Please provide complete information as applicable to your setup.
• Hardware Platform: Jetson Orin Nano
• DeepStream Version 6.2
• JetPack Version (valid for Jetson only) 5.1.1
• TensorRT Version 8.5.2.2
• Issue Type( questions, new requirements, bugs) Problem/Question
• 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’m constructing a pipeline that retrieves input from an RTSP camera, performs processing using the PeopleNet model, and subsequently showcases the processed frames on a display. for that, I use the deepstream-app -c
command. This is the pipeline config file:
[application]
enable-perf-measurement=1
perf-measurement-interval-sec=1
[tiled-display]
enable=0
rows=1
columns=1
width=640
height=360
gpu-id=0
[source1]
enable=0
#Type - 1=CameraV4L2 2=URI 3=MultiURI
type=2
num-sources=1
uri=file:///home/edgekit/Documents/edgekit-people-counting-demo/graphics/input_resized.mp4
gpu-id=0
[source0]
enable=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI 4=RTSP
type=4
#camera-width=1920
#camera-height=1080
uri=rtsp://192.168.178.139:554/stream0
#video-format=RGBA
[streammux]
gpu-id=0
batch-size=1
batched-push-timeout=40000
live-source=1
## Set muxer output width and height
width=960
height=540
[sink0]
enable=1
#Type - 1=FakeSink 2=EglSink 3=File
type=2
sync=1
source-id=1
gpu-id=0
nvbuf-memory-type=0
[osd]
enable=1
gpu-id=0
# process mode 0=CPU 1=GPU
process-mode=1
border-width=2
text-size=15
text-color=1;1;1;1;
text-bg-color=0.3;0.3;0.3;1
display-bbox=1
display-mask=0
font=Arial
[videoconvert]
enable=0
src_crop = "0:0:1920:1080"
dest_crop = "0:270:960:540"
[primary-gie]
enable=1
#(0): nvinfer; (1): nvinferserver
plugin-type=0
gpu-id=0
# Modify as necessary
batch-size=1
#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
gie-unique-id=1
config-file=./config_infer_primary_peoplenet.txt
#config-file=triton/config_infer_primary_peoplenet.txt
#config-file=triton-grpc/config_infer_primary_peoplenet.txt
[sink1]
enable=1
#Type - 1=FakeSink 2=EglSink 3=File 4=RTSPStreaming 5=Overlay
type=3
#1=mp4 2=mkv
container=1
#1=h264 2=h265 3=mpeg4
codec=1
#encoder type 0=Hardware 1=Software
enc-type=1
sync=0
bitrate=4000000
#H264 Profile - 0=Baseline 2=Main 4=High
#H265 Profile - 0=Main 1=Main10
profile=0
#udp-buffer-size= 1000
output-file=../../graphics/output_ds6.mp4
#source-id=0 # Enabling this prevents from creating the output file
[sink2]
enable=0
#Type - 1=FakeSink 2=EglSink 3=File 4=RTSPStreaming 5=Overlay
type=4
#1=h264 2=h265
codec=1
#encoder type 0=Hardware 1=Software
enc-type=1
sync=0
bitrate=5120000
#H264 Profile - 0=Baseline 2=Main 4=High
#H265 Profile - 0=Main 1=Main10
profile=0
# set below properties in case of RTSPStreaming
rtsp-port=554
udp-port=8091
[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-lib-file=/opt/nvidia/deepstream/deepstream/lib/gst-plugins/libnvdsgst_tracker.so #Did not work with any .yml configuration file
#ll-config-file required to set different tracker types
#ll-config-file=/opt/nvidia/deepstream/deepstream/samples/configs/deepstream-app/config_tracker_IOU.yml #Each detected person has a new id
ll-config-file=/opt/nvidia/deepstream/deepstream/samples/configs/deepstream-app/config_tracker_NvDCF_perf.yml #Track the person if he/she gets out of frame and then go back
#ll-config-file=/opt/nvidia/deepstream/deepstream/samples/configs/deepstream-app/config_tracker_NvDCF_accuracy.yml #Doesn't work
#ll-config-file=/opt/nvidia/deepstream/deepstream/samples/configs/deepstream-app/config_tracker_NvDeepSORT.yml #Doesn't work
gpu-id=0
enable-batch-process=1
enable-past-frame=1
display-tracking-id=1
[nvds-analytics]
enable=0
config-file=nvdsanalytics_config.txt
[ds-example]
enable=1
processing-width=960
processing-height=540
full-frame=0
gpu-id=0
unique-id=3
blur-objects=1
And this is the output log:
WARNING: [TRT]: Using an engine plan file across different models of devices is not recommended and is likely to affect performance or even cause errors.
0:00:05.144446701 215711 0xaaab0889d550 INFO nvinfer gstnvinfer.cpp:680:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::deserializeEngineAndBackend() <nvdsinfer_context_impl.cpp:1909> [UID = 1]: deserialized trt engine from :/home/edgekit/Documents/edgekit-people-counting-demo/deepstream_demo/models/deployable_quantized_v2.5/resnet34_peoplenet_int8.etlt.engine
INFO: [Implicit Engine Info]: layers num: 3
0 INPUT kFLOAT input_1 3x544x960
1 OUTPUT kFLOAT output_bbox/BiasAdd 12x34x60
2 OUTPUT kFLOAT output_cov/Sigmoid 3x34x60
ERROR: [TRT]: 3: Cannot find binding of given name: output_bbox/BiasAdd:0
0:00:05.348068069 215711 0xaaab0889d550 WARN nvinfer gstnvinfer.cpp:677:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Warning from NvDsInferContextImpl::checkBackendParams() <nvdsinfer_context_impl.cpp:1876> [UID = 1]: Could not find output layer 'output_bbox/BiasAdd:0' in engine
ERROR: [TRT]: 3: Cannot find binding of given name: output_cov/Sigmoid:0
0:00:05.348123430 215711 0xaaab0889d550 WARN nvinfer gstnvinfer.cpp:677:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Warning from NvDsInferContextImpl::checkBackendParams() <nvdsinfer_context_impl.cpp:1876> [UID = 1]: Could not find output layer 'output_cov/Sigmoid:0' in engine
0:00:05.348146662 215711 0xaaab0889d550 INFO nvinfer gstnvinfer.cpp:680:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::generateBackendContext() <nvdsinfer_context_impl.cpp:2012> [UID = 1]: Use deserialized engine model: /home/edgekit/Documents/edgekit-people-counting-demo/deepstream_demo/models/deployable_quantized_v2.5/resnet34_peoplenet_int8.etlt.engine
0:00:05.357061947 215711 0xaaab0889d550 INFO nvinfer gstnvinfer_impl.cpp:328:notifyLoadModelStatus:<primary_gie> [UID 1]: Load new model:/home/edgekit/Documents/edgekit-people-counting-demo/deepstream_demo/config/./config_infer_primary_peoplenet.txt sucessfully
Runtime commands:
h: Print this help
q: Quit
p: Pause
r: Resume
**PERF: FPS 0 (Avg)
**PERF: 0.00 (0.00)
** INFO: <bus_callback:239>: Pipeline ready
** ERROR: <cb_newpad3:510>: Failed to link depay loader to rtsp src
Opening in BLOCKING MODE
NvMMLiteOpen : Block : BlockType = 261
NVMEDIA: Reading vendor.tegra.display-size : status: 6
NvMMLiteBlockCreate : Block : BlockType = 261
** INFO: <bus_callback:225>: Pipeline running
**PERF: 26.23 (23.40)
**PERF: 25.45 (25.52)
**PERF: 24.67 (24.83)
**PERF: 25.38 (25.18)
**PERF: 24.38 (24.90)
**PERF: 25.51 (24.92)
Although the pipeline is working, there is no stream window popping-up and the output mp4 file is not correctly encoded (though it contains information).
Thank you in advance!