• Network Type (Detectnet_v2)
• TLT Version (Please run “tlt info --verbose” and share “docker_tag” here)
nvidia/tao/tao-toolkit:
5.0.0-tf2.11.0:
• Training spec file(If have, please share here)
kitti_config {
root_directory_path: “/home/sysadmin/Desktop/dataset/tao-getting-started_5.3.0/notebooks/tao_launcher_starter_kit/detectnet_v2/data/training”
image_dir_name: “image_2”
label_dir_name: “label_2”
image_extension: “.jpg”
partition_mode: “random”
num_partitions: 2
val_split: 20
num_shards: 10
}
image_directory_path: “/home/sysadmin/Desktop/dataset/tao-getting-started_5.3.0/notebooks/tao_launcher_starter_kit/detectnet_v2/data/training”
while iam running the cell
print(“Converting Tfrecords for kitti trainval dataset”)
!mkdir -p $LOCAL_DATA_DIR/tfrecords && rm -rf $LOCAL_DATA_DIR/tfrecords/*
!tao model detectnet_v2 dataset_convert
-d $SPECS_DIR/detectnet_v2_tfrecords_kitti_trainval.txt
-o $DATA_DOWNLOAD_DIR/tfrecords/kitti_trainval/kitti_trainval
-r $USER_EXPERIMENT_DIR/
iam getting an error
Converting Tfrecords for kitti trainval dataset
2024-05-19 11:44:59,636 [TAO Toolkit] [INFO] root 160: Registry: [‘nvcr.io’]
2024-05-19 11:44:59,694 [TAO Toolkit] [INFO] nvidia_tao_cli.components.instance_handler.local_instance 360: Running command in container: nvcr.io/nvidia/tao/tao-toolkit:5.0.0-tf1.15.5
2024-05-19 11:44:59,713 [TAO Toolkit] [INFO] nvidia_tao_cli.components.docker_handler.docker_handler 301: Printing tty value True
2024-05-19 06:15:00.408768: I tensorflow/stream_executor/platform/default/dso_loader.cc:50] Successfully opened dynamic library libcudart.so.12
2024-05-19 06:15:00,448 [TAO Toolkit] [WARNING] tensorflow 40: Deprecation warnings have been disabled. Set TF_ENABLE_DEPRECATION_WARNINGS=1 to re-enable them.
Using TensorFlow backend.
2024-05-19 06:15:01,673 [TAO Toolkit] [WARNING] tensorflow 43: TensorFlow will not use sklearn by default. This improves performance in some cases. To enable sklearn export the environment variable TF_ALLOW_IOLIBS=1.
2024-05-19 06:15:01,703 [TAO Toolkit] [WARNING] tensorflow 42: TensorFlow will not use Dask by default. This improves performance in some cases. To enable Dask export the environment variable TF_ALLOW_IOLIBS=1.
2024-05-19 06:15:01,707 [TAO Toolkit] [WARNING] tensorflow 43: TensorFlow will not use Pandas by default. This improves performance in some cases. To enable Pandas export the environment variable TF_ALLOW_IOLIBS=1.
2024-05-19 06:15:02,918 [TAO Toolkit] [WARNING] matplotlib 500: Matplotlib created a temporary config/cache directory at /tmp/matplotlib-fz899m0o because the default path (/.config/matplotlib) is not a writable directory; it is highly recommended to set the MPLCONFIGDIR environment variable to a writable directory, in particular to speed up the import of Matplotlib and to better support multiprocessing.
2024-05-19 06:15:03,131 [TAO Toolkit] [INFO] matplotlib.font_manager 1633: generated new fontManager
WARNING:tensorflow:Deprecation warnings have been disabled. Set TF_ENABLE_DEPRECATION_WARNINGS=1 to re-enable them.
Using TensorFlow backend.
WARNING:tensorflow:TensorFlow will not use sklearn by default. This improves performance in some cases. To enable sklearn export the environment variable TF_ALLOW_IOLIBS=1.
2024-05-19 06:15:04,507 [TAO Toolkit] [WARNING] tensorflow 43: TensorFlow will not use sklearn by default. This improves performance in some cases. To enable sklearn export the environment variable TF_ALLOW_IOLIBS=1.
WARNING:tensorflow:TensorFlow will not use Dask by default. This improves performance in some cases. To enable Dask export the environment variable TF_ALLOW_IOLIBS=1.
2024-05-19 06:15:04,536 [TAO Toolkit] [WARNING] tensorflow 42: TensorFlow will not use Dask by default. This improves performance in some cases. To enable Dask export the environment variable TF_ALLOW_IOLIBS=1.
WARNING:tensorflow:TensorFlow will not use Pandas by default. This improves performance in some cases. To enable Pandas export the environment variable TF_ALLOW_IOLIBS=1.
2024-05-19 06:15:04,541 [TAO Toolkit] [WARNING] tensorflow 43: TensorFlow will not use Pandas by default. This improves performance in some cases. To enable Pandas export the environment variable TF_ALLOW_IOLIBS=1.
Traceback (most recent call last):
File “/usr/local/lib/python3.8/dist-packages/nvidia_tao_tf1/cv/detectnet_v2/scripts/dataset_convert.py”, line 168, in
raise e
File “/usr/local/lib/python3.8/dist-packages/nvidia_tao_tf1/cv/detectnet_v2/scripts/dataset_convert.py”, line 137, in
main()
File “/usr/local/lib/python3.8/dist-packages/nvidia_tao_tf1/cv/detectnet_v2/scripts/dataset_convert.py”, line 113, in main
status_logging.StatusLogger(
File “/usr/local/lib/python3.8/dist-packages/nvidia_tao_tf1/cv/common/logging/logging.py”, line 203, in init
self.l_file = open(self.log_path, “a” if append else “w”)
PermissionError: [Errno 13] Permission denied: ‘/home/sysadmin/Desktop/dataset/tao-getting-started_5.3.0/notebooks/tao_launcher_starter_kit/detectnet_v2/status.json’
Execution status: FAIL
2024-05-19 11:45:08,822 [TAO Toolkit] [INFO] nvidia_tao_cli.components.docker_handler.docker_handler 363: Stopping container.
tao is running in the virtualwrapper launcher
in host machine i given all permission for folder
(/home/sysadmin/Desktop/dataset/tao-getting-started_5.3.0/notebooks/tao_launcher_starter_kit/detectnet_v2/status.json’ ) detectnet_v2 and when iam checking iam not able to see the status.json file
how should i fix it