• Hardware Platform (Jetson / GPU)
NVIDIA Jetson Nano (Developer Kit Version)
• DeepStream Version
5.0.0
• JetPack Version (valid for Jetson only)
4.4[L4T 32.4.3]
• TensorRT Version
7.1.3.0
• NVIDIA GPU Driver Version (valid for GPU only)
I don’t know how to find GPU Driver Version on Jetson nano
When I run deepstream-app -c test.txt at path /opt/nvidia/deepstream/deepstream-5.0/samples/configs/deepstream-app/ , it will run OK.
test.txt :
# Copyright (c) 2019 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=2
columns=1
width=640
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=3
#uri=file://../../streams/sample_1080p_h264.mp4
uri=rtsp://127.0.0.1:8554/test
num-sources=1
#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 4=RTSP
type=3
#uri=file://../../streams/sample_1080p_h264.mp4
uri=rtsp://127.0.0.1:8554/test
num-sources=1
#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
[sink0]
enable=1
#Type - 1=FakeSink 2=EglSink 3=File
type=5
sync=1
source-id=0
gpu-id=0
qos=0
nvbuf-memory-type=0
overlay-id=1
[sink1]
enable=0
type=3
#1=mp4 2=mkv
container=1
#1=h264 2=h265
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=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=1
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
# 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_Nano/resnet10.caffemodel_b8_fp16.engine
batch-size=2
#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=4
gie-unique-id=1
nvbuf-memory-type=0
config-file=config_infer_primary_nano.txt
[tracker]
enable=1
tracker-width=480
tracker-height=272
#ll-lib-file=/opt/nvidia/deepstream/deepstream-5.0/lib/libnvds_mot_iou.so
ll-lib-file=/opt/nvidia/deepstream/deepstream-5.0/lib/libnvds_mot_klt.so
#ll-config-file required for IOU only
#ll-config-file=iou_config.txt
gpu-id=0
[tests]
file-loop=0
But if I run at other folder, for example /home/user, it will occur following errors.
Error: Could not parse model engine file path
Failed to parse group property
** ERROR: <gst_nvinfer_parse_config_file:1242>: failed
Using winsys: x11
gstnvtracker: Loading low-level lib at /opt/nvidia/deepstream/deepstream-5.0/lib/libnvds_mot_klt.so
gstnvtracker: Optional NvMOT_RemoveStreams not implemented
gstnvtracker: Batch processing is OFF
gstnvtracker: Past frame output is OFF
0:00:00.246000790 19195 0x38d32200 WARN nvinfer gstnvinfer.cpp:766:gst_nvinfer_start:<primary_gie> error: Configuration file parsing failed
0:00:00.246075115 19195 0x38d32200 WARN nvinfer gstnvinfer.cpp:766:gst_nvinfer_start:<primary_gie> error: Config file path: /home/user/config_infer_primary_nano.txt
** ERROR: <main:655>: Failed to set pipeline to PAUSED
Quitting
ERROR from primary_gie: Configuration file parsing failed
Debug info: /dvs/git/dirty/git-master_linux/deepstream/sdk/src/gst-plugins/gst-nvinfer/gstnvinfer.cpp(766): gst_nvinfer_start (): /GstPipeline:pipeline/GstBin:primary_gie_bin/GstNvInfer:primary_gie:
Config file path: /home/user/config_infer_primary_nano.txt
App run failed
I try to copy config_infer_primary_nano.txt to /home/user path and modify config to using deepstream install path:
[property]
gpu-id=0
net-scale-factor=0.0039215697906911373
model-file=/opt/nvidia/deepstream/deepstream-5.0/samples/models/Primary_Detector_Nano/resnet10.caffemodel
proto-file=/opt/nvidia/deepstream/deepstream-5.0/samples/models/Primary_Detector_Nano/resnet10.prototxt
model-engine-file=/opt/nvidia/deepstream/deepstream-5.0/samples/models/Primary_Detector_Nano/resnet10.caffemodel_b8_gpu0_fp16.engine
labelfile-path=/opt/nvidia/deepstream/deepstream-5.0/samples/models/Primary_Detector_Nano/labels.txt
batch-size=8
process-mode=1
model-color-format=0
## 0=FP32, 1=INT8, 2=FP16 mode
network-mode=2
num-detected-classes=4
interval=0
gie-unique-id=1
output-blob-names=conv2d_bbox;conv2d_cov/Sigmoid
force-implicit-batch-dim=1
#parse-bbox-func-name=NvDsInferParseCustomResnet
#custom-lib-path=/path/to/libnvdsparsebbox.so
## 0=Group Rectangles, 1=DBSCAN, 2=NMS, 3= DBSCAN+NMS Hybrid, 4 = None(No clustering)
#cluster-mode=1
#scaling-filter=0
#scaling-compute-hw=0
#Use these config params for group rectangles clustering mode
[class-attrs-all]
pre-cluster-threshold=0.2
group-threshold=1
eps=0.2
roi-top-offset=0
roi-bottom-offset=0
detected-min-w=0
detected-min-h=0
detected-max-w=0
detected-max-h=0
But it still not working, how to solve this problem?
I’ve installed DeepStream 5.0 GA and DeepStream 5.0 Python by @Fiona.Chen in this post