I want to know if it is possible to integrate a custom deep learning model into your sdk. For example if one of the models provided for skeletal tracking is not good enough for my use case I need to do a custom training.
Thank you for your request.
Could you kindly elaborate a little bit on the use-case - if skeletal tracking isn’t good enough why Nuitrack could be useful at all ?
In case you have a better algorithm/model - why it can’t be used directly in this case?
For example: If I need to detect some more joints in the body and the I want to integrate this using C# I need to create all the code that is doing the inference in C++ and then some C# C++ interoperability.
If Nuitrack has already tested this pipeline instead of developing my custom pipeline (C++ C# ecc) I can modify the weights of the model and then pass some more parameters from C++ and C#. This, I supposed, could be the same for any type of integration that you have Unreal Unity ecc…
This will be much faster instead of creating a custom pipeline.
Thank you, it makes more sense now.
Do you have a commercial project which crucially requires this capability ?
Actually there are large number of AI cloud/edge deployment platforms on the market currently which provides all types of integrations and custom model import capabilities.
Yes I have, but as you correctly pointed out there are some AI cloud/edge options.
I wanted to know if nuitrack has this possibility because it has a plugin already developed for different types of camera and a plugin for unreal if i have understood correctly. That’s why I have asked.
@eric Sorry for late reply,
anyway we feel the need to provide additional comments.
These are correct.
Nuitrack (being kind of old / mature software) has plugins already developed for the most depth sensors on the market (this list is incomplete as Nuitrack is licensed by some sensor vendors as a white-label product).
In general, we are always interested in improving our tracking engines (instead of replacing them) and have a dedicated tools for that purpose.
We really didn’t thought about custom model integration, as the processing pipeline is always custom for different CNN models and Nuitrack has more non-trivial internals outside the model (model is 10% of the processing for AI, classical tracking engine doesn’t have “a model” at all).
Just out of curiosity / understanding of possibilities - what particular network/CNN architecture did you suppose to use/deploy/integrate ? (it would be great if you could kindly share this info)
Hi sorry for late answer. I have tested different deep learning software just for skeletal detection.
Yolov8
Mediapipe
YoloPose
Mediapipe is the most complete solution in my opinion, but has some drawback. Using it in C++ on windows is not easy.
The other solutions are not ready to use at least for a production environment in my opinion, but if you need to improve the model you can with custom training.
Other tool that I have tested is open pose,but not in depth. I think nuitrack is the best option for production, but the fact that is not possible to improve the pipeline is a bit blocking me to adopt, because if I cannot get the required specification I have not understood well how to improve the output.
As i said above I have a custom dataset and for some specific case my trained model is working better than mediapipe for example.