Feature Extraction From model

• Hardware Platform (Jetson / GPU) GTX 1650
• DeepStream Version
• TensorRT Version7.0.0.11
• NVIDIA GPU Driver Version (valid for GPU only) 450.51
• Issue Type( questions, new requirements, bugs) question


I want to use slowfast_4x16_resnet50_kinetics400 in deepstream but as feature extractor not a classifier. This model is a 400 classes classifier, but I don’t use this output, instead I am using the output of an earlier layer. How can I achieve that in deepstream?.

The model is in MXNET, in my code I call it like that, note that feat_ext=True

from gluoncv.model_zoo import get_model
net = get_model(name='slowfast_4x16_resnet50_kinetics400', nclass=400, pretrained=True, feat_ext=True, num_segments=1, num_crop=1)

I want to do the same thing in deepstream.


First, please find the layer name of the feature extractor layer.
And set it as the output in the Deepstream configure.

Then, you can get the Tensor raw data with the similar API as following:


1 Like

Thank you.