I am looking for an existing jetson nano application that utilizes tensorflow AND YOLO V3 Tiny. If someone can recommend a tutorial to me, I would also be very pleased.
It is also important that there is the possibility to re-train the pretrained weights with my own dataset.
I already tried several tutorial but was facing always different issues / problems / errors and have not yet managed to get an application up and running. One reason is unfortunately also my lack of experience.
Here is some information about my nano and installed software + packages:
Jetpack 4.3
Tensorflow 2.1.0
Python 3.6.9 (it is important for me that I can use python. The version is not the deciding factor.)
Do you have any dependences on TensorFlow,
If not, it’s recommended to use our TLT toolkit for transfer learning and use Deepstream SDK for deploying.
perhaps it is helpful if I briefly explain what I want to use the Nano for.
I want to detect and track people to count how often they walk through a certain area. (This is the topic of my masterthesis.)
It is mandatory to use SSD or YOLO V3 (Tiny).
I could use the TLT toolkit on the Nano itself because there is no obligation to use TensorFlow on the Nano.
But the training of the pre-training model shall be done on the virtual machine of the university (independent of the Nano). In this respect there is a dependence on TensorFlow. And it is not possible to install the TLT tollkit on the vm.
Therefore I don’t now if it is possible to use the TLT toolkit for my application?
I suspect it is easier to use another existing application / model that is indepentent of the TLT toolkit.
Please correct me if I’m wrong.
Yolo will get you your object detections for like people or cars, you can use yolov3 tiny if it is a requirement but would also look at yolov4 and the non tiny versions to compare performance and accuracy across some different models.
For tracking you need a tracker like DEEP_SORT then to do the line counting just need some python logic to have a line and check of the tracked objects moved across it.
There are a decent number of good examples of yolo and deep sort implementations on github if you do some googling, best of luck
Also there are models for deep sort and yolo already out there so no training is needed
for extra points you could also look at getting the yolo model running on tensorRT for better performance and or through the triton inference server, there are also some hand githubs, have fun
thanks a lot for your advice and suggestions.
I have already tried this ones:
But I did not make anything run because of different errors. Sometimes the requirements are not met, sometimes the Nano is running out of memory and so on. I got a lot of help here and could solve some problems but finally I made nothing work as intended.
It is quite possible that my little experience makes things more difficult.
Therefore I am looking for an application that is especially suitable for the Nano. I hope that in this way I can avoid problems concerning the requirements and also the out of memory errors.
Since I just tried YOLO V3 (Tiny) so far I will give YOLO V4 a try. Maybe I’ll have better luck with that.
Does your school machine support darknet, which is developed by the YOLO’s author?
If yes, it’s recommended to train your database with darknet directly.
You can also verify the model with the API provided in darknet.
After that, you can deploy the new YOLOv3 model with Deepstream and enable the tracker that integrated into Deepstream.
thanks for your recommendation. I have a question regarding the deepstream pdf you shared in your post.
Is it necessary to work with C++ or is there a way to work only with python?
Hi Chris,
I wanted to know if you were able to run deep sort on your nano?
I try to run deep sort on my jetson Xavier NX unfortunately without success.
I tried a lot of repo my last repo was FastMOT : GitHub - GeekAlexis/FastMOT: High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
I would be happy to know if you have found solution to your problem and if you have some repo or tutorial to send?
Thank you:)