Please provide the following information when requesting support.
• Hardware V100
• Network Type Detectnet_v2
• TLT Version (Please run “tlt info --verbose” and share “docker_tag” here)
dockers:
nvidia/tlt-streamanalytics:
docker_registry: nvcr.io
docker_tag: v3.0-py3
tasks:
1. augment
2. bpnet
3. classification
4. detectnet_v2
5. dssd
6. emotionnet
7. faster_rcnn
8. fpenet
9. gazenet
10. gesturenet
11. heartratenet
12. lprnet
13. mask_rcnn
14. multitask_classification
15. retinanet
16. ssd
17. unet
18. yolo_v3
19. yolo_v4
20. tlt-converter
nvidia/tlt-pytorch:
docker_registry: nvcr.io
docker_tag: v3.0-py3
tasks:
1. speech_to_text
2. speech_to_text_citrinet
3. text_classification
4. question_answering
5. token_classification
6. intent_slot_classification
7. punctuation_and_capitalization
format_version: 1.0
tlt_version: 3.0
published_date: 04/16/2021
• Training spec file(If have, please share here)
random_seed: 42
lpr_config {
hidden_units: 512
max_label_length: 8
arch: "baseline"
nlayers: 18 #setting nlayers to be 10 to use baseline10 model
}
training_config {
batch_size_per_gpu: 32
num_epochs: 24
learning_rate {
soft_start_annealing_schedule {
min_learning_rate: 1e-6
max_learning_rate: 1e-5
soft_start: 0.001
annealing: 0.5
}
}
regularizer {
type: L2
weight: 5e-4
}
}
eval_config {
validation_period_during_training: 5
batch_size: 1
}
augmentation_config {
output_width: 96
output_height: 48
output_channel: 3
keep_original_prob: 0.3
# transform_prob: 0.5
# rotate_degree: 5
}
dataset_config {
data_sources: {
label_directory_path: "/workspace/tlt-experiments/data/openalpr/train/label"
image_directory_path: "/workspace/tlt-experiments/data/openalpr/train/image"
}
characters_list_file: "/workspace/tlt-experiments/lprnet/specs/us_lp_characters.txt"
validation_data_sources: {
label_directory_path: "/workspace/tlt-experiments/data/openalpr/val/label"
image_directory_path: "/workspace/tlt-experiments/data/openalpr/val/image"
}
}
• How to reproduce the issue ?
I just followed Creating a Real-Time License Plate Detection and Recognition App | NVIDIA Technical Blog and trained LPD and LPR networks. Now am trying to make etlt file by the below command which gives me the below error
$ tlt lprnet export -m /workspace/tlt-experiments/lprnet/weights/lprnet_epoch-24.tlt -k nvidia_tlt -e /workspace/tlt-experiments/lprnet/tutorial_spec.txt
2021-07-02 10:27:19,956 [INFO] root: Registry: ['nvcr.io']
Matplotlib created a temporary config/cache directory at /tmp/matplotlib-78fgwu6_ 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.
Using TensorFlow backend.
WARNING:tensorflow:Deprecation warnings have been disabled. Set TF_ENABLE_DEPRECATION_WARNINGS=1 to re-enable them.
Using TensorFlow backend.
2021-07-02 10:27:31,438 [INFO] iva.common.export.keras_exporter: Using input nodes: ['image_input']
2021-07-02 10:27:31,438 [INFO] iva.common.export.keras_exporter: Using output nodes: ['tf_op_layer_ArgMax', 'tf_op_layer_Max']
2021-07-02 10:27:31,438 [INFO] iva.lprnet.utils.spec_loader: Merging specification from /workspace/tlt-experiments/lprnet/tutorial_spec.txt
The ONNX operator number change on the optimization: 132 -> 61
2021-07-02 10:27:47,248 [INFO] keras2onnx: The ONNX operator number change on the optimization: 132 -> 61
Traceback (most recent call last):
File "/opt/tlt/.cache/dazel/_dazel_tlt/2b81a5aac84a1d3b7a324f2a7a6f400b/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/lprnet/scripts/export.py", line 215, in <module>
File "/opt/tlt/.cache/dazel/_dazel_tlt/2b81a5aac84a1d3b7a324f2a7a6f400b/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/lprnet/scripts/export.py", line 142, in main
File "/opt/tlt/.cache/dazel/_dazel_tlt/2b81a5aac84a1d3b7a324f2a7a6f400b/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/lprnet/scripts/export.py", line 211, in run_export
File "/opt/tlt/.cache/dazel/_dazel_tlt/2b81a5aac84a1d3b7a324f2a7a6f400b/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/common/export/keras_exporter.py", line 371, in export
TypeError: set_data_preprocessing_parameters() got an unexpected keyword argument 'image_mean'
2021-07-02 10:27:49,446 [INFO] tlt.components.docker_handler.docker_handler: Stopping container.
any suggestions will be appreciated