If you use this toolbox as part of a research project, please consider citing the corresponding paper
@inproceedings{.., title={}, author={}, booktitle={}, year={} }
To train the network, you first need to run and change the following code:
(1) Step1_preproc.py:
Note I used first 650 examples for training and 50 for validation with 1000 frames per storage. (line 85-91)
change input directory: line 37: raise NotImplementedError("TODO: implement this function.")-->set to data = r"I:\Kaggle_multimodal\Training" change destination directory: lin 87-90: dest = r"I:\Kaggle_multimodal\Training_prepro\train_wudi" # dir to destination processed data
(2) Step2_Train_CNN.py: in the file: classes/hyperparameters.py you will have all the specs, e.g., train, valid dir,line 14-19: line 27: use.fast_conv
It takes about 600 second for each example file . (I use Theano GPU model, but I reckon CPU model should almost of the same speed)
Voila, here you go.
If you read the code and find it really hard to understand, please send feedback to: stevenwudi@gmail.com Thank you!