Hello, Dear community.
I want to share the problem I am facing now.
Jetson TX2:
Jetpack4.5
Orbitty carrier
Tensorflow 2.4.0
Keras 2.4.0
python 3.6
Host:
Ubuntu 18.04
Tensorflow 2.4.0
keras 2.4.0
python 3.6
In the host, I have created a siamese network, and I have trained. For the siamese network, I am using VGG19, and I am doing fine-tuning. The problem comes in the jetson TX2. When I run the facial recognition python script (including the model from the host), the face detection with OpenCV runs a little bit slow, but when it has to recognize the face, the jetson tx2 runs too slow.
To help me to fix this problem, what do you need to know? Why the siamese network inference run too slow in jetson tx2?
Hi dear @AastaLLL
In the host machine, I am using the GTX 1060i.
Obviously, in the host, the performance is excellent and fast.
What is your recommendation? Shall I move to vgg16?
How can I improve the performance of the jetson tx2 using vgg19? or shall I move to vgg16?
Is the performance too slow because I am using a siamese network?