Hellomynameisleo

I came home with my unraid server unresponsive, so I have rebooted my computer and was met with the picture below. I've tried inserting the usb in a 2.0 slot behind the motherboard and in front of the case IO but the results are still the same. I am thinking its my USB that has failed after a year of 24/7 use. I use Unraid connect which has a backup from 2 days ago, how would I go about installing the same config and everything on a new USB drive? Do I have to move some files from the old usb to new usb?

Thanks I given it a try and extracted the storcli64 from \Linux-PPC\LittleEndian\ to the tmp folder and did the "chmod 777 storcli64", then "./storcli64 /c0 show temperature" but get an error saying "bash: ./storcli64: cannot execute binary file: Exec format error" any ideas?

In unraid how do I get the temperature sensor data for the HBA 9300-16I? It has 2 SAS3008 controllers in it and when I touch the heatsink is it really hot even though I only got 2 HDD connected

updated to latest version of unraid and nvidia drivers, still doesn't trigger events even though I can see it working on the GPU load for the detector. Might be a frigate bug in this version. edit: Got it working now, had to add input_tensor and input_pixel_format model: path: /config/model_cache/tensorrt/yolov7x-640.trt input_tensor: nchw input_pixel_format: rgb width: 640 height: 640

thinking its my unraid gpu driver version v530.41.03, that I need to update, but can't because I need to update my unraid which is still on 6.12.0-rc3. Feel like unraid will brick itself and the docker containers if I update the OS

okay got my gpu working in frigate but for some reason the event detection is not working with the tensorrt, I see no events being triggered any ideas why? My config below mqtt: enabled: False detectors: tensorrt: type: tensorrt device: 0 model: path: /config/model_cache/tensorrt/yolov7x-640.trt width: 640 height: 640 go2rtc: streams: bedroom: - http://192.168.4.183/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=admin&password={FRIGATE_RTSP_PASSWORD} cameras: bedroom: enabled: True ffmpeg: inputs: - path: http://192.168.4.183/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=admin&password={FRIGATE_RTSP_PASSWORD} input_args: preset-http-reolink roles: - record - path: http://192.168.4.183/flv?port=1935&app=bcs&stream=channel0_sub.bcs&user=admin&password={FRIGATE_RTSP_PASSWORD} input_args: preset-http-reolink roles: - detect detect: enabled: True width: 640 height: 480 fps: 7 record: enabled: True retain: days: 10 mode: all events: retain: mode: motion default: 20 birdseye: enabled: True mode: continuous restream: False width: 640 height: 480 quality: 12 ffmpeg: hwaccel_args: preset-nvidia-h264 output_args: record: -f segment -segment_time 10 -segment_format mp4 -reset_timestamps 1 -strftime 1 -g 300 -c:v hevc_nvenc -preset p7 -tune hq -level 6.2 -tier high -c:a copy and the logs doesn't show any errors: 2024-02-10 13:41:15.567309349 [INFO] Preparing Frigate... 2024-02-10 13:41:15.579936723 [INFO] Starting Frigate... 2024-02-10 13:41:17.224436812 [2024-02-10 13:41:17] frigate.app INFO : Starting Frigate (0.13.1-34fb1c2) 2024-02-10 13:41:18.796348475 [2024-02-10 13:41:18] peewee_migrate.logs INFO : Starting migrations 2024-02-10 13:41:18.805579722 [2024-02-10 13:41:18] peewee_migrate.logs INFO : There is nothing to migrate 2024-02-10 13:41:18.813163234 [2024-02-10 13:41:18] frigate.app INFO : Recording process started: 742 2024-02-10 13:41:18.816235491 [2024-02-10 13:41:18] frigate.app INFO : go2rtc process pid: 99 2024-02-10 13:41:18.841004447 [2024-02-10 13:41:18] frigate.app INFO : Output process started: 753 2024-02-10 13:41:18.862050587 [2024-02-10 13:41:18] detector.tensorrt INFO : Starting detection process: 751 2024-02-10 13:41:18.941615303 [2024-02-10 13:41:18] frigate.app INFO : Camera processor started for bedroom: 766 2024-02-10 13:41:18.943448568 [2024-02-10 13:41:18] frigate.app INFO : Capture process started for bedroom: 768 2024-02-10 13:41:20.430493881 [2024-02-10 13:41:20] frigate.detectors.plugins.tensorrt INFO : Loaded engine size: 317 MiB 2024-02-10 13:41:24.024620445 [2024-02-10 13:41:24] frigate.detectors.plugins.tensorrt INFO : [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +772, GPU +192, now: CPU 1731, GPU 1287 (MiB) 2024-02-10 13:41:24.407048625 [2024-02-10 13:41:24] frigate.detectors.plugins.tensorrt INFO : [MemUsageChange] Init cuDNN: CPU +235, GPU +52, now: CPU 1966, GPU 1339 (MiB) 2024-02-10 13:41:24.409465278 [2024-02-10 13:41:24] frigate.detectors.plugins.tensorrt INFO : [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +0, GPU +320, now: CPU 0, GPU 320 (MiB) 2024-02-10 13:41:24.422489353 [2024-02-10 13:41:24] frigate.detectors.plugins.tensorrt INFO : [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 1649, GPU 1335 (MiB) 2024-02-10 13:41:24.422599790 [2024-02-10 13:41:24] frigate.detectors.plugins.tensorrt INFO : [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 1649, GPU 1343 (MiB) 2024-02-10 13:41:24.426641410 [2024-02-10 13:41:24] frigate.detectors.plugins.tensorrt INFO : [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +222, now: CPU 0, GPU 542 (MiB) 2024-02-10 13:41:24.426747591 [2024-02-10 13:41:24] frigate.detectors.plugins.tensorrt WARNING : CUDA lazy loading is not enabled. Enabling it can significantly reduce device memory usage. See `CUDA_MODULE_LOADING` in https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#env-vars

No its not being used for anything, my GPU settings was working before the frigate docker update so not sure why its not working now

any idea why my frigate container won't start? I'm trying to add my RTX 2060 GPU with the drivers already installed, and --runtime=nvidia set in extra paramaters with gpu id set too, I get the error docker: Error response from daemon: failed to create shim task: OCI runtime create failed: runc create failed: unable to start container process: error during container init: error running hook #1: error running hook: exit status 1, stdout: , stderr: Auto-detected mode as 'legacy' nvidia-container-cli: initialization error: open failed: /proc/sys/kernel/overflowuid: permission denied: unknown.

So I have my wireguard set up as NAT = yes, host access to custom network = no, so I can't use my vpn peer client to access any docker containers on custom network br0. I need to set host access to custom network to yes but then the wireguard peer won't have access to LAN devices without static routes set on router. My router doesn't have the setting for it, what are my options to make this work? would hosting wireguard on another LAN device instead work?

I have seen many reverse proxy guides, but it seems they all cover for remoting into your docker containers exposed to the internet then securing them with reverse proxy authentication. This seems insecure since if someone got access to your LAN they can bypass your reverse proxy authentication and directly access the docker containers using their IP:port as your docker containers are exposed to the host's LAN network. Is there guides for when you already have home VPN access to your LAN remotely using unraid's own wireguard, and then securing your docker containers behind a reverse proxy authentication? But having your docker containers not exposed to your LAN network, only an internal docker network. This would be suitable for when you are sharing internet connection with other untrust users on the LAN.

any idea why I am getting this error when trying to query the log dates? I have setup a new pihole, just modified the http and https ports to 6000

I have a 10GBe network card that is ETH1 (192.168.11.1) and have enabled bridging as BR1, and have ticked the checkbox in the docker settings for BR1 to be enabled but it is not shown as an option for docker containers. The 10GBe network card is directly attached to my windows pc (192.168.11.2) using a DAC which also has the same network card. Any ideas what I could be doing wrong? I accidentially changed something and now its no longer showing up as an option but it was before I changed a setting. network settings docker settings container settings

Yes its mapped to frigate, I've stopped the frigate container and started the Tensorrt-models docker and it the same error that pops up. Is there something else I am missing?

I am trying to get started with the Tensorrt-models docker container and have set it up as below with the script, have did the "chmod +x /mnt/user/appdata/trt-models/tensorrt_models.sh" and when running the container I get the error below: /opt/nvidia/nvidia_entrypoint.sh: /tensorrt_models.sh: /bin/bash^M: bad interpreter: No such file or directory /opt/nvidia/nvidia_entrypoint.sh: line 49: /tensorrt_models.sh: Success any ideas what I am doing wrong?

unraid uses fuse for user shares on the array and its very slow espcially at listing directories in windows with 1000s of small files. Would it be a good or bad idea to instead smb all my unraid disk shares to my Windows pc which bypasses fuse then use rclone's union on my windows pc to merge all the mapped disk shares? It will be like doing what fuse does but instead on the windows computer for improved performance gains. Any thoughts on doing this?