Please provide complete information as applicable to your setup.
• Hardware Platform (Jetson / GPU):dGPU
• DeepStream Version:6.1.1
• TensorRT Version:8.4.1
• NVIDIA GPU Driver Version (valid for GPU only):515.65.01
• Issue Type( questions, new requirements, bugs):questions
• How to reproduce the issue ? (This is for bugs. Including which sample app is using, the configuration files content, the command line used and other details for reproducing)
I ran the deepstream-test5-app sample using new nvstreammux for 1 day.
I also measured the RSS of that program with ps -aux
.
When I checked the results, it seemed to have a 528KB memory leak.
How can I fix this memory leak?
I ran this command in thre docker container.
command
cd /opt/nvidia/deepstream/deepstream/sources/apps/sample_apps/deepstream-test5/configs/
# change the configuration file and RTSP streaming
export USE_NEW_NVSTREAMMUX=yes
/opt/nvidia/deepstream/deepstream/bin/deepstream-test5-app -c test5_config_file_src_infer.txt
I use this ocnfig file
[application]
enable-perf-measurement=1
perf-measurement-interval-sec=5
#gie-kitti-output-dir=streamscl
[tiled-display]
enable=0 # change to disable
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 # change to RTSP type
uri=rtsp://<IP address>:554/test.mpeg4 # change to RTSP URI
num-sources=2
gpu-id=0
nvbuf-memory-type=0
[source1]
enable=0 # change to disable
#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=1 # change to fakesink type
sync=0
source-id=0
gpu-id=0
nvbuf-memory-type=0
[sink1]
enable=0 # change to disable
#Type - 1=FakeSink 2=EglSink 3=File 4=UDPSink 5=nvdrmvideosink 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/lib/libnvds_kafka_proto.so
#Provide your msg-broker-conn-str here
msg-broker-conn-str=<host>;<port>;<topic>
topic=<topic>
#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/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=1 # change to 1
## 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/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