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[property]
gpu-id=0
net-scale-factor=0.01735207357279195
offsets=123.675;116.28;103.53
labelfile-path=     ../../models/citysemsegformer_vdeployable_v1.0/labels.txt
model-engine-file=  ../../models/citysemsegformer_vdeployable_v1.0/citysemsegformer.etlt_b1_gpu0_fp16.engine
tlt-encoded-model=  ../../models/citysemsegformer_vdeployable_v1.0/citysemsegformer.etlt
tlt-model-key=tlt_encode
infer-dims=3;1024;1820
model-color-format=0
batch-size=1
## 0=FP32, 1=INT8, 2=FP16 mode
network-mode=2
## workspace-size default to 1024 x 1024 MB
workspace-size=1048576
interval=0
gie-unique-id=1
cluster-mode=2
## 0=Detector, 1=Classifier, 2=Semantic Segmentation, 3=Instance Segmentation, 100=Other
network-type=100 # Skip nvinfer post-processing, use pgie_pad_buffer_probe_network_type100() instead.
## num-detected-classes= is required to set NvDsInferSegmentationMeta::classes.
num-detected-classes=19
## Allow post-processing to access output tensors.
output-tensor-meta=1
##specify the output tensor order, 0(default value) for CHW and 1 for HWC
segmentation-output-order=1