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* Model class done, pipeline class still needs more visualization stuffs * Renaming the BaseDataContainer to DataloaderOutputs and adding documentation * Pushing more documentation, removing some trivial functions * Updating dict typing * Removing config dicts for collider * Passing tests * Pushing shell new dataloader * Saving work, need to fix NGP model's get_loss_dict and Pipeline * V1 of the ngp pipeline should be done. Need train script and debugging * Updating with latest instant-ngp code * Syntax updates from latest ngp graph code * Linter, removing unneeded code in new NGP graph code * Style * Should be good now. Linter is happy and the code is verbatum current instant-ngp * Everything done except novel view testing code * Fixing some nitpicks * Debugging dataloader * merged master * WOP. integrating pipeline with configs and notebook demo * removing model folder * a lot of name changing from Graph to Model * in progress... changing trainer to use pipeline... broken right now * pipeline code runs * switched to val dataset * makes run_eval.py work * updated configs for pipeline change * fixing test_run_train script * fixing black and linting * fix docs * small updates to trainer Co-authored-by: Jake Austin <jake-austin@berkeley.edu>
Python Kernel and Client Viewer App communication
The purpose of this document is to explain how to communicate from Python with the Client Viewer app. We will eventually move this into the read the docs.
- Python Kernel (nerfactory code)
- Bridge Server
- Client Viewer App
We have two types of components that we want to keep state updated in both locations.
- Widgets
- The widgets are used to keep track of the
- SceneNode
- The scene nodes are used to represent the three.js objects. The properties relevant to these objects are the following:
"object", "transform", "properties".
- The scene nodes are used to represent the three.js objects. The properties relevant to these objects are the following:
Checklist
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Currently using request-reply (REQ, REP with zmq). I.e., Python Kernel -> Bridge Server <-> Client Viewer App. We want a way to update the Python Kernel when the Bridge Server is updated. This requries some form of binding with callbacks. When the Bridge Server is updated, we want to update the binded Python variable. We can take inspiration from ipywidgets.