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Implement support for neuroglancer visualisation
It would be useful to implement visualisation of objects of class neurons
(and by default extensions of that) in the neuroglancer format. The following are the task check list that need to be completed (this is ongoing and hence will be frequently updated):
- [ ] Implement conversion to
precomputed
format: 1. Format spec for segments(skeletons) here: https://github.com/google/neuroglancer/blob/master/src/neuroglancer/datasource/precomputed/skeletons.md 2. See python implementation here for conversion from swc: https://github.com/seung-lab/cloud-volume/blob/c3d1f8005397f72d04720f864e9c95d63725b0c0/cloudvolume/skeleton.py#L908 3. See misc here: https://github.com/google/neuroglancer/issues/207 https://github.com/google/neuroglancer/issues/169 - [ ] Implement starting a
Node.js
session to communicate tohttp
port: 1. See example in python here: https://github.com/google/neuroglancer/tree/master/python 2. An exampler
package that does that is here: https://github.com/ColinFay/bubble - [ ] Further add segments, layers to the port for display
The ideal output in the http
port would be like below:
This task would be taken up once the urgent tasks in https://github.com/natverse/fafbseg/issues/ are completed
Dear Sri, I think this is a very interesting idea. Ideally one might be able to post to the same neuroglancer instance via python or R (not sure how easy that would be). Integrating local data in neuroglancer views with external data would certainly bring lots of possibilities. @perlman has a fair bit of experience with this.
Sent from my iPhone
On 16 Jul 2020, at 12:52, Sridhar Jagannathan [email protected] wrote:
This task would be taken up once the urgent tasks in https://github.com/natverse/fafbseg/issues/ are completed
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Some issues wrt to ongoing implementation here: https://github.com/google/neuroglancer/issues/261