I want to improve a pre-trained model to detect people from above. What is the difference if I trained the model in TLT and DIGITS. From what I understand, both can improve pre-trained model and generate ready to deploy model for Jetson Nano.
The detectnet_v2 network in TLT is similar to DIGITS.
What I mean is more to the what objective and purpose difference between TLT and DIGITS? Because DIGITS and TLT offer improve pre-trained model functionality.
In TLT, ngc already provides the pre-trained models.
Hi. I need use my models (CNN’s) made in digits (caffe) and improve with TLT. It’s possible? If yes, How I do?
Other, anyone know How prune layer or connection in caffe with digits?
Only tlt format models can be pruned.
NVIDIA GPU Cloud(NGC) provides the pretrained weights.
We cannot ensure other pre-trained weights can work.
One more question. There are problem docker digits-tensorflow for Driver Version: 440.82 and CUDA Version: 10.2?
Digits run but not work when I creat job for model in TensorFlow.
Sorry, I did not understand what your problem is. Could you please give more details or the steps for reproducing? BTW, if it is not a TLT issue, I am afraid you can create a new topic under other forums.