I want to use python sample to stream with command:
python3 deepstream_test_3.py rtsp://admin:passwd@ip:554/media/
and I got
Creating Pipeline
Creating streamux
Creating source_bin 0
Creating source bin
source-bin-00
Creating Pgie
Creating tiler
Creating nvvidconv
Creating nvosd
Creating transform
Creating EGLSink
Atleast one of the sources is live
Adding elements to Pipeline
Linking elements in the Pipeline
Now playing...
1 : rtsp://admin:passwd@ip:554/media/
Starting pipeline
Using winsys: x11
ERROR: Deserialize engine failed because file path: /usr/local/deepstream_python_apps/apps/deepstream-test3/../../../../samples/models/Primary_Detector/resnet10.caffemodel_b1_gpu0_int8.engine open error
0:00:01.482180951 25590 0xc795010 WARN nvinfer gstnvinfer.cpp:616:gst_nvinfer_logger:<primary-inference> NvDsInferContext[UID 1]: Warning from NvDsInferContextImpl::deserializeEngineAndBackend() <nvdsinfer_context_impl.cpp:1690> [UID = 1]: deserialize engine from file :/usr/local/deepstream_python_apps/apps/deepstream-test3/../../../../samples/models/Primary_Detector/resnet10.caffemodel_b1_gpu0_int8.engine failed
0:00:01.482247828 25590 0xc795010 WARN nvinfer gstnvinfer.cpp:616:gst_nvinfer_logger:<primary-inference> NvDsInferContext[UID 1]: Warning from NvDsInferContextImpl::generateBackendContext() <nvdsinfer_context_impl.cpp:1797> [UID = 1]: deserialize backend context from engine from file :/usr/local/deepstream_python_apps/apps/deepstream-test3/../../../../samples/models/Primary_Detector/resnet10.caffemodel_b1_gpu0_int8.engine failed, try rebuild
0:00:01.482319496 25590 0xc795010 INFO nvinfer gstnvinfer.cpp:619:gst_nvinfer_logger:<primary-inference> NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::buildModel() <nvdsinfer_context_impl.cpp:1715> [UID = 1]: Trying to create engine from model files
ERROR: Cannot access prototxt file '/usr/local/deepstream_python_apps/apps/deepstream-test3/../../../../samples/models/Primary_Detector/resnet10.prototxt'
ERROR: failed to build network since parsing model errors.
ERROR: failed to build network.
0:00:01.482583617 25590 0xc795010 ERROR nvinfer gstnvinfer.cpp:613:gst_nvinfer_logger:<primary-inference> NvDsInferContext[UID 1]: Error in NvDsInferContextImpl::buildModel() <nvdsinfer_context_impl.cpp:1735> [UID = 1]: build engine file failed
0:00:01.482614972 25590 0xc795010 ERROR nvinfer gstnvinfer.cpp:613:gst_nvinfer_logger:<primary-inference> NvDsInferContext[UID 1]: Error in NvDsInferContextImpl::generateBackendContext() <nvdsinfer_context_impl.cpp:1821> [UID = 1]: build backend context failed
0:00:01.482643306 25590 0xc795010 ERROR nvinfer gstnvinfer.cpp:613:gst_nvinfer_logger:<primary-inference> NvDsInferContext[UID 1]: Error in NvDsInferContextImpl::initialize() <nvdsinfer_context_impl.cpp:1148> [UID = 1]: generate backend failed, check config file settings
0:00:01.482683411 25590 0xc795010 WARN nvinfer gstnvinfer.cpp:809:gst_nvinfer_start:<primary-inference> error: Failed to create NvDsInferContext instance
0:00:01.482705235 25590 0xc795010 WARN nvinfer gstnvinfer.cpp:809:gst_nvinfer_start:<primary-inference> error: Config file path: dstest3_pgie_config.txt, NvDsInfer Error: NVDSINFER_CONFIG_FAILED
Error: gst-resource-error-quark: Failed to create NvDsInferContext instance (1): /dvs/git/dirty/git-master_linux/deepstream/sdk/src/gst-plugins/gst-nvinfer/gstnvinfer.cpp(809): gst_nvinfer_start (): /GstPipeline:pipeline0/GstNvInfer:primary-inference:
Config file path: dstest3_pgie_config.txt, NvDsInfer Error: NVDSINFER_CONFIG_FAILED
Exiting app
• 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
But I can open this script by using deepstream-app -c by the @DaneLLL of this post
# 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 it is not in windowed mode, I can not close it by using X button, only ctrl + C to kill process
What is your platform and software information?
• Hardware Platform (Jetson / GPU)
• DeepStream Version
• JetPack Version (valid for Jetson only)
• TensorRT Version
• NVIDIA GPU Driver Version (valid for GPU only)
Have you checked whether there is /usr/samples/models/Primary_Detector/resnet10.prototxt in your system?
I don’t think you have installed python sdk and sample correctly. Please clean your system and install DeepStream 5.0 GA and DeepStream 5.0 Python according to the instruction:
https://docs.nvidia.com/metropolis/deepstream/dev-guide/index.html#page/DeepStream_Development_Guide/deepstream_quick_start.html#
https://docs.nvidia.com/metropolis/deepstream/dev-guide/index.html#page/DeepStream_Development_Guide/deepstream_Python_sample_apps.html#