Is it possible to run Deepstream on GTX Titan? Or it has to be Tesla?
When I run with configuration file “source30_720p_dec_infer-resnet_tiled_display_int8.txt”, I got error:
** WARN: <parse_streammux:474>: Unknown key 'config-file' for group [streammux]
** ERROR: <create_multi_source_bin:710>: Failed to create element 'src_bin_muxer'
** ERROR: <create_multi_source_bin:772>: create_multi_source_bin failed
** ERROR: <create_pipeline:790>: create_pipeline failed
** ERROR: <main:588>: Failed to create pipeline
Quitting
App run failed
I change the sink0 to type 1, but it didn’t change anything. Is there any part that I have missed? I downloaded opengl too, and driver should installed properly as command
nvidia-smi
will show the GPU I am using.
What is the architecture of your GTX TITAN ?
Kepler,Maxwell or Pascal?
We have been testing with GTX 1050 , RTX TITAN and RTX 2080 and it works fine.
Try Clearing the Cache by executing the command sudo rm -r ~/.cache/gstreamer-1.0/registry*
It is a Titan X, so should be Maxwell?
Also, i have tried to clean the cache, but same error
Deepstream can work on GeForce cards but we don’t do any validation on any consumer cards. So you can use it but it will be on your own. Alternate is you can either upgrade to T4 or use Jetson dev kits. With a unified sdk in 4.0, you can port between platforms easily.
Can you show your config file?
# Copyright (c) 2018 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=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
#(2): nvbuf-mem-cuda-device - Allocate Device cuda memory
#(3): nvbuf-mem-cuda-unified - Allocate Unified cuda memory
#(4): nvbuf-mem-surface-array - Allocate Surface Array memory, applicable for Jetson
#(5): nvbuf-mem-handle - Allocate Surface Handle memory, applicable for Jetson
#(6): nvbuf-mem-system - Allocate Surface System memory, allocated using calloc
nvbuf-memory-type=0
[source0]
enable=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI
type=3
uri=file://../../streams/sample_720p.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=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI
type=3
uri=file://../../streams/sample_720p.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 3=File
type=3
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 3=mpeg4
## only SW mpeg4 is supported right now.
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=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=30
##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=1280
height=720
##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=config_mux_source30.txt
# 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_int8.engine
#Required to display the PGIE labels, should be added even when using config-file
#property
labelfile-path=../../models/Primary_Detector/labels.txt
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
I tried different sink0 type, 1, 2, 3. But none of them work
sink0, The default type=2 to display, make sure you have screen connection
You can check deepstream 4.0 package source30_1080p_dec_infer-resnet_tiled_display_int8.txt
Hello ChrisDing,
Thanks for your reply! This problem is solved. DeepStream doesn’t work on GTX Titan. After switching to RTX, the problem is solved.
Thanks
Thanks for share.
Can you give more details about “DeepStream doesn’t work on GTX Titan” ? I think it should work.
More specifically I mean analytics server set up in sample test 4. An analytics server with GTX Titan can run all of the required docker containers, but the perception server will not be able to find the broker. Problem was solved after setting up the server with RTX machine.
Please also consider helping with my problem under the link: https://devtalk.nvidia.com/default/topic/1058327/deepstream-sdk/questions-regarding-test-application-4-/post/5369954/#5369954