June 2018
Intermediate to advanced
436 pages
10h 33m
English
Now we start creating the network by combining convolutional, max pooling, dense (feedforward), and recurrent (LSTM) layers to classify each frame of a video clip. First, we need to define some hyperparameters and the necessary instantiation, as shown here:
private static MultiLayerConfiguration conf;private static MultiLayerNetwork net; private static String modelPath = "bin/ConvLSTM_Model.zip";private static int NUM_CLASSES;private static int nTrainEpochs = 100;
Here, NUM_CLASSES is the number of classes from UCF101 calculated as the quantity of directories in the dataset base directory:
NUM_CLASSES = reader.labelMap().size();
Then we start the training by calling the networkTrainer() method. Well, as I stated ...