Convert the Inoutdoor dataset to a TFRecord file. (Specifically for the Object Detection Task)
This repository shall help to create a tfrecord file for the berkeley deep drive dataset. I have no affiliation with Berkeley and/or the deep drive team.
Now also supports the new data format
You can use the script create_tfrecord.py in order to create the TFRecord file you need.
--fold_type = ['train', 'val', 'test'] : Select for which fold you want to create the tfrecord (default=train)
--version = ['100k', '10k'] : The Berkeley Deepdrive Dataset comes in two sizes. (default=100k)
--elements_per_tfrecord = integer : You can specify, how many images are put into one tfrecord file. Multiple TFRecord files are generated.
--number_images_to_write = integer : Restricts the number of files to be written. [E.g. to create smaller files to test overfitting]
The resulting TFRecord files can be found in : ~/.deepdrive/tfrecord/[version]/[fold_type]/
Using read_data.py you can check your TFRecord file.
--batch_size = int: Specify the batch-size
--fold_type = see above
--version = see above
It will plot all images, and all boundingboxes.