I am trying to achieve the task mentioned below .
Camera sources will be added dynamically to both memory and the configuration file. This eliminates the need to restart DeepStream when adding new cameras. In case DeepStream restarts, all previously added cameras will be loaded from the configuration file automatically.
Currently working with the occupancy analytics project by NVIDIA (GitHub - NVIDIA-AI-IOT/deepstream-occupancy-analytics: This is a sample application for counting people entering/leaving in a building using NVIDIA Deepstream SDK, Transfer Learning Toolkit (TLT), and pre-trained models. This application can be used to build real-time occupancy analytics applications for smart buildings, hospitals, retail, etc. The application is based on deepstream-test5 sample application.)
I have compiled the project and sucessilly running it for multi stream rtsp but i want to add cameras dynamically to the running deepstreream insstance so that it rtsp will be updated in real time . I have reffered to this deepstream_python_apps/apps/runtime_source_add_delete/deepstream_rt_src_add_del.py at master · NVIDIA-AI-IOT/deepstream_python_apps · GitHub
but not able to get the desired out put .
System specification
Tue Feb 11 11:14:12 2025
±----------------------------------------------------------------------------------------+
| NVIDIA-SMI 550.142 Driver Version: 550.142 CUDA Version: 12.4 |
|-----------------------------------------±-----------------------±---------------------+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+========================+======================|
| 0 NVIDIA RTX A4000 On | 00000000:01:00.0 Off | Off |
| 46% 65C P2 44W / 140W | 7484MiB / 16376MiB | 0% Default |
| | | N/A |
±----------------------------------------±-----------------------±---------------------+
±----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| 0 N/A N/A 2950 G /usr/lib/xorg/Xorg 167MiB |
| 0 N/A N/A 3320 G …3/usr/bin/snapd-desktop-integration 31MiB |
| 0 N/A N/A 71207 G /usr/lib/xorg/Xorg 25MiB |
| 0 N/A N/A 565327 C python3 662MiB |
| 0 N/A N/A 565452 C python3 662MiB |
| 0 N/A N/A 565574 C python3 662MiB |
| 0 N/A N/A 565981 C python3 662MiB |
| 0 N/A N/A 687280 C python3 158MiB |
| 0 N/A N/A 695436 C python3 158MiB |
| 0 N/A N/A 696568 C python3 158MiB |
| 0 N/A N/A 713628 C python3 158MiB |
| 0 N/A N/A 759034 G /usr/bin/gnome-shell 112MiB |
| 0 N/A N/A 858458 C /usr/local/bin/a2f_pipeline.run 3282MiB |
| 0 N/A N/A 937132 G …irefox/5701/usr/lib/firefox/firefox 337MiB |
±----------------------------------------------------------------------------------------+
config file for deepstream occupancy app
################################################################################
# Copyright (c) 2018-2020, NVIDIA CORPORATION. All rights reserved.
#
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# copy of this software and associated documentation files (the "Software"),
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# 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 portionsa 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.
################################################################################
[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
type=4
#uri=file:///opt/nvidia/deepstream/deepstream-7.0/sources/apps/sample_apps/deepstream-occupancy-analytics/videos/video2.mp4
uri=rtsp://username:password@ipaddress:8888
camera-id=1
num-sources=1
gpu-id=0
nvbuf-memory-type=0
[source1]
enable=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI 4=RTSP
type=3
uri=rtsp://username:password@ipaddress:8888
num-sources=1
camera-id=3
gpu-id=0
nvbuf-memory-type=0
# smart record specific fields, valid only for source type=4
# 0 = disable, 1 = through cloud events, 2 = through cloud + local events
smart-record=2
# 0 = mp4, 1 = mkv
#smart-rec-container=0
smart-rec-start-time=1
smart-rec-file-prefix=smart_record
#smart-rec-dir-path=/home/monika/record
# cache size in seconds
smart-rec-cache=10
[source2]
enable=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI
type=4
uri=rtsp://username:password@ipaddress:8888
camera-id=1
num-sources=1
gpu-id=0
nvbuf-memory-type=0
[source3]
enable=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI
type=4
uri=rtsp://username:password@ipaddress:8888
camera-id=1
num-sources=1
gpu-id=0
nvbuf-memory-type=0
[sink0]
enable=1
type=2
#1=mp4 2=mkv
container=1
#1=h264 2=h265
codec=1
#encoder type 0=Hardware 1=Software
enc-type=0
sync=0
#iframeinterval=10
bitrate=100000
#H264 Profile - 0=Baseline 2=Main 4=High
#H265 Profile - 0=Main 1=Main10
profile=0
output-file=resnet.mp4
source-id=0
[sink1]
enable=1
#Type - 1=FakeSink 2=EglSink 3=File 4=UDPSink 5=nvoverlaysink 6=MsgConvBroker
type=6
msg-conv-config=msgconv_sample_config.txt
# Name of library having custom implementation.
# msg-conv-msg2p-lib=/opt/nvidia/deepstream/deepstream/sources/apps/sample_apps/deepstream-occupancy-analytics/bin/jetson/libnvds_msgconv.so
msg-conv-msg2p-lib=/opt/nvidia/deepstream/deepstream-7.0/sources/apps/sample_apps/occupancy_analytics/bin/x86/libnvds_msgconv.so
#(0): PAYLOAD_DEEPSTREAM - Deepstream schema payload
#(1): PAYLOAD_DEEPSTREAM_MINIMAL - Deepstream schema payload minimal
#(256): PAYLOAD_RESERVED - Reserved type
#(257): PAYLOAD_CUSTOM - Custom schema payload
msg-conv-payload-type=0
msg-broker-proto-lib=/opt/nvidia/deepstream/deepstream/lib/libnvds_kafka_proto.so
#Provide your msg-broker-conn-str here
msg-broker-conn-str=kafka_container;9092;quickstart-events
#topic=<topic>
#Optional:
#msg-broker-config=../../deepstream-test4/cfg_kafka.txt
[sink2]
enable=1
type=1
#1=mp4 2=mkv
container=1
#1=h264 2=h265 3=mpeg4
## only SW mpeg4 is supported right now.
codec=3
sync=1
bitrate=2000000
output-file=out.mp4
source-id=2
# sink type = 6 by default creates msg converter + broker.
# To use multiple brokers use this group for converter and use
# sink type = 6 with disable-msgconv = 1
[sink3]
enable=1
type=1
#1=mp4 2=mkv
container=1
#1=h264 2=h265 3=mpeg4
## only SW mpeg4 is supported right now.
codec=3
sync=1
bitrate=2000000
output-file=out.mp4
source-id=3
# sink type = 6 by default creates msg converter + broker.
# To use multiple brokers use this group for converter and use
# sink type = 6 with disable-msgconv = 1
[message-converter]
enable=0
msg-conv-config=msgconv_sample_config.txt
#(0): PAYLOAD_DEEPSTREAM - Deepstream schema payload
#(1): PAYLOAD_DEEPSTREAM_MINIMAL - Deepstream schema payload minimal
#(256): PAYLOAD_RESERVED - Reserved type
#(257): PAYLOAD_CUSTOM - Custom schema payload
msg-conv-payload-type=0
# Id of component in case only selected message to parse.
#msg-conv-comp-id=<val>
# Configure this group to enable cloud message consumer.... [message-converter]
enable=0
msg-conv-config=msgconv_sample_config.txt
#(0): PAYLOAD_DEEPSTREAM - Deepstream schema payload
#(1): PAYLOAD_DEEPSTREAM_MINIMAL - Deepstream schema payload minimal
#(256): PAYLOAD_RESERVED - Reserved type
#(257): PAYLOAD_CUSTOM - Custom schema payload
msg-conv-payload-type=0
# Id of component in case only selected message to parse.
#msg-conv-comp-id=<val>
# Configure this group to enable cloud message consumer.
[message-consumer0]
enable=0
proto-lib=/opt/nvidia/deepstream/deepstream/lib/libnvds_kafka_proto.so
conn-str=localhost;9092
#config-file=<broker config file e.g. cfg_kafka.txt>
subscribe-topic-list=quickstart-events
# Use this option if message has sensor name as id instead of index (0,1,2 etc.).
sensor-list-file=msgconv_sample_config.txt
[osd]
enable=1
gpu-id=0
border-width=1
text-size=10
text-color=1;1;1;1;
text-bg-color=0.3;0.3;0.3;1
font=Arial
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
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
[primary-gie]
enable=1
gpu-id=0
batch-size=2
## 0=FP32, 1=INT8, 2=FP16 mode
bbox-border-color0=1;0;0;1
#bbox-border-color1=0;1;1;1
#bbox-border-color2=0;1;1;1
#bbox-border-color3=0;1;0;1
nvbuf-memory-type=0
interval=0
config-file=pgie_peoplenet_tao_config.txt
#infer-raw-output-dir=../../../../../samples/primary_detector_raw_output/
[tracker]
enable=1
tracker-width=640
tracker-height=384
gpu-id=0
ll-lib-file=/opt/nvidia/deepstream/deepstream/lib/libnvds_nvmultiobjecttracker.so
# ll-config-file required to set different tracker types
# ll-config-file=../../../../samples/configs/deepstream-app/config_tracker_IOU.yml
# ll-config-file=../../../../samples/configs/deepstream-app/config_tracker_NvSORT.yml
ll-config-file=../../../../samples/configs/deepstream-app/config_tracker_NvDCF_perf.yml
# ll-config-file=../../../../samples/configs/deepstream-app/config_tracker_NvDCF_accuracy.yml
# ll-config-file=../../../../samples/configs/deepstream-app/config_tracker_NvDeepSORT.yml
# enable-batch-process=0
[nvds-analytics]
enable=1
config-file=nvdsanalytics_config.txt
[tests]
file-loop=0