I am using this “jetson.utils.videoSource”
image = input.Capture(“/dev/video0”)
when my application runs for a long time then it is ending up to “End of stream”
What does end of stream mean on envidia?
hello bryllatKS,
may I know which JetPack release you’re working with, and what’s your use-case?
how many hours did you put the camera for running, is there any post-processing executed?
thanks
Hi JerryChang,
$ sudo apt-cache show nvidia-jetpack → gives me:
`
Package: nvidia-jetpack
Version: 4.4.1-b50
Architecture: arm64
Maintainer: NVIDIA Corporation
Installed-Size: 194
Depends: nvidia-cuda (= 4.4.1-b50), nvidia-opencv (= 4.4.1-b50), nvidia-cudnn8 (= 4.4.1-b50), nvidia-tensorrt (= 4.4.1-b50), nvidia-visionworks (= 4.4.1-b50), nvidia-container (= 4.4.1-b50), nvidia-vpi (= 4.4.1-b50), nvidia-l4t-jetson-multimedia-api (>> 32.4-0), nvidia-l4t-jetson-multimedia-api (<< 32.5-0)
Homepage: Autonomous Machines | NVIDIA Developer
Priority: standard
Section: metapackages
Filename: pool/main/n/nvidia-jetpack/nvidia-jetpack_4.4.1-b50_arm64.deb
Size: 29412
SHA256: ec502e1e3672c059d8dd49e5673c5b2d8c606584d4173ee514bbc4376547a171
SHA1: 75a405f1ad533bfcd04280d1f9b237b880c39be5
MD5sum: 1267b31d8b8419d9847b0ec4961b15a4
Description: NVIDIA Jetpack Meta Package
Description-md5: ad1462289bdbc54909ae109d1d32c0a8
Package: nvidia-jetpack
Version: 4.4-b186
Architecture: arm64
Maintainer: NVIDIA Corporation
Installed-Size: 194
Depends: nvidia-cuda (= 4.4-b186), nvidia-opencv (= 4.4-b186), nvidia-cudnn8 (= 4.4-b186), nvidia-tensorrt (= 4.4-b186), nvidia-visionworks (= 4.4-b186), nvidia-container (= 4.4-b186), nvidia-vpi (= 4.4-b186), nvidia-l4t-jetson-multimedia-api (>> 32.4-0), nvidia-l4t-jetson-multimedia-api (<< 32.5-0)
Homepage: Autonomous Machines | NVIDIA Developer
Priority: standard
Section: metapackages
Filename: pool/main/n/nvidia-jetpack/nvidia-jetpack_4.4-b186_arm64.deb
Size: 29376
SHA256: 7f90f2def712d993bd84855355aec47a1b63ae54edefcbf4c963dbe0cb6fbf92
SHA1: bd1f0b05adbdf8f0df4dce4f655bb9615172594f
MD5sum: f9d2f9a9dfee794ef361b1bd1ec38130
Description: NVIDIA Jetpack Meta Package
Description-md5: ad1462289bdbc54909ae109d1d32c0a8
Package: nvidia-jetpack
Version: 4.4-b144
Architecture: arm64
Maintainer: NVIDIA Corporation
Installed-Size: 195
Depends: nvidia-container-csv-cuda (= 10.2.89-1), libopencv-python (= 4.1.1-2-gd5a58aa75), libvisionworks-sfm-dev (= 0.90.4.501), libvisionworks-dev (= 1.6.0.501), libnvparsers7 (= 7.1.0-1+cuda10.2), libnvinfer-plugin-dev (= 7.1.0-1+cuda10.2), libnvonnxparsers7 (= 7.1.0-1+cuda10.2), libnvinfer-samples (= 7.1.0-1+cuda10.2), libnvinfer-bin (= 7.1.0-1+cuda10.2), libvisionworks-samples (= 1.6.0.501), libvisionworks-tracking-dev (= 0.88.2.501), vpi-samples (= 0.2.0), tensorrt (= 7.1.0.16-1+cuda10.2), libopencv (= 4.1.1-2-gd5a58aa75), libnvinfer-doc (= 7.1.0-1+cuda10.2), libnvparsers-dev (= 7.1.0-1+cuda10.2), libnvidia-container0 (= 0.9.0~beta.1), nvidia-container-csv-visionworks (= 1.6.0.501), cuda-toolkit-10-2 (= 10.2.89-1), graphsurgeon-tf (= 7.1.0-1+cuda10.2), libcudnn8 (= 8.0.0.145-1+cuda10.2), libopencv-samples (= 4.1.1-2-gd5a58aa75), nvidia-container-csv-cudnn (= 8.0.0.145-1+cuda10.2), python-libnvinfer-dev (= 7.1.0-1+cuda10.2), libnvinfer-plugin7 (= 7.1.0-1+cuda10.2), libvisionworks (= 1.6.0.501), libcudnn8-doc (= 8.0.0.145-1+cuda10.2), nvidia-container-toolkit (= 1.0.1-1), libnvinfer-dev (= 7.1.0-1+cuda10.2), nvidia-l4t-jetson-multimedia-api (>> 32.4-0), nvidia-l4t-jetson-multimedia-api (<< 32.5-0), libopencv-dev (= 4.1.1-2-gd5a58aa75), vpi-dev (= 0.2.0), vpi (= 0.2.0), libcudnn8-dev (= 8.0.0.145-1+cuda10.2), python3-libnvinfer (= 7.1.0-1+cuda10.2), python3-libnvinfer-dev (= 7.1.0-1+cuda10.2), opencv-licenses (= 4.1.1-2-gd5a58aa75), nvidia-container-csv-tensorrt (= 7.1.0.16-1+cuda10.2), libnvinfer7 (= 7.1.0-1+cuda10.2), libnvonnxparsers-dev (= 7.1.0-1+cuda10.2), uff-converter-tf (= 7.1.0-1+cuda10.2), nvidia-docker2 (= 2.2.0-1), libvisionworks-sfm (= 0.90.4.501), libnvidia-container-tools (= 0.9.0~beta.1), nvidia-container-runtime (= 3.1.0-1), python-libnvinfer (= 7.1.0-1+cuda10.2), libvisionworks-tracking (= 0.88.2.501)
Conflicts: cuda-command-line-tools-10-0, cuda-compiler-10-0, cuda-cublas-10-0, cuda-cublas-dev-10-0, cuda-cudart-10-0, cuda-cudart-dev-10-0, cuda-cufft-10-0, cuda-cufft-dev-10-0, cuda-cuobjdump-10-0, cuda-cupti-10-0, cuda-curand-10-0, cuda-curand-dev-10-0, cuda-cusolver-10-0, cuda-cusolver-dev-10-0, cuda-cusparse-10-0, cuda-cusparse-dev-10-0, cuda-documentation-10-0, cuda-driver-dev-10-0, cuda-gdb-10-0, cuda-gpu-library-advisor-10-0, cuda-libraries-10-0, cuda-libraries-dev-10-0, cuda-license-10-0, cuda-memcheck-10-0, cuda-misc-headers-10-0, cuda-npp-10-0, cuda-npp-dev-10-0, cuda-nsight-compute-addon-l4t-10-0, cuda-nvcc-10-0, cuda-nvdisasm-10-0, cuda-nvgraph-10-0, cuda-nvgraph-dev-10-0, cuda-nvml-dev-10-0, cuda-nvprof-10-0, cuda-nvprune-10-0, cuda-nvrtc-10-0, cuda-nvrtc-dev-10-0, cuda-nvtx-10-0, cuda-samples-10-0, cuda-toolkit-10-0, cuda-tools-10-0, libcudnn7, libcudnn7-dev, libcudnn7-doc, libnvinfer-plugin6, libnvinfer6, libnvonnxparsers6, libnvparsers6
Homepage: Autonomous Machines | NVIDIA Developer
Priority: standard
Section: metapackages
Filename: pool/main/n/nvidia-jetpack/nvidia-jetpack_4.4-b144_arm64.deb
Size: 30376
SHA256: 0556dbf2044a9d12e2c26e1a342033d4816f5d84f87dfe7a82916449249bb04b
SHA1: 38e788c5cd84b3e4bd956dcd7c9e018276e17b18
MD5sum: 0a96d0fa91591f10b7c86022d068970d
Description: NVIDIA Jetpack Meta Package
Description-md5: ad1462289bdbc54909ae109d1d32c0a8
`
Use-case is:
We use videoSource to capture 5 images from 5 different /dev/video{com-s} and save them locally using saveImageRGBA. Those 5 pictures are taken very 5 minutes. We let nvidia running throw all the night when we finished work. Next morning the error was shown in terminal :) “End of stream”
hello bryllatKS,
are you working with Xavier NX SD-card or eMMC version?
did you check the storage to confirm you’re still having enough space for saving capture frames?
could you please also narrow down the issue by putting camera to preview streams.
you may enable argus_camera application, and switch to “Multi-session” modes.
or,
you may enable 13_multi_camera, this multi_camera sample captures multiple cameras and composites them to one frame.
thanks