jetson nano locks up when running deepstream-app

I can successfully run the test app3 against my rtsp camera (hikvision). However when I try to run deepstream-app aginst multiple rtsp cameras it locks up the jetson.

I’ve made a minor change to the ‘source8_1080p_dec_infer-resnet_tracker_tiled_display_fp16_nano.txt’ config file so that I have sources from rtsp cameras (x4). See config file further below.

I have two issues:
(1) the deepstream-app seems to just see the first source and use it 4 times.
(2) the output display is fullscreen and I’m unable to alt-tab to other applications nor quit the app. Its like the whole system freezes - however the app is running well and if I walk in front of my camera it detects in real-time well… Only way I can exit is to pull the power cable out of the jetson and prey it doesn’t corrupt my sd card!
Would be nice if the tiled display used a proper window with the X in the top-left corner to kill the app.

I also notice this in the code:
" (“NOTE: To expand a source in the 2D tiled display and view object details,”
" left-click on the source.\n"
" To go back to the tiled display, right-click anywhere on the window.\n\n");
"

However left/right clicking on the display does nothing.

CONFIG FILE.
Just changed the num sources to 4 and specified the sources

Copyright © 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=2
width=1280
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=3
#uri=file://…/…/streams/sample_1080p_h264.mp4
uri=rtsp://
uri=rtsp://
uri=rtsp://
uri=rtsp://
num-sources=4
#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=1
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=0
live-source=1
batch-size=8
##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_b8_fp16.engine
batch-size=8
#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

Hi,
Please refer to
https://devtalk.nvidia.com/default/topic/1058086/deepstream-sdk/how-to-run-rtp-camera-in-deepstream-on-nano/post/5367474/#5367474

You should have [source0], [source1], [source2], [source3] and each one is with ‘num-sources=1’. Also please set ‘batch-size=4’ in [streammux] and [primary-gie].

Thanks for the info on the sources groups. It’s a bit confusing having a multi-source option that can actually only take one uri and have num sources still set to zero.

My other question was about the jetson freezing. If I have 4 incoming streams that overlay takes up my whole monitor and does not accept mouse clicks so it’s impossible to stop the app running and I can’t switch to anything else. The only solution is to pull the power cable out??

I too am experiencing the same problem, the app loads and runs fine but I can’t find anyway of ending the application, it is running on-top of all my other windows so the only way to stop this is to reset the nano.

Hi,
There are runtime commands you can use to control the pipeline:

Runtime commands:
        h: Print this help
        q: Quit

        p: Pause
        r: Resume

You may consider to use window-based nveglglessink, though we suggest use nvoverlaysink on Jetson Nano.
https://docs.nvidia.com/metropolis/deepstream/dev-guide/index.html#page/DeepStream_Development_Guide%2Fdeepstream_app_config.3.2.html%23wwpID0ENHA

nveglglesink takes certain GPU loading and shall run better on TX2 or Xavier.

Hi,
Attach a config of launching 4 rtsp sources. Please modify uri=rtsp://<source*> to your sources.

# 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=2
width=1280
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://<source1>
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://<source2>
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

[source2]
enable=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI 4=RTSP
type=4
#uri=file://../../streams/sample_1080p_h264.mp4
uri=rtsp://<source3>
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

[source3]
enable=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI 4=RTSP
type=4
#uri=file://../../streams/sample_1080p_h264.mp4
uri=rtsp://<source4>
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=2
sync=1
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=0
live-source=1
batch-size=4
##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_b8_fp16.engine
batch-size=4
#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

We have verified it with HikVision IP cameras( such as DS-2CD2043G0-I,… ) on DS4.0.1. FYI.

Thanks for the example config files. These work well. The locking up issue occurs with the sample apps (test1, test 2, etc) that use the overlay output. If the overlay takes up the whole screen I’m unable to quit. So you have to be careful to keep the dimensions of the overlay window small.
With deepstream-app there is no issue as I can just click ‘q’.