2024

I tested the model on both the V100 (32GB) and the TITAN RTX (24GB). Both tests were successful without encountering any ‘out of memory’ errors. Therefore, it’s advisable to increase the numnode value as much as possible on your machine with 24G memory. The numnode of 5000 is too small.

@zyy1234q
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zyy1234q commented Jul 9, 2024 via email

@Jiang-HB
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Jiang-HB commented Jul 9, 2024

Yes, I suggest adding an if-else statement at Line 40 in "test_3DMatch.py" to prevent this error. For example, if numnode > 10000 (determined by yourself), you can clip them to 10000 using src_keypts[:, :10000]. As such, you can constrain the scale of too large input.

@zyy1234q
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zyy1234q commented Jul 9, 2024 via email

@zyy1234q
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zyy1234q commented Sep 4, 2024 via email

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