I use TAO to train a detectnet_v2:resnet10 model. TAO is an excellent tool !
I’d like to use offline data augmentation for a special use case and I’m not sure I can do it with TAO. Perhaps I need a tool of my own.
Here is the use case:
Images of different size enter the network. They all have the same width but different height. These image contains people and the people have a “human aspect ratio” on them. Now, when the image enter the network, the people are re-scaled vertically right ? They get smaller or taller depending of the original image height.
Here is my understanding:
So I understand that I have to create a data augmentation to make the people randomly taller or smaller. But apparently I cannot zoom in or zoom out in only one direction.
Am I right when I understand that the network will create various aspect ratio for people ?
What’s the best way to train the model with such a constraint ?