################################################################################ # Copyright (c) 2018-2021, NVIDIA CORPORATION. All rights reserved. # # Permission is hereby granted, free of charge, to any person obtaining a # copy of this software and associated documentation files (the "Software"), # to deal in the Software without restriction, including without limitation # the rights to use, copy, modify, merge, publish, distribute, sublicense, # and/or sell copies of the Software, and to permit persons to whom the # Software is furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL # THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING # FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER # DEALINGS IN THE SOFTWARE. ################################################################################ # 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: # 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 model-file=/opt/nvidia/deepstream/deepstream-6.0/samples/models/Primary_Detector/resnet10.caffemodel proto-file=/opt/nvidia/deepstream/deepstream-6.0/samples/models/Primary_Detector/resnet10.prototxt model-engine-file=/opt/nvidia/deepstream/deepstream-6.0/samples/models/Primary_Detector/resnet10.caffemodel_b30_gpu0_int8.engine labelfile-path=/opt/nvidia/deepstream/deepstream-6.0/samples/models/Primary_Detector/labels.txt int8-calib-file=/opt/nvidia/deepstream/deepstream-6.0/samples/models/Primary_Detector/cal_trt.bin batch-size=30 process-mode=1 model-color-format=0 ## 0=FP32, 1=INT8, 2=FP16 mode network-mode=1 num-detected-classes=4 interval=0 gie-unique-id=1 output-blob-names=conv2d_bbox;conv2d_cov/Sigmoid force-implicit-batch-dim=1 #parse-bbox-func-name=NvDsInferParseCustomResnet #custom-lib-path=/path/to/libnvdsparsebbox.so ## 1=DBSCAN, 2=NMS, 3= DBSCAN+NMS Hybrid, 4 = None(No clustering) cluster-mode=2 #scaling-filter=0 #scaling-compute-hw=0 #Use the config params below for dbscan clustering mode #[class-attrs-all] #detected-min-w=4 #detected-min-h=4 #minBoxes=3 #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 #[class-attrs-2] #pre-cluster-threshold=0.1 #eps=0.6 #dbscan-min-score=0.95 #[class-attrs-3] #pre-cluster-threshold=0.05 #eps=0.7 #dbscan-min-score=0.5