'2022/03/29'에 해당되는 글 3건

  1. 2022.03.29 deepstream part.3
  2. 2022.03.29 deepstream onnx part.2
  3. 2022.03.29 jetson nano python numpy Illegal instruction (core dumped)
embeded/jetson2022. 3. 29. 16:02

 

[링크 : https://github.com/NVIDIA-AI-IOT/deepstream_python_apps]

[링크 : https://github.com/NVIDIA-AI-IOT/deepstream_python_apps/tree/master/apps/deepstream-ssd-parser]

 

 

----

tritonserver for jetson (build)

[링크 : https://github.com/triton-inference-server/server/blob/main/docs/jetson.md]

 

+

[ 50%] Building CXX object CMakeFiles/triton-core.dir/backend_model_instance.cc.o
In file included from /home/jetson/work/server/build/_deps/repo-core-src/src/backend_model_instance.cc:37:0:
/home/jetson/work/server/build/_deps/repo-core-src/src/metrics.h:40:10: fatal error: dcgm_agent.h: No such file or directory
 #include <dcgm_agent.h>
          ^~~~~~~~~~~~~~
compilation terminated.

[링크 : https://github.com/NVIDIA/gpu-monitoring-tools/tree/master/bindings/go/dcgm]

  [링크 : https://github.com/NVIDIA/gpu-monitoring-tools]

 

pytorch 다운로드 경로

[링크 : https://jstar0525.tistory.com/171]

 

Known Issues
Triton PIP wheels for ARM SBSA are not available from PyPI and pip will install an incorrect Jetson version of Triton for ARM SBSA. The correct wheel file can be pulled directly from the ARM SBSA SDK image and manually installed.

[링크 : https://github.com/triton-inference-server/server/releases]

 

$ sudo docker pull nvcr.io/nvidia/tritonserver:21.11-py3-sdk

[링크 : https://zhuanlan.zhihu.com/p/471291236]

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Posted by 구차니

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embeded/jetson2022. 3. 29. 11:32

생각해보니 deepstream onnx  github프로젝트의 경우

tiny_yolov2를 기반으로 작동하도록 libnvdsinfer_custom_bbox_tiny_yolo.so 를 생성했으니

ssd 와는 구조가 달라 당연히(?) 맞지 않으니 에러가 발생하고 죽는 듯.

[링크 : https://github.com/thatbrguy/Deep-Stream-ONNX]

 

ERROR: [TRT]: 2: [pluginV2DynamicExtRunner.cpp::execute::115] Error Code 2: Internal Error (Assertion status == kSTATUS_SUCCESS failed.)
ERROR: Build engine failed from config file
ERROR: failed to build trt engine.
0:08:17.537206102  9070     0x3f617730 ERROR                nvinfer gstnvinfer.cpp:632:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Error in NvDsInferContextImpl::buildModel() <nvdsinfer_context_impl.cpp:1934> [UID = 1]: build engine file failed
0:08:17.545680634  9070     0x3f617730 ERROR                nvinfer gstnvinfer.cpp:632:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Error in NvDsInferContextImpl::generateBackendContext() <nvdsinfer_context_impl.cpp:2020> [UID = 1]: build backend context failed
0:08:17.545766053  9070     0x3f617730 ERROR                nvinfer gstnvinfer.cpp:632:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Error in NvDsInferContextImpl::initialize() <nvdsinfer_context_impl.cpp:1257> [UID = 1]: generate backend failed, check config file settings
0:08:17.546456543  9070     0x3f617730 WARN                 nvinfer gstnvinfer.cpp:841:gst_nvinfer_start:<primary_gie> error: Failed to create NvDsInferContext instance
0:08:17.546521285  9070     0x3f617730 WARN                 nvinfer gstnvinfer.cpp:841:gst_nvinfer_start:<primary_gie> error: Config file path: /home/jetson/work/Deep-Stream-ONNX/config/config_infer_custom_yolo.txt, NvDsInfer Error: NVDSINFER_CONFIG_FAILED
** ERROR: <main:658>: Failed to set pipeline to PAUSED

 

azure의 custom vision 의 README에 기재된 링크를 가보았는데

[링크 : https://github.com/Azure-Samples/customvision-export-samples]

 

onnx 포맷으로는 python과 c#만 제공하고

해당 사이트에서 python을 받아서 실행해보니 하나의 사진에 대해서 처리가 가능한 예제를 제공한다.

[링크 : https://github.com/Azure-Samples/customvision-export-samples/tree/main/samples/python/onnx]

[링크 : https://github.com/Azure-Samples/customvision-export-samples/tree/main/samples/csharp/onnx]

 

 

+

ssd deepstream 예제가 있는데

python 스크립트에 h264 elementary stream을 넣어주어야 한댄다

[링크 : https://github.com/NVIDIA-AI-IOT/deepstream_python_apps/tree/master/apps/deepstream-ssd-parser]

 

-h h264가 포인트 인 듯.

$ ffmpeg -f video4linux2 -s 320x240 -i /dev/video0 -vcodec libx264 -f h264 test.264

[링크 : https://stackoverflow.com/questions/27090114/what-does-elementary-stream-mean-in-terms-of-h264]

 

JVT NAL sequence, H.264 라는 타입으로 변경된 듯.

sample_0.h264: JVT NAL sequence, H.264 video @ L 31
sample_0.mp4:  ISO Media, MP4 v2 [ISO 14496-14]

 

Joint Video Team (JVT)
NAL: Network Abstraction Layer

[링크 : http://iphome.hhi.de/suehring/tml/JM%20Reference%20Software%20Manual%20(JVT-AE010).pdf]

 

+

sample_ssd_relu6.uff 파일은 ssd inception v2 기반 모델인가?

[링크 :  https://eva-support.adlinktech.com/docs/ssdnbspinception-v2-nbsp-nbsp-nbsp-nbspnbsp]

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embeded/jetson2022. 3. 29. 11:27

 

$ OPENBLAS_CORETYPE=ARMV8 python3

[링크 : https://stackoverflow.com/questions/65631801/illegal-instructioncore-dumped-error-on-jetson-nano]

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