Are TFrecords supported for the validation set using SSD and DSSD?
Using the nvcr.io/nvidia/tao/tao-toolkit:4.0.0-tf1.15.5
Docker image directly. With the below dataset configurations the output of the following command ssd train -e /Config/experiment_config.txt -r /Training/ -k encryption_key -m /Pretrained/mobilenet_v2.hdf5
is as shown below the dataset config. The rest runs as expected just the validation step is missing.
dataset_config:
data_sources:
tfrecords_path: "/Data/train_val-fold-001*"
include_difficult_in_training: true
validation_data_sources:
tfrecords_path: "/Data/train_val-fold-000*"
2023-02-15 08:22:48,649 [INFO] __main__: Number of images in the training dataset: 41
2023-02-15 08:22:48,649 [INFO] __main__: Number of images in the validation dataset: 0
Flipping the folds around gives the same problem, indicating that the records are valid:
dataset_config:
data_sources:
tfrecords_path: "/Data/train_val-fold-000*"
include_difficult_in_training: true
validation_data_sources:
tfrecords_path: "/Data/train_val-fold-001*"
2023-02-15 08:23:15,246 [INFO] __main__: Number of images in the training dataset: 10
2023-02-15 08:23:15,246 [INFO] __main__: Number of images in the validation dataset: 0