Smart record video deepstream app

can someone provide “smart record video deepstream app” Python Git repository Link ,

i am unable to find “deepstream-test5” for python

There is no such sample.

i tried c++ app , and i get below error


root@c9ff04c856cb:/opt/nvidia/deepstream/deepstream-6.0/sources/apps/sample_apps/deepstream-test5# ./deepstream-test5-app -c configs/test5_dec_infer-resnet_tracker_sgie_tiled_display_int8.txt -p 0
** ERROR: <main:1455>: Failed to set pipeline to PAUSED
Quitting
ERROR from sink_sub_bin_sink2: Could not configure supporting library.
Debug info: gstnvmsgbroker.cpp(402): legacy_gst_nvmsgbroker_start (): /GstPipeline:pipeline/GstBin:sink_sub_bin2/GstNvMsgBroker:sink_sub_bin_sink2:
unable to connect to broker library
ERROR from sink_sub_bin_sink2: GStreamer error: state change failed and some element failed to post a proper error message with the reason for the failure.
Debug info: gstbasesink.c(5265): gst_base_sink_change_state (): /GstPipeline:pipeline/GstBin:sink_sub_bin2/GstNvMsgBroker:sink_sub_bin_sink2:
Failed to start
App run failed

above error is fixed .

below error i have received


root@c9ff04c856cb:/opt/nvidia/deepstream/deepstream-6.0/sources/apps/sample_apps/deepstream-test5# ./deepstream-test5-app -c configs/test5_config_file_src_infer.txt -p 0
%3|1642522223.920|FAIL|rdkafka#producer-1| [thrd:ec2-18-119-132-28.us-east-2.compute.amazonaws.com:5672/bootstra]: ec2-18-119-132-28.us-east-2.compute.amazonaws.com:5672/bootstrap: Receive failed: Invalid response size 1095586128 (0..100000000): increase receive.message.max.bytes
%3|1642522223.921|ERROR|rdkafka#producer-1| [thrd:ec2-18-119-132-28.us-east-2.compute.amazonaws.com:5672/bootstra]: ec2-18-119-132-28.us-east-2.compute.amazonaws.com:5672/bootstrap: Receive failed: Invalid response size 1095586128 (0..100000000): increase receive.message.max.bytes
** ERROR: <main:1455>: Failed to set pipeline to PAUSED
Quitting
App run failed

below is the config file : test5_config_file_src_infer.txt

################################################################################
# Copyright (c) 2018-2020, 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.
################################################################################

[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=3
uri=file://../../../../../samples/streams/sample_1080p_h264.mp4
num-sources=2
gpu-id=0
nvbuf-memory-type=0

[source1]
enable=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI
type=3
uri=file://../../../../../samples/streams/sample_1080p_h264.mp4
num-sources=2
gpu-id=0
nvbuf-memory-type=0

[sink0]
enable=1
#Type - 1=FakeSink 2=EglSink 3=File
type=2
sync=1
source-id=0
gpu-id=0
nvbuf-memory-type=0

[sink1]
enable=1
#Type - 1=FakeSink 2=EglSink 3=File 4=UDPSink 5=nvoverlaysink 6=MsgConvBroker
type=6
msg-conv-config=dstest5_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
msg-broker-proto-lib=/opt/nvidia/deepstream/deepstream-6.0/lib/libnvds_kafka_proto.so
#Provide your msg-broker-conn-str here
#msg-broker-conn-str=<host>;<port>;<topic>
msg-broker-conn-str=ec2-18-119-132-28.us-east-2.compute.amazonaws.com;5672;rabbit
#topic=<topic>
topic=<rabbit>
#Optional:
#msg-broker-config=../../deepstream-test4/cfg_kafka.txt

[sink2]
enable=0
type=3
#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=0

# 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=dstest5_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
# Name of library having custom implementation.
#msg-conv-msg2p-lib=<val>
# 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-6.0/lib/libnvds_kafka_proto.so
conn-str=<host>;<port>
config-file=<broker config file e.g. cfg_kafka.txt>
subscribe-topic-list=<topic1>;<topic2>;<topicN>
# Use this option if message has sensor name as id instead of index (0,1,2 etc.).
#sensor-list-file=dstest5_msgconv_sample_config.txt

[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=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=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
## 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=4
## 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
gie-unique-id=1
model-engine-file=../../../../../samples/models/Primary_Detector/resnet10.caffemodel_b4_gpu0_int8.engine
labelfile-path=../../../../../samples/models/Primary_Detector/labels.txt
config-file=../../../../../samples/configs/deepstream-app/config_infer_primary.txt
#infer-raw-output-dir=../../../../../samples/primary_detector_raw_output/

[tracker]
enable=1
# For NvDCF and DeepSORT 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-6.0/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_NvDCF_perf.yml
# ll-config-file=../../../../../samples/configs/deepstream-app/config_tracker_NvDCF_accuracy.yml
# ll-config-file=../../../../../samples/configs/deepstream-app/config_tracker_DeepSORT.yml
gpu-id=0
enable-batch-process=1
enable-past-frame=1
display-tracking-id=1

[tests]
file-loop=0

Please set “GST_DEBUG=3” to debug.

below is the error i get

root@c9ff04c856cb:/opt/nvidia/deepstream/deepstream-6.0/sources/apps/sample_apps/deepstream-test5# export GST_DEBUG=3
root@c9ff04c856cb:/opt/nvidia/deepstream/deepstream-6.0/sources/apps/sample_apps/deepstream-test5# ./deepstream-test5-app -c configs/test5_config_file_src_infer.txt -p 0
%3|1642597953.395|FAIL|rdkafka#producer-1| [thrd:ec2-18-119-132-28.us-east-2.compute.amazonaws.com:5672/bootstra]: ec2-18-119-132-28.us-east-2.compute.amazonaws.com:5672/bootstrap: Receive failed: Invalid response size 1095586128 (0..100000000): increase receive.message.max.bytes
%3|1642597953.395|ERROR|rdkafka#producer-1| [thrd:ec2-18-119-132-28.us-east-2.compute.amazonaws.com:5672/bootstra]: ec2-18-119-132-28.us-east-2.compute.amazonaws.com:5672/bootstrap: Receive failed: Invalid response size 1095586128 (0..100000000): increase receive.message.max.bytes
0:00:00.663136302 13579 0x55d947749990 ERROR            egladaption ext/eglgles/gstegladaptation_egl.c:160:gst_egl_adaptation_init_display:<sink_sub_bin_sink1> Could not init EGL display connection
0:00:00.663170708 13579 0x55d947749990 ERROR            egladaption ext/eglgles/gstegladaptation_egl.c:183:gst_egl_adaptation_init_display:<sink_sub_bin_sink1> EGL call returned error 3000
0:00:00.663180926 13579 0x55d947749990 ERROR            egladaption ext/eglgles/gstegladaptation_egl.c:185:gst_egl_adaptation_init_display:<sink_sub_bin_sink1> Couldn't setup window/surface from handle
0:00:00.663190150 13579 0x55d947749990 ERROR          nveglglessink ext/eglgles/gsteglglessink.c:536:egl_init:<sink_sub_bin_sink1> Couldn't init EGL display
0:00:00.663198670 13579 0x55d947749990 ERROR          nveglglessink ext/eglgles/gsteglglessink.c:562:egl_init:<sink_sub_bin_sink1> Failed to perform EGL init
** ERROR: <main:1455>: Failed to set pipeline to PAUSED
Quitting
App run failed
root@c9ff04c856cb:/opt/nvidia/deepstream/deepstream-6.0/sources/apps/sample_apps/deepstream-test5#

Please provide complete information as applicable to your setup.

• Hardware Platform (Jetson / GPU)
• DeepStream Version
• JetPack Version (valid for Jetson only)
• TensorRT Version
• NVIDIA GPU Driver Version (valid for GPU only)

Did you run the case from a remote terminal? Did you run the case in docker container?

yes its docker container deepstream.6.0-devev

root@c9ff04c856cb:/opt/nvidia/deepstream/deepstream-6.0# nvidia-smi
Thu Jan 20 04:14:30 2022
±----------------------------------------------------------------------------+
| NVIDIA-SMI 470.63.01 Driver Version: 470.63.01 CUDA Version: 11.4 |
|-------------------------------±---------------------±---------------------+
| 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 Tesla T4 Off | 00000000:00:1E.0 Off | 0 |
| N/A 31C P0 26W / 70W | 0MiB / 15109MiB | 0% Default |
| | | N/A |
±------------------------------±---------------------±---------------------+

±----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
±----------------------------------------------------------------------------+

Please make sure you have connect a monitor to your T4 server. And before you run the docker container, you have run “xhost +”.

After all this, you can run the docker container. Don’t forget to include “-v /tmp/.X11-unix:/tmp/.X11-unix -e DISPLAY=$DISPLAY” in your “docker run” command line.

If you don’t have a monitor or run from a remote terminal, please refer to Quickstart Guide — DeepStream 6.0 Release documentation

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