Message type 'ClassWiseBboxHandlerConfig' has no field named 'confidence_threshold'

Accelerated Computing Intelligent Video Analytics TAO Toolkit
1

When I am following the tutorial to test some images with pruned and retrained ‘detectnet_v2’ model, the error is occurred.
My TLT version is 3.0.0 and the configuration is like:
bbox_handler_config{
kitti_dump: true
disable_overlay: false
overlay_linewidth: 2
classwise_bbox_handler_config{
key:“car”
value: {
confidence_model: “aggregate_cov”
output_map: “car”
confidence_threshold: 0.9
bbox_color{
R: 0
G: 255
B: 0
}
clustering_config{
coverage_threshold: 0.00
dbscan_eps: 0.3
dbscan_min_samples: 0.05
minimum_bounding_box_height: 4
}
}
}
classwise_bbox_handler_config{
key:“default”
value: {
confidence_model: “aggregate_cov”
confidence_threshold: 0.9
bbox_color{
R: 255
G: 0
B: 0
}
clustering_config{
coverage_threshold: 0.00
dbscan_eps: 0.3
dbscan_min_samples: 0.05
minimum_bounding_box_height: 4
}
}
}
}

How do I solve this?

tlt detectnet_v2 inference -e detectnet_v2_inference_kitti.txt -i input/ -o output/ -k KEY

3

The inference spec file is old. It is not for TLT 3.0. We will fix the user guide. DetectNet_v2 — Transfer Learning Toolkit 3.0 documentation

For workaround, please download the latest samples according to https://docs.nvidia.com/metropolis/TLT/tlt-user-guide/text/requirements_and_installation.html#running-the-transfer-learning-toolkit

wget --content-disposition https://api.ngc.nvidia.com/v2/resources/nvidia/tlt_cv_samples/versions/v1.0.2/zip -O tlt_cv_samples_v1.0.2.zip
unzip -u tlt_cv_samples_v1.0.2.zip -d ./tlt_cv_samples_v1.0.2 && rm -rf tlt_cv_samples_v1.0.2.zip && cd ./tlt_cv_samples_v1.0.2

There are specs and .ipynb in it.
See tlt_cv_samples_v1.0.2/detectnet_v2/specs/detectnet_v2_inference_kitti_tlt.txt

inferencer_config{
# defining target class names for the experiment.
# Note: This must be mentioned in order of the networks classes.
target_classes: “car”
target_classes: “cyclist”
target_classes: “pedestrian”
# Inference dimensions.
image_width: 1248
image_height: 384
# Must match what the model was trained for.
image_channels: 3
batch_size: 16
gpu_index: 0
# model handler config
tlt_config{
model: “/workspace/tlt-experiments/detectnet_v2/experiment_dir_retrain/weights/resnet18_detector_pruned.tlt”
}
}
bbox_handler_config{
kitti_dump: true
disable_overlay: false
overlay_linewidth: 2
classwise_bbox_handler_config{
key:“car”
value: {
confidence_model: “aggregate_cov”
output_map: “car”
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:“cyclist”
value: {
confidence_model: “aggregate_cov”
output_map: “cyclist”
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:“pedestrian”
value: {
confidence_model: “aggregate_cov”
output_map: “pedestrian”
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
}
}
}
}