I wonder do you have plans to support resuming from checkpoints for classification? As we all know, in terms of training ImageNet, the training process is really long and it can be interrupted somehow, but I haven't notice any code related to "resume" in scripts/classification/train_imagenet.py.
In fact, you can find a issue very similar to this one, check #110
lianuo said just feed st-gcn (3,t,18,1) frames, as t he used is 20, I think it's a good solution but if you directly use the pre-trained model, or even trained on your own dataset without modifying the structure of the st-gcn network, the result will be quite terrible!
Look deep into the structure! If you keep temporal size
Apply ML to the skeletons from OpenPose; 9 actions; multiple people. (WARNING: I'm sorry that this is only good for course demo, not for real world applications !!! Those ary very difficult !!!)
Video-friendly caffe -- comes with the most recent version of Caffe (as of Jan 2019), a video reader, 3D(ND) pooling layer, and an example training script for C3D network and UCF-101 data
Hi, thanks for the great code!
I wonder do you have plans to support resuming from checkpoints for classification? As we all know, in terms of training ImageNet, the training process is really long and it can be interrupted somehow, but I haven't notice any code related to "resume" in
scripts/classification/train_imagenet.py.Maybe @hetong007 ? Thanks in advance.