Please provide complete information as applicable to your setup.
• Jetson nano)
• DeepStream Version v5
**• 4.4DP - Jetpack
**• 7.1,0,16
I am trying to run deepstream-app on jetson nano , but I am using 100% GPU with single source and adding another source gives me segmentation fault. Am I missing something ?
Following is the link which mentions extraordinary performance by jetson nano
https://docs.nvidia.com/metropolis/deepstream/dev-guide/index.html#page/DeepStream_Development_Guide/deepstream_performance.html#wwpID0E1HA
My config :
# Copyright (c) 2018-2020 NVIDIA Corporation. All rights reserved.
#
# NVIDIA Corporation and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA Corporation is strictly prohibited.
[application]
enable-perf-measurement=1
perf-measurement-interval-sec=5
#gie-kitti-output-dir=streamscl
#kitti-track-output-dir=../../../kitti_track/
[source0]
enable=1
type=4
latency=500
uri=rtsp://admin:@192.168.1.12:554/mode=real&idc=1&ids=1
num-sources=1
#drop-frame-interval=2
[source1]
enable=0
type=4
latency=500
uri=rtsp://admin:@192.168.1.12:554/mode=real&idc=1&ids=1
num-sources=1
gpu-id=0
[source2]
enable=0
#Type - 1=CameraV4L2 2=URI 3=MultiURI 4=RTSP
type=4
latency=500
uri=rtsp://admin:@192.168.1.11:554/mode=real&idc=1&ids=1
num-sources=1
#drop-frame-interval=2
camera-id=2
gpu-id=0
# (0): memtype_device - Memory type Device
# (1): memtype_pinned - Memory type Host Pinned
# (2): memtype_unified - Memory type Unified
cudadec-memtype=0
[source3]
enable=0
#Type - 1=CameraV4L2 2=URI 3=MultiURI 4=RTSP
type=4
latency=500
uri=rtsp://admin:@192.168.1.100:554/mode=real&idc=1&ids=1
num-sources=1
#drop-frame-interval=2
camera-id=100
gpu-id=0
# (0): memtype_device - Memory type Device
# (1): memtype_pinned - Memory type Host Pinned
# (2): memtype_unified - Memory type Unified
cudadec-memtype=0
[source4]
enable=0
#Type - 1=CameraV4L2 2=URI 3=MultiURI 4=RTSP
type=4
latency=500
uri=rtsp://admin:@192.168.1.101:554/mode=real&idc=1&ids=1
num-sources=1
#drop-frame-interval=2
gpu-id=0
camera-id=101
# (0): memtype_device - Memory type Device
# (1): memtype_pinned - Memory type Host Pinned
# (2): memtype_unified - Memory type Unified
cudadec-memtype=0
[sink0]
enable=1
#Type - 1=FakeSink 2=EglSink 3=File
type=1
qos=0
sync=0
source-id=0
gpu-id=0
nvbuf-memory-type=0
[sink1]
enable=0
#Type - 1=FakeSink 2=EglSink 3=File
type=1
sync=0
qos=0
source-id=1
gpu-id=0
nvbuf-memory-type=0
[streammux]
gpu-id=0
##Boolean property to inform muxer that sources are live
live-source=1
batch-size=2
##time out in usec, to wait after the first buffer is available
##to push the batch even if the complete batch is not formed
batched-push-timeout=40000
## Set muxer output width and height
width=1920
height=1080
##Enable to maintain aspect ratio wrt source, and allow black borders, works
##along with width, height properties
enable-padding=0
nvbuf-memory-type=0
## If set to TRUE, system timestamp will be attached as ntp timestamp
## If set to FALSE, ntp timestamp from rtspsrc, if available, will be attached
# attach-sys-ts-as-ntp=1
# config-file property is mandatory for any gie section.
# Other properties are optional and if set will override the properties set in
# the infer config file.
[primary-gie]
enable=1
gpu-id=0
model-engine-file=../../models/tlt_pretrained_models/peoplenet/resnet34_peoplenet_pruned.etlt_b1_gpu0_fp16.engine
batch-size=2
#Required by the app for OSD, not a plugin property
interval=0
gie-unique-id=1
nvbuf-memory-type=0
config-file=../tlt_pretrained_models/config_infer_primary_peoplenet.txt
[tracker]
enable=0
# For the case of NvDCF tracker, tracker-width and tracker-height must be a multiple of 32, respectively
tracker-width=640
tracker-height=384
#ll-lib-file=/opt/nvidia/deepstream/deepstream-5.0/lib/libnvds_mot_iou.so
ll-lib-file=/opt/nvidia/deepstream/deepstream-5.0/lib/libnvds_nvdcf.so
#ll-lib-file=/opt/nvidia/deepstream/deepstream-5.0/lib/libnvds_mot_klt.so
#ll-config-file required for DCF/IOU only
#ll-config-file=tracker_config.yml
#ll-config-file=iou_config.txt
gpu-id=0
#enable-batch-process applicable to DCF only
enable-batch-process=1
[ds-example]
enable=1
processing-width=1920
processing-height=1080
full-frame=0
unique-id=15
gpu-id=0
[tests]
file-loop=0