I have gone through the provided notebooks to retrain the Gazenet model from the provided DeepStream Notebooks. But I am having trouble integrating the model into a DeepStream pipeline.
Does anyone have an example of how to use the GazeNet model (either Trained\Deployable), in a DeepStream pipeline? I have successfully generated a new etlt and also transformed it to a engine file, but I’m a bit stuck.
See Gaze Estimation — Transfer Learning Toolkit 3.0 documentation
The pretrained model for gaze estimation provided through NGC is available by default to use inside the TLT CV Inference Pipeline. You can also deploy a model trained through TLT workflow to the TLT CV Inference Pipeline. Refer to TLT CV Quick Start Scripts section for instructions of both options.
Please follow above inference pipeline.
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