How to train a secondary detector (SGIE)

Accelerated Computing Intelligent Video Analytics TAO Toolkit
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After a steep learning period with loads of help from the mods and posts from other members, I’m having fun in tryingtraining a model (DetectNet v2 detector) through TLT and run it in a custom built Deepstream App. Now I want to train a secondary detector (SGIE) that further specifies the primary predictions.

While I already have labeled 1000s of images, I came across a forumpost, stating the secondary detector (SGIE) actually is an image classification model instead of an object detector.
I have 3 questions regarding the SGIE;

  1. Is the SGIE (no back-to-back detector) indeed an image classifier and do I need to use the TLT Image classifier Jupyter notebook?
  2. Can I use a trained object detector as SGIE, without being used as a back-to-back detector
  3. If I need to train an image classifier, does it use the labeled bounding boxes (As area if interest)?

Thanks in advance!

Gerard

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  1. It depends on your target. You want to train a SGIE as an image classification model , right? If yes, you can use TLT classification network to train.
  2. What do you mean by “trained object detector”? Is it the primary GIE ?
  3. If you train a classification network, there are no bboxes. You just need to split your images into different classes you want to train. You can refer to classification Jupyter notebook.
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Hi @Morganh,

Thanks for the post.

You have specified to refer to classification Jupyter notebook for the classification network train,

  • Can you provide a link to that notebook?
  • Is annotated data with coordinates required for classification network(sgie)?
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Download jupyter notebooks from https://docs.nvidia.com/metropolis/TLT/tlt-user-guide/text/requirements_and_installation.html#use-the-examples

wget --content-disposition https://api.ngc.nvidia.com/v2/resources/nvidia/tlt_cv_samples/versions/v1.0.2/zip -O tlt_cv_samples_v1.0.2.zip
unzip -u tlt_cv_samples_v1.0.2.zip -d ./tlt_cv_samples_v1.0.2 && rm -rf tlt_cv_samples_v1.0.2.zip && cd ./tlt_cv_samples_v1.0.2

When you train a classification network, just need to split your images into different classes you want to train.

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Hey @Morganh ,

You have mentioned to split the images into folders,

  • Does that require annotation to KITTI format?

  • What is the directory structure I have to use while training for gender: male and female for example?

Thanks

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image