Quote:
Originally Posted by faust1706
Are you going to make a script to install caffe with cudNN support? (if not, I'll write one up this weekend, or at the least a step by step guide). I feel caffe + cuda + cudNN is a more valuable and a different application of cuda than cuda based opencv.
My arguement: while opencv is great, teams have just about exhausted the real time use for it. Even with what 900 did, they were getting 15 fps. It's time to move on if we wish to advance what we are doing. The easiest way to do that, I argue, is to switch our roots entirely to a library that is more encompassing.
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I installed the cuda libraries using the Jetson instructions. I think an automatic script would be a great idea.
The biggest issue for teams and the neural network stuff is going to be collecting good training data and building a useful model. Ideally you'd have targets for recognition in-situ, but practice fields are usually unavailable until later in the season.
I wouldn't take a single implementation as setting the bar for what's possible. Even setting aside the CUDA cores, 4 2ghz ARMv7 cores are quite capable.