• Hardware: A100
• Network Type: LPRNet
• TLT Version: 5.2.0
• How to reproduce the issue:
I tried testing inference with LPRNet before training like so:
lprnet inference -m us_lprnet_baseline18_trainable.tlt -i inference/1152.jpg -e experiment.txt
However I get this result:
2024-01-09 11:28:38.963247: I tensorflow/stream_executor/platform/default/dso_loader.cc:50] Successfully opened dynamic library libcudart.so.12
2024-01-09 11:28:39,010 [TAO Toolkit] [WARNING] tensorflow 40: Deprecation warnings have been disabled. Set TF_ENABLE_DEPRECATION_WARNINGS=1 to re-enable them.
Using TensorFlow backend.
2024-01-09 11:28:40,577 [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.
2024-01-09 11:28:40,606 [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.
2024-01-09 11:28:40,610 [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.
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.
WARNING: 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.
WARNING: 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.
WARNING: TensorFlow will not use Pandas by default. This improves performance in some cases. To enable Pandas export the environment variable TF_ALLOW_IOLIBS=1.
INFO: Log file already exists at /home/nikola.stojanovic.mcs/lprnet/status.json
INFO: Starting LPRNet Inference.
INFO: Merging specification from experiment.txt
INFO: Inference was interrupted
Execution status: PASS
My experiment spec file:
random_seed: 42
lpr_config {
hidden_units: 512
max_label_length: 8
arch: "baseline"
nlayers: 10
}
training_config {
batch_size_per_gpu: 32
num_epochs: 100
learning_rate {
soft_start_annealing_schedule {
min_learning_rate: 1e-6
max_learning_rate: 1e-4
soft_start: 0.001
annealing: 0.7
}
}
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
max_rotate_degree: 5
rotate_prob: 0.5
gaussian_kernel_size: 5
gaussian_kernel_size: 7
gaussian_kernel_size: 15
blur_prob: 0.5
reverse_color_prob: 0.5
keep_original_prob: 0.3
}
dataset_config {
data_sources: {
label_directory_path: "dataset/train/labels"
image_directory_path: "dataset/train/images"
}
characters_list_file: "chars.txt"
validation_data_sources: {
label_directory_path: "dataset/val/labels"
image_directory_path: "dataset/val/images"
}
}
What am I doing wrong?
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