When I increase number of source to 2 multi URI sources , I get :
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Hi
Please set ‘type=4’ and try again. You may refer to
https://devtalk.nvidia.com/default/topic/1058086/deepstream-sdk/how-to-run-rtp-camera-in-deepstream-on-nano/post/5366807/#5366807
And for two sources, you need to set ‘batch-size=2’.
Done that. But I get segmentation fault again. However if I disable gst-dsexample it works fine, and if I enable gst-dsexample it works fine with only one source
Tracker , Primary and Secondary gie works absolutely fine. Problem comes when I enable ds-example on multiple sources.
Hi,
Please share full config file for reference.
Also does the issue happen in two RTSP sources? It looks not correct to have same ‘uri=rtsp://admin:@192.168.1.10:554/mode=real&idc=1&ids=1’ in both source0 and source1. You should run two individual IP cameras.
Hey thank you for your response.
Issue happens when with two RTSP sources I enable ds-example , with one RTSP sources and ds-example
disabled it works fine. With one RTSP source and ds-example enabled it works fine.
Here is full config for reference.
Hi,
We can run the following config files on DS4.0.1/TX2. FYR.
# Copyright (c) 2019 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
[tiled-display]
enable=1
rows=2
columns=1
width=640
height=720
gpu-id=0
#(0): nvbuf-mem-default - Default memory allocated, specific to particular platform
#(1): nvbuf-mem-cuda-pinned - Allocate Pinned/Host cuda memory, applicable for Tesla
#(2): nvbuf-mem-cuda-device - Allocate Device cuda memory, applicable for Tesla
#(3): nvbuf-mem-cuda-unified - Allocate Unified cuda memory, applicable for Tesla
#(4): nvbuf-mem-surface-array - Allocate Surface Array memory, applicable for Jetson
nvbuf-memory-type=0
[source0]
enable=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI 4=RTSP
type=4
#uri=file://../../streams/sample_1080p_h264.mp4
uri=rtsp://wowzaec2demo.streamlock.net/vod/mp4:BigBuckBunny_115k.mov
num-sources=1
#drop-frame-interval=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
[source1]
enable=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI 4=RTSP
type=4
#uri=file://../../streams/sample_1080p_h264.mp4
uri=rtsp://wowzaec2demo.streamlock.net/vod/mp4:BigBuckBunny_115k.mov
num-sources=1
#drop-frame-interval=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
[sink0]
enable=1
#Type - 1=FakeSink 2=EglSink 3=File
type=5
sync=0
source-id=0
gpu-id=0
qos=0
nvbuf-memory-type=0
overlay-id=1
[sink1]
enable=0
type=3
#1=mp4 2=mkv
container=1
#1=h264 2=h265
codec=1
sync=0
#iframeinterval=10
bitrate=2000000
output-file=out.mp4
source-id=0
[sink2]
enable=0
#Type - 1=FakeSink 2=EglSink 3=File 4=RTSPStreaming
type=4
#1=h264 2=h265
codec=1
sync=0
bitrate=4000000
# set below properties in case of RTSPStreaming
rtsp-port=8554
udp-port=5400
[osd]
enable=1
gpu-id=0
border-width=1
text-size=15
text-color=1;1;1;1;
text-bg-color=0.3;0.3;0.3;1
font=Serif
show-clock=0
clock-x-offset=800
clock-y-offset=820
clock-text-size=12
clock-color=1;0;0;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
# 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/Primary_Detector_Nano/resnet10.caffemodel_b2_fp16.engine
batch-size=2
#Required by the app for OSD, not a plugin property
bbox-border-color0=1;0;0;1
bbox-border-color1=0;1;1;1
bbox-border-color2=0;0;1;1
bbox-border-color3=0;1;0;1
interval=4
gie-unique-id=1
nvbuf-memory-type=0
config-file=config_infer_primary_nano.txt
[tracker]
enable=1
tracker-width=480
tracker-height=272
#ll-lib-file=/opt/nvidia/deepstream/deepstream-4.0/lib/libnvds_mot_iou.so
ll-lib-file=/opt/nvidia/deepstream/deepstream-4.0/lib/libnvds_mot_klt.so
#ll-config-file required for IOU only
#ll-config-file=iou_config.txt
gpu-id=0
[tests]
file-loop=0
[ds-example]
enable=1
processing-width=640
processing-height=480
full-frame=0
unique-id=15
gpu-id=0
I am also cropping and saving selected objects in my ds-example. Hope thats not causing Segmentation Fault for multiple streams.
When I changed URI to above mentioned URI , I get :
Creating LL OSD context new
** INFO: <bus_callback:175>: Pipeline running
**PERF: 94.06 (94.06) 28.18 (28.18)
**PERF: 24.81 (25.25) 25.01 (25.45)
Segmentation fault (core dumped)
Quick follow up , pipeline fails even when I try to run using multiple videos with following config , however it runs without any issue on single file.
Hi,
Would suggest you reset ds-example to default and try again. From the information, it looks to be an issue in customization code in ds-example.
The config file is verified working. Please try to run it as a reference example and do further debugging.