Hi,
Trying to train TLT ResNet18SSD model on a custom data-set. Converted the Pascal VOC Annotations to Kitti Format using xml2kitti. Here is the reference used
TF-records kitti txt
kitti_config {
root_directory_path: “/workspace/tlt-experiments/data/training”
image_dir_name: “image_2”
label_dir_name: “label_2”
image_extension: “.jpg”
partition_mode: “random”
num_partitions: 2
val_split: 14
num_shards: 10
}
image_directory_path: “/workspace/tlt-experiments/data/training”
The following error occurred while running in the jupyter notebook.
!tlt-dataset-convert -d $SPECS_DIR/ssd_tfrecords_kitti_trainval.txt
-o $USER_EXPERIMENT_DIR/tfrecords/kitti_trainval
Traceback (most recent call last):
File “/usr/local/bin/tlt-dataset-convert”, line 10, in
sys.exit(main())
File “./detectnet_v2/scripts/dataset_convert.py”, line 64, in main
File “./detectnet_v2/dataio/dataset_converter_lib.py”, line 74, in convert
File “./detectnet_v2/dataio/dataset_converter_lib.py”, line 108, in _write_partitions
File “./detectnet_v2/dataio/dataset_converter_lib.py”, line 149, in _write_shard
File “./detectnet_v2/dataio/kitti_converter_lib.py”, line 169, in _create_example_proto
File “./detectnet_v2/dataio/kitti_converter_lib.py”, line 272, in _add_targets
AssertionError: Ground truth kitti labels should have only 15 fields.
Please help me with this issue.
Thanks in Advance