Giters

stereolabs / zed-docker

Docker images for the ZED SDK

Home Page:https://hub.docker.com/r/stereolabs/zed/

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

Docker SVO recording fails using hardware encoding (H264/H265)

timongentzsch opened this issue · comments

commented

Preliminary Checks

  • This issue is not a duplicate. Before opening a new issue, please search existing issues.
  • This issue is not a question, feature request, or anything other than a bug report directly related to this project.

Description

When starting an SVO recording in a Docker container I get an Segmentation fault (core dumped) error. All other functions of the SDK (depth sensing, ground plane estimation, object detection, etc.) work without problems. Even recording in LOSSLESS compression mode works, so the problem is most likely due to the use of NVENC.

Since I'm not using the official Jetpack image, but a yocto build with the BSP layer for NVIDIA Jetson, it may well be that certain libraries are in different places. For example, I had to set up this symlink: ln -s /usr/lib/aarch64-linux-gnu/libv4l/plugins/libv4l2_nvvidconv_wrapper.so /usr/lib/aarch64-linux-gnu/libv4l/plugins-wrapped/libv4l2_nvvidconv.so beforehand so that the corresponding library could be found. However, since I do not receive any further information besides the SEGFAULT error message, I do not know exactly where the problem is. Is there a way to further debug this?

I already ran the ZED_Diagnostic tool and got following result:

ZED Diagnotic File 
{
    "Camera Test": {
        "ZEDCount": 1,
        "camera": {
            "Device ID": 0,
            "Firmware": 1523,
            "Init Output": "OK",
            "Model": "ZED 2",
            "Serial Number": 22557364,
            "valid": [
                "<b>Camera: </b>ZED 2",
                "<b>Firmware: </b>1523"
            ]
        },
        "resolutions": {
            "HD1080@15": {
                "fps (input)": 15,
                "fps (output)": 15,
                "height (input)": 1080,
                "height (output)": 1080,
                "initialization": "OK",
                "status": true,
                "width (input)": 1920,
                "width (output)": 1920
            },
            "HD1080@30": {
                "fps (input)": 30,
                "fps (output)": 30,
                "height (input)": 1080,
                "height (output)": 1080,
                "initialization": "OK",
                "status": true,
                "width (input)": 1920,
                "width (output)": 1920
            },
            "HD2K@15": {
                "fps (input)": 15,
                "fps (output)": 15,
                "height (input)": 1242,
                "height (output)": 1242,
                "initialization": "OK",
                "status": true,
                "width (input)": 2208,
                "width (output)": 2208
            },
            "HD720@15": {
                "fps (input)": 15,
                "fps (output)": 15,
                "height (input)": 720,
                "height (output)": 720,
                "initialization": "OK",
                "status": true,
                "width (input)": 1280,
                "width (output)": 1280
            },
            "HD720@30": {
                "fps (input)": 30,
                "fps (output)": 30,
                "height (input)": 720,
                "height (output)": 720,
                "initialization": "OK",
                "status": true,
                "width (input)": 1280,
                "width (output)": 1280
            },
            "HD720@60": {
                "dropCount": 3,
                "fps (input)": 60,
                "fps (output)": 60,
                "height (input)": 720,
                "height (output)": 720,
                "imageCount": 497,
                "initialization": "OK",
                "status": true,
                "tearingCount": 0,
                "width (input)": 1280,
                "width (output)": 1280
            },
            "VGA@100": {
                "fps (input)": 100,
                "fps (output)": 100,
                "height (input)": 376,
                "height (output)": 376,
                "initialization": "OK",
                "status": true,
                "width (input)": 672,
                "width (output)": 672
            },
            "VGA@15": {
                "fps (input)": 15,
                "fps (output)": 15,
                "height (input)": 376,
                "height (output)": 376,
                "initialization": "OK",
                "status": true,
                "width (input)": 672,
                "width (output)": 672
            },
            "VGA@30": {
                "fps (input)": 30,
                "fps (output)": 30,
                "height (input)": 376,
                "height (output)": 376,
                "initialization": "OK",
                "status": true,
                "width (input)": 672,
                "width (output)": 672
            },
            "VGA@60": {
                "fps (input)": 60,
                "fps (output)": 60,
                "height (input)": 376,
                "height (output)": 376,
                "initialization": "OK",
                "status": true,
                "width (input)": 672,
                "width (output)": 672
            }
        },
        "sensors": {
            "Firmware": 776,
            "Init Output": "OK",
            "Model": "ZED 2 (MCU)",
            "Serial Number": 22557364
        }
    },
    "Graphics Card": {
        "deviceCount": 1,
        "deviceDriverVersion": 10020,
        "devices": [
            {
                "arch": "Volta",
                "computeCapability": "7.2",
                "cores": 768,
                "name": "Xavier",
                "totalMemoryBytes": "8148172800",
                "totalMemoryMB": 7770.703125
            }
        ],
        "initResult": 0,
        "valid": [
            "<b>Graphics card: </b> Xavier"
        ]
    },
    "Processor": {
        "OS": "Ubuntu 18.04.5 LTS ",
        "avxSupported": false,
        "coreCount": "6",
        "cpu": " ARMv8 Processor rev 0 (v8l)",
        "datetime": "2022-01-31 07:39:35",
        "hyperThreading": "0",
        "motherboard": ", ",
        "ramCapacity": "8.148173",
        "ramUsage": "",
        "ramUsed": "5.589459",
        "threadCount": "6",
        "valid": [
            "<b>Processor: </b>  ARMv8 Processor rev 0 (v8l)"
        ]
    },
    "USB": {
        "CorruptedFirmware": false,
        "MCUDetected": true,
        "USBList": [
            {
                "USBMode": 3,
                "USB_path": "/3/3",
                "bDescriptorType": 1,
                "bDeviceProtocol": 1,
                "bLength": 18,
                "bMaxPacketSize0": 9,
                "bNumConfigurations": 1,
                "bcdDevice": "1.0",
                "bcdUSB": "3.0",
                "bcdUSBClass": 239,
                "bcdUSBSubClass": 2,
                "busNumber": 2,
                "device": "ZED2",
                "iManufacturer": 1,
                "iProduct": 2,
                "iSerial": 0,
                "idProduct": "0xf780",
                "idVendor": "0x2b03"
            },
            {
                "USB_path": "/3",
                "idProduct": "0x0489",
                "idVendor": "0x0bda"
            },
            {
                "USB_path": "/3",
                "idProduct": "0x3549",
                "idVendor": "0x13d3"
            },
            {
                "USBMode": 2,
                "USB_path": "/2/3/2",
                "bDescriptorType": 1,
                "bDeviceProtocol": 0,
                "bLength": 18,
                "bMaxPacketSize0": 64,
                "bNumConfigurations": 1,
                "bcdDevice": "3.8",
                "bcdUSB": "2.0",
                "bcdUSBClass": 0,
                "bcdUSBSubClass": 0,
                "busNumber": 1,
                "device": "ZED2 MCU",
                "iManufacturer": 1,
                "iProduct": 2,
                "iSerial": 3,
                "idProduct": "0xf781",
                "idVendor": "0x2b03"
            },
            {
                "USB_path": "/2/3",
                "idProduct": "0x2512",
                "idVendor": "0x0424"
            },
            {
                "USB_path": "/2",
                "idProduct": "0x5489",
                "idVendor": "0x0bda"
            }
        ],
        "USBMode": 3,
        "ZED Camera Module Detected": 63360,
        "ZED MCU Module Detected": 63361,
        "ZEDDetected": true,
        "valid": [
            "<b>USB Bandwidth: </b> OK"
        ]
    },
    "ZED SDK": {
        "CUDA Toolkit version": "V10.2.300 -->located in /usr/local/cuda-10.2/bin/nvcc",
        "CUDA loading": false,
        "ZED SDK Version (Diag)": "3.6.4",
        "ZED SDK Version (RT)": "3.6.4",
        "ai": {
            "checkAI": true,
            "cudaVersion": 10020,
            "cudnnCudartVersion": 10020,
            "cudnnVersion": 8201,
            "cudnnVersionExpected": 8000,
            "tensorVersion": 8001
        },
        "binFiles": [
            "libsl_ai.so",
            "libsl_zed.so",
            "libsl_zed_static.a"
        ],
        "resourcesFiles": [
        ],
        "resourcesFilesExpected": [
            "objects_performance_2.1"
        ],
        "valid": [
            "<b>ZED SDK version:</b> 3.6.4",
            "<b>CUDA version:</b> V10.2.300"
        ]
    }
}

Steps to Reproduce

Since its a custom Image its hard to give clear steps to reproduce. However i linked the image features in the Environment section.
Regarding the docker image itself: I used the recording example from stereolabs/zed:3.6-py-devel-jetson-jp4.6

Expected Result

.svo file in specified path

Actual Result

Segmentation fault (core dumped)

ZED Camera model

ZED2

Environment

Yocto Image based on L4T release r32.6.1 (Jetpack 4.6) with following image features: `nvidia-docker cuda-toolkit cuda-driver cuda-target-environment tensorrt-core tensorrt-plugins-prebuilt python3-tensorrt v4l-utils libv4l` Is there something Im missing out?

Anything else?

No response

commented

Hi @timongentzsch
we noted your bug report and we are going to analyze it as soon as possible.

commented

I just check which libs were actually used by a simple program recording an SVO file on a Xavier NX JP4.6.1, here is the result:

/lib/aarch64-linux-gnu/libuuid.so.1.3.0
/lib/aarch64-linux-gnu/libblkid.so.1.1.0
/lib/aarch64-linux-gnu/libmount.so.1.1.0
/lib/aarch64-linux-gnu/libmount.so.1.1.0
/lib/aarch64-linux-gnu/libresolv-2.27.so
/lib/aarch64-linux-gnu/libselinux.so.1
/usr/lib/aarch64-linux-gnu/libgio-2.0.so.0.5600.4
/usr/lib/aarch64-linux-gnu/libgmodule-2.0.so.0.5600.4
/lib/aarch64-linux-gnu/libpcre.so.3.13.3
/usr/lib/aarch64-linux-gnu/tegra/libnvdla_runtime.so
/usr/lib/aarch64-linux-gnu/libglib-2.0.so.0.5600.4
/usr/lib/aarch64-linux-gnu/libgobject-2.0.so.0.5600.4
/usr/lib/aarch64-linux-gnu/tegra/libnvmmlite_image.so
/usr/lib/aarch64-linux-gnu/tegra/libnvparser.so
/usr/lib/aarch64-linux-gnu/tegra/libnvtnr.so
/usr/lib/aarch64-linux-gnu/tegra/libnvddk_2d_v2.so
/usr/lib/aarch64-linux-gnu/tegra/libnvmedia.so
/usr/lib/aarch64-linux-gnu/tegra/libnvavp.so
/usr/lib/aarch64-linux-gnu/tegra/libnvmmlite_utils.so
/usr/lib/aarch64-linux-gnu/tegra/libnvmmlite.so
/usr/lib/aarch64-linux-gnu/tegra/libnvmm_utils.so
/usr/lib/aarch64-linux-gnu/tegra/libnvbufsurface.so.1.0.0
/usr/lib/aarch64-linux-gnu/tegra/libnvtvmr.so
/usr/lib/aarch64-linux-gnu/tegra/libnvmmlite_video.so
/usr/lib/aarch64-linux-gnu/tegra/libtegrav4l2.so
/usr/lib/aarch64-linux-gnu/tegra/libv4l2_nvvideocodec.so
/usr/lib/aarch64-linux-gnu/gconv/UTF-16.so
/usr/lib/aarch64-linux-gnu/tegra/libnvidia-eglcore.so.32.6.1
/usr/lib/aarch64-linux-gnu/libffi.so.6.0.4
/usr/lib/aarch64-linux-gnu/libwayland-server.so.0.1.0
/usr/lib/aarch64-linux-gnu/libwayland-client.so.0.3.0
/usr/lib/aarch64-linux-gnu/tegra/libnvidia-egl-wayland.so
/usr/lib/aarch64-linux-gnu/libdrm.so.2.4.0
/usr/lib/aarch64-linux-gnu/tegra/libnvimp.so
/usr/lib/aarch64-linux-gnu/tegra/libnvdc.so
/usr/lib/aarch64-linux-gnu/tegra/libnvll.so
/usr/lib/aarch64-linux-gnu/tegra/libdrm.so.2
/usr/lib/aarch64-linux-gnu/tegra/libnvidia-rmapi-tegra.so.32.6.1
/usr/lib/aarch64-linux-gnu/tegra/libnvidia-glsi.so.32.6.1
/usr/lib/aarch64-linux-gnu/tegra-egl/libEGL_nvidia.so.0
/lib/aarch64-linux-gnu/libbsd.so.0.8.7
/usr/lib/aarch64-linux-gnu/libGLdispatch.so.0.0.0
/usr/lib/aarch64-linux-gnu/libXdmcp.so.6.0.0
/usr/lib/aarch64-linux-gnu/libXau.so.6.0.0
/usr/lib/aarch64-linux-gnu/tegra/libnvos.so
/usr/lib/aarch64-linux-gnu/tegra/libnvbuf_fdmap.so.1.0.0
/usr/lib/aarch64-linux-gnu/tegra/libnvddk_vic.so
/usr/lib/aarch64-linux-gnu/libEGL.so.1.0.0
/usr/lib/aarch64-linux-gnu/libxcb.so.1.1.0
/usr/lib/aarch64-linux-gnu/tegra/libnvv4lconvert.so
/lib/aarch64-linux-gnu/libudev.so.1.6.9
/usr/lib/aarch64-linux-gnu/tegra/libnvidia-fatbinaryloader.so.440.18
/usr/lib/aarch64-linux-gnu/tegra/libnvrm_graphics.so
/usr/lib/aarch64-linux-gnu/tegra/libnvrm.so
/usr/lib/aarch64-linux-gnu/tegra/libnvrm_gpu.so
/usr/lib/aarch64-linux-gnu/libgomp.so.1.0.0
/lib/aarch64-linux-gnu/libm-2.27.so
/usr/lib/aarch64-linux-gnu/tegra/libnvbuf_utils.so.1.0.0
/usr/lib/aarch64-linux-gnu/libX11.so.6.3.0
/usr/lib/aarch64-linux-gnu/tegra/libnvv4l2.so
/lib/aarch64-linux-gnu/libusb-1.0.so.0.1.0
/usr/lib/aarch64-linux-gnu/libturbojpeg.so.0.1.0
/usr/lib/aarch64-linux-gnu/libjpeg.so.8.1.2
/lib/aarch64-linux-gnu/libz.so.1.2.11
/usr/lib/aarch64-linux-gnu/libpng16.so.16.34.0
/usr/lib/aarch64-linux-gnu/tegra/libcuda.so.1.1
/lib/aarch64-linux-gnu/librt-2.27.so
/lib/aarch64-linux-gnu/libdl-2.27.so
/lib/aarch64-linux-gnu/libpthread-2.27.so
/lib/aarch64-linux-gnu/libc-2.27.so
/lib/aarch64-linux-gnu/libgcc_s.so.1
/usr/lib/aarch64-linux-gnu/libstdc++.so.6.0.25
/usr/local/zed/lib/libsl_zed.so
/lib/aarch64-linux-gnu/ld-2.27.so

I got the list by reading the /proc/<PID>/maps file, so it should also include the dynamically loaded ones. If they're all at the same location, I guess it should work

commented

thanks @adujardin!
i solved it by manually passing the libv4l library in the docker via -v /usr/lib/libv4l:/usr/lib/aarch64-linux-gnu/libv4l for now. (Probably makes sense to edit the container-runtime-csv in the libv4l layer on the yocto side)