depthai-experiments
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luxonis
Gaze Estimation Demo Latency?
Is there a reason why I'm getting a 5second delay/latency on the video feed with that demo? Is that a Mac OSX specific issue or it's the pipeline (got too deep?). Thank you.
Hi Raymond, It's not OS specific It's the current implementation that lacks nn results synchronization, we'll be working more on it so that gets implemented
Is that a problem across the entire Gen2 pipeline? I mean all demo got the same latency related issues?
No, there are ways to sync the nn results, here is an example - https://github.com/luxonis/depthai-experiments/tree/master/gen2-nn-sync
The latency is great with the nn demo! Let me learn this and see if I can apply that to others.
Thanks @raymondlo84 for taking this and applying it to the others! Much appreciated. (So as background, we implemented demos as we were refining the Gen2 system, so you are seeing it exactly correctly - we need to go through and update others to use the improvements/techniques learned from the initial implementations and resultant improvements to the API, or improvements to how it is used (or both).)
https://github.com/luxonis/depthai-experiments/pull/51 addressed this issue. I will close this issue once the PR is merged.
Thanks @raymondlo84 for taking this and applying it to the others! Much appreciated. (So as background, we implemented demos as we were refining the Gen2 system, so you are seeing it exactly correctly - we need to go through and update others to use the improvements/techniques learned from the initial implementations and resultant improvements to the API, or improvements to how it is used (or both).)
Glad to be able to help.
No, there are ways to sync the nn results, here is an example - https://github.com/luxonis/depthai-experiments/tree/master/gen2-nn-sync
What are the advantages and disadvantages of these two methods proposed in that demo?
@VanDavv can describe the two implementations used there in more detail.
The syncing is usually required when we want to display NN results on a continuous stream which is faster. The added latency to match those two up is at best the inference time of one frame.
In gen2 one can "desync" a slow consumer by settings its input to be non blocking. In this case NeuralNetwork.passthrough output can be used to determine on which input frame the inference was made.
The latency issue can also happen if ColorCamera is connected to a slow consumer in a blocking manner. That is something we have to further investigate, to send out most recent frames instead of old ones which got queued up.
