For configuring the training of some TensorFlow SSD models it's necessary to know the number of examples in the evaluation dataset. In order to come up with this number, we will add a function into the analyze.py module which will take a directory containing TFRecord files and count the number of examples contained in the TFRecord files within the directory. So the input will be a directory path and the output will be the total number of examples found in the TFRecord files in the directory.
For configuring the training of some TensorFlow SSD models it's necessary to know the number of examples in the evaluation dataset. In order to come up with this number, we will add a function into the
analyze.pymodule which will take a directory containing TFRecord files and count the number of examples contained in the TFRecord files within the directory. So the input will be a directory path and the output will be the total number of examples found in the TFRecord files in the directory.