Please provide the following information when requesting support.
• Hardware ntel® Core™ i5-10500H CPU @ 2.50GHz × 12 NVIDIA GeForce RTX 3060 Laptop GPU/PCIe/SSE2 (USING TAO docker)
• Network Type : Detectnet_v2
• TAO Version 3.22.02
• Training spec file Kitti file :
kitti_config {
root_directory_path: “/tao/data/training”
image_dir_name: “image”
label_dir_name: “label”
image_extension: “.png”
partition_mode: “random”
num_partitions: 2
val_split: 14
num_shards: 10
}
image_directory_path: “/tao”
• How to reproduce the issue ?
I have used the following command to convert the kitti dataset to tfrecords:
tao detectnet_v2 dataset_convert
-d $SPECS_DIR/train_kitti_config.txt
-o $LOCAL_DATA_DIR/tfrecords
Got the following output:
tao detectnet_v2 dataset_convert
-d $SPECS_DIR/train_kitti_config.txt
-o $LOCAL_DATA_DIR/tfrecords
And this is the result I am getting :

I don’t understand where I went wrong.
000000.txt (670 Bytes)
person 0.00 0 0.00 266 525 587 1048 0.00 0.00 0.00 0.00 0.00 0.00 0.00
person 0.00 0 0.00 1232 462 1514 1023 0.00 0.00 0.00 0.00 0.00 0.00 0.00
That is how my label files looks like.
Please point me to right direction.
You have only 10 images. It is not enough.
Please set
num_shards: 10
to
num_shards: 1
and retry.
Hi Morganh,
I tried that it didn’t work. I have also used the dataset provided in kitti format which has 7481 images with no result.
Here is the command
!tao detectnet_v2 dataset_convert
-d $SPECS_DIR/train_kitti_config.txt
-o $LOCAL_PROJECT_DIR/tfrecords
and config file:
kitti_config {
root_directory_path: “/tao/data/training”
image_dir_name: “image_2”
label_dir_name: “label_2”
image_extension: “.png”
partition_mode: “random”
num_partitions: 2
val_split: 14
num_shards: 10
}
image_directory_path: “/tao/data/training”
and this is the output but no files created on the directory.
Could you please make sure if the result folder has written access?
Thank you for the reply but the directory has read write permission

To debug, please run below in terminal instead of notebook. I am afraid you need to check if ~/.tao_mounts.json is correct.
$ tao detectnet_v2
then
#
detectnet_v2 dataset_convert xxx
bijay1
7

Result after running detectnet dataset_convert XXX in docker and ~/.tao_mounts.json looks fine

system
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