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[property]
gpu-id=1
net-scale-factor=0.0039215697906911373
tlt-model-key=tlt_encode
# 
enable-dla=1
use-dla-core=0
# use-dla-core=1
#
tlt-encoded-model=../../models/tao_pretrained_models/peopleNet/V2.3.2/resnet34_peoplenet_pruned_int8_v2_3_2_quantized.etlt
labelfile-path=../../models/tao_pretrained_models/peopleNet/V2.3.2/labels.txt
model-engine-file=../../models/tao_pretrained_models/peopleNet/V2.3.2/resnet34_peoplenet_pruned_int8_v2_3_2_quantized.etlt_b2_dla0_int8.engine
int8-calib-file=../../models/tao_pretrained_models/peopleNet/V2.3.2/resnet34_peoplenet_pruned_int8_v2_3_2_quantized.txt
#
# input-dims=5;544;960;0
# input-dims=3;544;960;0
# infer-dims=3;544;960
# uff-input-blob-name=input_1
batch-size=2
process-mode=1
model-color-format=0
## 0=FP32, 1=INT8, 2=FP16 mode
network-mode=1
#
num-detected-classes=3
cluster-mode=2
interval=0
gie-unique-id=1
# output-blob-names=output_bbox/BiasAdd;output_cov/Sigmoid



#Use the config params below for NMS clustering mode
[class-attrs-all]
topk=20
nms-iou-threshold=0.5
pre-cluster-threshold=0.2

# ## Per class configurations
# [class-attrs-0]
# topk=20
# nms-iou-threshold=0.5
# pre-cluster-threshold=0.4

#[class-attrs-1]
#pre-cluster-threshold=0.05
#eps=0.7
#dbscan-min-score=0.5