Hello. When I do the inference of PeopleNet Transformer, the process was interrupted without any error messages.
What made this interruption happend ? How should I do to deal with the problem ?
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My data is jpg and jpeg files
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The model I used was resnet50_peoplenet_transformer.tlt from NGC
Here is my command
sudo docker run -it --rm -v /home/ubuntu/tao_test_2023/peoplenet_transformer:/workspace/tao-experiments/peoplenet_transformer/
nvcr.io/nvidia/tao/tao-toolkit:4.0.1-tf1.15.5
detectnet_v2 inference
-e /workspace/tao-experiments/peoplenet_transformer/specs.txt
-o /workspace/tao-experiments/peoplenet_transformer
-i /workspace/tao-experiments/peoplenet_transformer/data
-k tlt_encode
Here is my spec file
inferencer_config{ # defining target class names for the experiment.
# Note: This must be mentioned in order of the networks classes.
target_classes: "person"
target_classes: "bag"
target_classes: "face"
# Inference dimensions.
image_width: 960
image_height: 544
# Must match what the model was trained for.
image_channels: 3
batch_size: 16
gpu_index: 0
# model handler config
tlt_config{
model: "/workspace/tao-experiments/peoplenet_transformer/resnet50_peoplenet_transformer.tlt"
}
}
bbox_handler_config{
kitti_dump: true
disable_overlay: false
overlay_linewidth: 2
classwise_bbox_handler_config{
key:"person"
value: {
confidence_model: "aggregate_cov"
output_map: "person"
bbox_color{
R: 0
G: 255
B: 0
}
clustering_config{
clustering_algorithm: DBSCAN
coverage_threshold: 0.005
dbscan_eps: 0.3
dbscan_min_samples: 0.05
dbscan_confidence_threshold: 0.9
minimum_bounding_box_height: 4
}
}
}
classwise_bbox_handler_config{
key:"bag"
value: {
confidence_model: "aggregate_cov"
output_map: "bag"
bbox_color{
R: 0
G: 255
B: 255
}
clustering_config{
clustering_algorithm: DBSCAN
coverage_threshold: 0.005
dbscan_eps: 0.3
dbscan_min_samples: 0.05
dbscan_confidence_threshold: 0.9
minimum_bounding_box_height: 4
}
}
}
classwise_bbox_handler_config{
key:"face"
value: {
confidence_model: "aggregate_cov"
output_map: "face"
bbox_color{
R: 255
G: 0
B: 0
}
clustering_config{
clustering_algorithm: DBSCAN
coverage_threshold: 0.005
dbscan_eps: 0.3
dbscan_min_samples: 0.05
dbscan_confidence_threshold: 0.9
minimum_bounding_box_height: 4
}
}
}
classwise_bbox_handler_config{
key:"default"
value: {
confidence_model: "aggregate_cov"
bbox_color{
R: 255
G: 0
B: 0
}
clustering_config{
clustering_algorithm: DBSCAN
dbscan_confidence_threshold: 0.9
coverage_threshold: 0.005
dbscan_eps: 0.3
dbscan_min_samples: 0.05
minimum_bounding_box_height: 4
}
}
}
}