Comments (2)
Backend and frontend both now threaded listeners (polling for a new message to receive) while being available locally to send a message if another component requires it. Using multiprocessing.connection
library for managing a connection over a socket.
Designed messages in JSON/dict format with "tags" describing the type of data, e.g. {"loss_values": loss_data, "render_image": image_data, "error_log": err_data}.
On frontend, created paradigm where any window that is interested in "listening" for certain tag can subscribe to the AppController
to be alerted about that data when a message with that tag is received.
Backend has not been changed like so since it is much more static.
Next, will be testing some simple messaging back and forth.
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At a workable state now where each window will be able to subscribe for the messages they want to listen for, and be automatically routed those messages from the AppController
. The ServerController
will take care of all the messages itself so as to keep networking tasks outside of the Trainer
, GaussianModel
, and Dataset
classes.
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Related Issues (20)
- Display training camera locations HOT 1
- Render thread slowed down by communication thread HOT 1
- Frontend camera path for renders
- Backend camera path for renders HOT 1
- Create documentation
- Web-based frontend HOT 1
- Combine standard OpenGL rendering with GS model HOT 3
- Loading existing model HOT 1
- Update GitHub landing page to look good! HOT 1
- Initialize model from the start HOT 1
- OpenGL rendering speed HOT 1
- Dataset creation from images HOT 1
- Create executable builds for frontend application HOT 1
- Launch backend from frontend HOT 1
- Edit tool panel HOT 3
- Add points edit operation HOT 1
- Remove points operation HOT 2
- Undo/redo edit operations HOT 1
- Depth rendering HOT 1
- Loading window and error window modals
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