As Fabrizio says, TensorBoard is a great tool for visualizing the contents of your summary logs. However, if you want to perform a custom analysis, you can use tf.train.summary_iterator() function to loop over all of the tf.Event and tf.Summary protocol buffers in the log:
for summary in tf.train.summary_iterator("/path/to/log/file"):
# Perform custom processing in here.
UPDATE for tf2:
from tensorflow.python.summary.summary_iterator import summary_iterator
You need to import it, that module level is not currently imported by default. On 2.0.0-rc2