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# Following properties are mandatory when engine files are not specified:
#   int8-calib-file(Only in INT8)
#   Caffemodel mandatory properties: model-file, proto-file, output-blob-names
#   UFF: uff-file, input-dims, uff-input-blob-name, output-blob-names
#   ONNX: onnx-file
#
# Mandatory properties for detectors:
#   num-detected-classes
#
# Optional properties for detectors:
#   enable-dbscan(Default=false), interval(Primary mode only, Default=0)
#   custom-lib-path,
#   parse-bbox-func-name
#
# Mandatory properties for classifiers:
#   classifier-threshold, is-classifier
#
# Optional properties for classifiers:
#   classifier-async-mode(Secondary mode only, Default=false)
#
# Optional properties in secondary mode:
#   operate-on-gie-id(Default=0), operate-on-class-ids(Defaults to all classes),
#   input-object-min-width, input-object-min-height, input-object-max-width,
#   input-object-max-height
#
# Following properties are always recommended:
#   batch-size(Default=1)
#
# Other optional properties:
#   net-scale-factor(Default=1), network-mode(Default=0 i.e FP32),
#   model-color-format(Default=0 i.e. RGB) model-engine-file, labelfile-path,
#   mean-file, gie-unique-id(Default=0), offsets, gie-mode (Default=1 i.e. primary),
#   custom-lib-path, network-mode(Default=0 i.e FP32)
#
# The values in the config file are overridden by values set through GObject
# properties.

# [property]
# gpu-id=0
# net-scale-factor=0.0039215697906911373
# model-engine-file=../../samples/models/Primary_Detector/resnet10.caffemodel_b1_fp16.engine
# model-file=../../samples/models/Primary_Detector/resnet10.caffemodel
# proto-file=../../samples/models/Primary_Detector/resnet10.prototxt
# labelfile-path=../../samples/models/Primary_Detector/labels.txt
# int8-calib-file=../../samples/models/Primary_Detector/cal_trt.bin
# batch-size=1
# network-mode=1
# num-detected-classes=4
# interval=0
# gie-unique-id=1
# output-blob-names=conv2d_bbox;conv2d_cov/Sigmoid

# [class-attrs-all]
# threshold=0.2
# eps=0.2
# group-threshold=1

# YOLOV3 CONFIG
[property]
gpu-id=0
net-scale-factor=1.0
offsets=103.939;116.779;123.68
model-color-format=1
labelfile-path=./nvdsinfer_customparser_yolov3_tlt/yolov3_labels.txt
tlt-encoded-model=./models/yolov3/yolo_resnet18.etlt
tlt-model-key=nvidia_tlt
# will build this engine from the etlt file (if not exist), adjust engine name when change batch-size, gpu-id & network-mode 
model-engine-file=./models/yolov3/yolo_resnet18.etlt_b2_gpu0_int8.engine
# needed to build int8 engine
int8-calib-file=./models/yolov3/cal.bin
uff-input-dims=3;544;960;0
uff-input-blob-name=Input
batch-size=2
## 0=FP32, 1=INT8, 2=FP16 mode
network-mode=1
num-detected-classes=4
interval=0
gie-unique-id=1
is-classifier=0
#network-type=0
#no cluster
cluster-mode=3
output-blob-names=BatchedNMS
# use custom parser for yolov3, instead of the default custom parser
parse-bbox-func-name=NvDsInferParseCustomYOLOV3TLT
custom-lib-path=./nvdsinfer_customparser_yolov3_tlt/libnvds_infercustomparser_yolov3_tlt.so

[class-attrs-all]
pre-cluster-threshold=0.5
roi-top-offset=0
roi-bottom-offset=0
detected-min-w=0
detected-min-h=0
detected-max-w=0
detected-max-h=0