densecap-tensorflow
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about context feature in code
Hi. When reading your code, I confused that why the context feature is implemented as in the code: $ROOT/lib/nets/network/py line:340
global_feature, region_features = tf.split(region_features, [1, -1], axis=0)
around codes as follows
region_features = slim.fully_connected(fc7, cfg.EMBED_DIM,
weights_initializer=initializer,
trainable=is_training,
activation_fn=None, scope='region_features')
if cfg.CONTEXT_FUSION:
# global_feature [1, cfg.EMBED_DIM(512)]
global_feature, region_features = tf.split(region_features, [1, -1], axis=0)
batch_size = tf.shape(region_features)[0]
# global_feature_rep [batch_size(256), cfg.EMBED_DIM(512)]
global_feature_rep = tf.tile(global_feature, [batch_size, 1])
gfeat_lstm_cell = rnn.BasicLSTMCell(cfg.EMBED_DIM, forget_bias=1.0,
state_is_tuple=True)
else:
batch_size = tf.shape(region_features)[0]
I do not understand why $region_features$ contain the $global_feature$ in the axis 0?
thanks a lot.