onnx目标检测模型部署-在Jetson-Nano上使用deepstream部署ONNX模型项目C++源码（含使用说明）.zip

################################################################################ # Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved. # # Permission is hereby granted, free of charge, to any person obtaining a # copy of this software and associated documentation files (the "Software"), # to deal in the Software without restriction, including without limitation # the rights to use, copy, modify, merge, publish, distribute, sublicense, # and/or sell copies of the Software, and to permit persons to whom the # Software is furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL # THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING # FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER # DEALINGS IN THE SOFTWARE. ################################################################################ [application] enable-perf-measurement=1 perf-measurement-interval-sec=5 #gie-kitti-output-dir=streamscl [tiled-display] enable=1 rows=2 columns=2 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 type=3 uri=file://../vids/sample_%d.mp4 num-sources=4 drop-frame-interval=1 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=2 sync=0 source-id=0 gpu-id=0 nvbuf-memory-type=0 [sink1] enable=1 #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 [sink2] enable=1 #Type - 1=FakeSink 2=EglSink 3=File 4=RTSPStreaming type=3 #1=h264 2=h265 codec=1 sync=0 bitrate=4000000 container=1 output-file=./output.mp4 [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;1 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 width=1200 height=1200 ##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=model_b1_fp32.engine labelfile-path=../labels.txt 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 nvbuf-memory-type=0 config-file=config_infer_custom_yolo.txt [tests] file-loop=0