Skeletonizing Merge Task produces error

Skeletonizing Merge Task produces error

Just to follow up on the above, those reference were very useful in helping tweak parameters. When I did modify the parameters, both steps seemed to complete successfully

[william-silversmith]

Hi vikramcns,

Thanks for writing in! The floating point bounds on the skeleton file is probably the culprit. Can you share with me your info file? That would help me better understand what is going on.

Will

yes! the contents of the info file in the skeletons_mip_0 folder are below:

{"@type": "neuroglancer_skeletons", "transform": [1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0], "vertex_attributes": [{"id": "radius", "data_type": "float32", "num_components": 1}], "spatial_index": {"resolu
tion": [4200.0, 4200.0, 4200.0], "chunk_size": [2150400.0, 2150400.0, 2150400.0]}, "mip": 0}

[william-silversmith]

Interesting, can you also show me the info file for the main image volume?

Yes, see below. The ellipses indicate downsampled scales:

{
  "data_type": "uint64",
  "mesh": "mesh_mip_0_err_40",
  "num_channels": 1,
  "scales": [
    {
      "chunk_sizes": [
        [
          128,
          128,
          128
        ]
      ],
      "compressed_segmentation_block_size": [
        8,
        8,
        8
      ],
      "encoding": "compressed_segmentation",
      "key": "4200.0_4200.0_4200.0",
      "resolution": [
        4200.0,
        4200.0,
        4200.0
      ],
      "size": [
        4904,
        4904,
        2946
      ],
      "voxel_offset": [
        0,
        0,
        0
      ]
    },...
  ],
  "skeletons": "skeletons_mip_0",
  "type": "segmentation"
}

[william-silversmith]

Okay, so I think that on cursory inspection, handling these floating point names is a feature I should modify cloudvolume to support. Give me a bit, I think I almost have a fix.

Perfect, thank you!

[william-silversmith]

Okay, try installing pip install cloud-volume==8.9.2 and see if that fixes things. There could be other problems that crop up, but that one should not be the issue anymore.

I will test that now and get back to you shortly

seems to be working so far! I will let you know if anything breaks

so after a few hours it looks like there is no progress on the actual tasks. the progress bar shows 0/999 after 3 hours with parallel=16 for the fusing skeletons step

[william-silversmith]

You may have selected parameters during initial skeletonization that are not appropriate for your dataset. If there are loops or many tiny branches introduced, this can result in very slow merging (with poor final results too). You can also try killing the parallel job and seeing if a single core makes any progress. If its taking up too much memory and your working with swap, that could lead to very slow progress.

Give this tutorial a look, it might help you debug your run:

• https://github.com/seung-lab/kimimaro/wiki/A-Pictorial-Guide-to-TEASAR-Skeletonization
• https://github.com/seung-lab/kimimaro/wiki/Intuition-for-Setting-Parameters-const-and-scale

[william-silversmith]

Fantastic! You can check if they make sense by visualizing them in neuroglancer.

…

On Sun, Sep 11, 2022, 1:50 PM vikramcns ***@***.***> wrote: When I modified the parameters, both steps seemed to complete successfully — Reply to this email directly, view it on GitHub <#139 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AATGQSM32BLQY7DIIL5CQ5DV5YLVPANCNFSM6AAAAAAQGDHPSA> . You are receiving this because you commented.Message ID: ***@***.***>

[william-silversmith]

perfect! glad to hear it. hope your job is successful!

…

On Tue, Sep 6, 2022, 7:07 PM vikramcns ***@***.***> wrote: seems to be working so far! I will let you know if anything breaks — Reply to this email directly, view it on GitHub <#139 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AATGQSOUQBFJ6A5QTH4N73LV47FCTANCNFSM6AAAAAAQGDHPSA> . You are receiving this because you commented.Message ID: ***@***.***>

[william-silversmith]

Closing due to inactivity. Reopen if you need it!