# Following properties are mandatory when engine files are not specified:
#   int8-calib-file(Only in INT8), model-file-format
#   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:
#   cluster-mode(Default=Group Rectangles), 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, process-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
#0=RGB, 1=BGR
model-color-format=0
# custom-network-config=yolov3-tiny.cfg
# model-file=yolov3-tiny.weights
model-engine-file=yolov5s-zj.engine
labelfile-path=labels.txt
# process-mode (Default=1 primary)
process-mode=1
## 0=FP32, 1=INT8, 2=FP16 mode
network-mode=2
num-detected-classes=11
gie-unique-id=1
network-type=0
batch-size=8
#is-classifier=0
output-blob-names=prob
## 0=Group Rectangles, 1=DBSCAN, 2=NMS, 3= DBSCAN+NMS Hybrid, 4 = None(No clustering)
#cluster-mode=2
maintain-aspect-ratio=1
parse-bbox-func-name=NvDsInferParseCustomYoloV5
custom-lib-path=nvdsinfer/libnvdsinfer_Yolo.so
engine-create-func-name=NvDsInferYoloCudaEngineGet
#scaling-filter=0
#scaling-compute-hw=0

[class-attrs-all]
nms-iou-threshold=0.5
pre-cluster-threshold=0.4