Issue on deepstream 6. 3 containers with wsl2

Hi, thank you for your help.
If some other infomration is needed please don´t hesitate

Setup

**system**

GPU NVIDIA GeForce GTX 1650 SUPER
Driver GPU - NVIDIA versión 537.42:
SO - windows 11 - wsl2 Ubuntu 22.04.3 LTS
//Nvidia container toolkit//
dpkg -l | grep nvidia-container-toolkit
ii nvidia-container-toolkit 1.14.2-1
amd64 NVIDIA Container toolkit
ii nvidia-container-toolkit-base 1.14.2-1
amd64 NVIDIA Container Toolkit Base

deepstrean-container; I´ve tested some of the latest
deepstream:6.3-gc-triton-devel
deepstream:6.3-samples
These containers should have everythig installed.

Issue:

**Running** 

deepstream-app -c /opt/nvidia/deepstream/deepstream-6.3/samples/configs/deepstream-app/source30_1080p_dec_infer-resnet_tiled_display_int8.txt

**Output**

0:00:00.469151910 32255 0x55670e4030d0 WARN GST_ELEMENT_FACTORY gstelementfactory.c:458:gst_element_factory_make: no such element factory “nvinfer”!
** ERROR: <create_primary_gie_bin:129>: Failed to create ‘primary_gie’
** ERROR: <create_primary_gie_bin:193>: create_primary_gie_bin failed
** ERROR: <create_pipeline:1576>: create_pipeline failed
** ERROR: main:697: Failed to create pipeline
Quitting
nvstreammux: Successfully handled EOS for source_id=0
App run failed

config file :
[application]
enable-perf-measurement=1
perf-measurement-interval-sec=5
#gie-kitti-output-dir=streamscl

[tiled-display]
enable=1
rows=5
columns=6
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=2
uri=file://…/…/streams/sample_1080p_h264.mp4
num-sources=15
#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=0
#Type - 1=CameraV4L2 2=URI 3=MultiURI 4=RTSP
type=3
uri=file://…/…/streams/sample_1080p_h264.mp4
num-sources=15
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/nv3dsink (Jetson only) 3=File
type=2
sync=1
source-id=0
gpu-id=0
nvbuf-memory-type=0

[sink1]
enable=0
type=3
#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=2000000
#H264 Profile - 0=Baseline 2=Main 4=High
#H265 Profile - 0=Main 1=Main10

set profile only for hw encoder, sw encoder selects profile based on sw-preset

profile=0
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
encoder type 0=Hardware 1=Software
enc-type=0
#sw-preset=1 #for SW enc=(0)None (1)ultrafast (2)superfast (3)veryfast (4)faster
#(5)fast (6)medium (7)slow (8)slower (9)veryslow (10)placebo
sync=0
bitrate=4000000
#H264 Profile - 0=Baseline 2=Main 4=High
#H265 Profile - 0=Main 1=Main10

set profile only for hw encoder, sw encoder selects profile based on sw-preset

profile=0

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
batch-size=1
##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

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/resnet10.caffemodel_b30_gpu0_int8.engine
#Required to display the PGIE labels, should be added even when using config-file
#property
batch-size=30
#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=0
#Required by the app for SGIE, when used along with config-file property
gie-unique-id=1
nvbuf-memory-type=0
config-file=config_infer_primary.txt

[tests]
file-loop=0

WSL2 is not supported so far.

Thanks a lot for your answer. It might have a solution GitHub - sylvain-prevost/deepstream_wsl: Adjustments to Deepstream (v6.2) plugins to enable inference execution/debugging/visualization under WSL2
kind regards
JC

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