Very nice project. The only note is that the installation of TensorRT is outdated. Just replace 'Install TensorFlow-GPU 2.0 and TensorRT Runtime:' section with the following. It may take some time to run.

%%bash

sudo apt install python3-libnvinfer

python3 -m pip install --upgrade tensorrt

The installation may be also verified by:

import tensorrt

print(tensorrt.__version__)

This is something that I was looking for. I've studied a lot of theories about TensorRT but this project gives a clear view of how to do it. Good job, and thanks for the awesome course.

One last thing, Please upload the TensorRT deployment of TensorFlow object detection on Jetson devices. That would be helpful

good content, but some code is out of date, especially the package installation part.

I do not recommend taking this type of course, take one and pass it, however after a few days I have tried to review the material, and my surprise is that it asks me to pay again to be able to review the material. Of course coursera gives me a small discount for having already paid it previously. It is very easy to download the videos and difficult to get hold of the material, but with ingenuity it is possible. Then I recommend uploading them to YouTube and keeping them private for when they want to consult (they avoid legal problems and can share with friends), then they can request a refund.

It's a very cool course, but it's outdated and underlying working environment won't let you proceed with practise just at the middle.

A lot has changed, float32 and float16 are now not faster than normal tensorflow. But but it is really good pipeline for model optimizing.

Great workshop, all the concepts were very well explained.

The first to introduce such a rare and important topic.

Excelent and compresed way of explaining TensorRT

Awesome project. Thank you so much.

Excellent guided course

Informative course

Very good...

The library versions is dated so it would be very hard for people, especially new learners, to setup the environment. But the lecturer and content is indeed amazing. I learned a lot about TF-TRT systematically.

Need more theoretical explanation on concepts

excellent

I expect for Coding and Implementation part but this is just theory based evaluation

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