This commit is contained in:
Andrew Z 2023-01-05 09:33:35 -05:00
parent b887fa3f75
commit 654cbe4243
8 changed files with 1140 additions and 675 deletions

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@ -193099,6 +193099,7 @@
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{
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@ -265500,8 +265501,8 @@
"GameServers"
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"Network-Other",
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{
"Name": "NetBird-Client",
"Repository": "netbirdio/netbird",
"Registry": "https://hub.docker.com/r/netbirdio/netbird/",
"Network": "host",
"Shell": "bash",
"Privileged": "false",
"Support": "https://forums.unraid.net/topic/133241-support-netbird/",
"Project": "https://netbird.io",
"Overview": "NetBird is an open-source VPN management platform built on top of WireGuard\u00ae making it easy to create secure private networks for your organization or home.",
"TemplateURL": "https://raw.githubusercontent.com/dannymate/unraid-templates/master/netbird-client/netbird-client.xml",
"Icon": "https://raw.githubusercontent.com/dannymate/unraid-templates/master/icons/NetBird-Icon.png",
"ExtraParams": "--cap-add=NET_ADMIN",
"Config": [
{
"@attributes": {
"Name": "Setup Key",
"Target": "NB_SETUP_KEY",
"Default": "",
"Mode": "",
"Description": "Setup key obtained from the Management Service Dashboard (used to register peer)",
"Type": "Variable",
"Display": "always",
"Required": "true",
"Mask": "false"
},
"value": ""
},
{
"@attributes": {
"Name": "Management URL",
"Target": "NB_MANAGEMENT_URL",
"Default": "https://api.wiretrustee.com:33073",
"Mode": "",
"Description": "Management Service URL [http|https]://[host]:[port]",
"Type": "Variable",
"Display": "always",
"Required": "false",
"Mask": "false"
},
"value": "https://api.wiretrustee.com:33073"
},
{
"@attributes": {
"Name": "Appdata",
"Target": "/etc/netbird",
"Default": "",
"Mode": "rw",
"Description": "",
"Type": "Path",
"Display": "always",
"Required": "true",
"Mask": "false"
},
"value": "/mnt/user/appdata/netbird"
},
{
"@attributes": {
"Name": "Log File",
"Target": "NB_LOG_FILE",
"Default": "",
"Mode": "",
"Description": "",
"Type": "Variable",
"Display": "advanced",
"Required": "false",
"Mask": "false"
},
"value": "console"
},
{
"@attributes": {
"Name": "Log Level",
"Target": "NB_LOG_LEVEL",
"Default": "",
"Mode": "",
"Description": "",
"Type": "Variable",
"Display": "advanced",
"Required": "false",
"Mask": "false"
},
"value": "info"
},
{
"@attributes": {
"Name": "Admin Portal URL",
"Target": "NB_ADMIN_URL",
"Default": "https://app.netbird.io",
"Mode": "",
"Description": "Admin Panel URL [http|https]://[host]:[port]",
"Type": "Variable",
"Display": "advanced",
"Required": "false",
"Mask": "false"
},
"value": "https://app.netbird.io"
},
{
"@attributes": {
"Name": "Wireguard PreSharedKey",
"Target": "NB_PRESHARED_KEY",
"Default": "",
"Mode": "",
"Description": "Sets Wireguard PreSharedKey property. If set, then only peers that have the same key can communicate.",
"Type": "Variable",
"Display": "advanced",
"Required": "false",
"Mask": "true"
},
"value": ""
}
],
"Repo": "jimrummy101's Repository",
"templatePath": "/tmp/GitHub/AppFeed/templates/jimrummy101sRepository/netbird-client/netbird-client.xml",
"CategoryList": [
"Network-DNS",
"Network-Management",
"Network-VPN"
],
"downloads": 6914,
"LastUpdate": 1670937891,
"LastUpdateScan": 1672929212,
"FirstSeen": 1672929212
}
],
"repositories": {
@ -271196,6 +271322,14 @@
"Forum": "https://github.com/meisnate12/Plex-Meta-Manager/issues/new/choose",
"Discord": "https://discord.gg/NfH6mGFuAB",
"WebPage": "https://metamanager.wiki"
},
"jimrummy101's Repository": {
"url": "https://github.com/dannymate/unraid-templates",
"profile": "https://forums.unraid.net/profile/87501-jimrummy101/",
"bio": "FOSS and Self-Hosting fan hoping to bring interesting applications to UNRAID.",
"icon": "https://raw.githubusercontent.com/dannymate/unraid-templates/master/icons/avatar.png",
"Twitter": "https://twitter.com/slumbering_cat",
"WebPage": "https://github.com/dannymate"
}
},
"blacklisted": {

View File

@ -2539,5 +2539,6 @@
"jokobsk/pi.alert": 1672902244,
"blakeblackshear/frigate:0.12.0-beta1": 1672916675,
"nvcr.io/nvidia/tensorrt:22.07-py3": 1672916675,
"blakeblackshear/frigate:0.12.0-beta1-tensorrt": 1672923894
"blakeblackshear/frigate:0.12.0-beta1-tensorrt": 1672923894,
"netbirdio/netbird": 1672929212
}

View File

@ -3324,3 +3324,7 @@ Updating GitHub
Saving /tmp/GitHub/Squidly271.github.io/forum_post0
[master b887fa3f] Update
8 files changed, 767 insertions(+), 116 deletions(-)
To https://github.com/Squidly271/AppFeed.git
896c18b5..b887fa3f master -> master

View File

@ -75373,7 +75373,6 @@
],
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"trending": 0.65,
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@ -75403,6 +75402,7 @@
1167169
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@ -106237,7 +106237,6 @@
"Tools-Utilities",
"Plugins"
],
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},
{
@ -178270,7 +178269,7 @@
"Privileged": "true",
"Support": "https://forums.unraid.net/topic/98064-support-blakeblackshear-frigate/",
"Project": "https://frigate.video/",
"Overview": "A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras.\r\n\r\nUse of a Google Coral Accelerator is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead. There is another frigate app version 'frigate-nvidia' prepared to use a NVIDIA GPU as a detector\r\n\r\n- Tight integration with Home Assistant via a custom component\r\n- Designed to minimize resource use and maximize performance by only looking for objects when and where it is necessary\r\n- Leverages multiprocessing heavily with an emphasis on realtime over processing every frame\r\n- Uses a very low overhead motion detection to determine where to run object detection\r\n- Object detection with TensorFlow runs in separate processes for maximum FPS\r\n- Communicates over MQTT for easy integration into other systems\r\n- Records video with retention settings based on detected objects\r\n- 24/7 recording\r\n- Re-streaming via RTSP to reduce the number of connections to your camera\r\n- A dynamic combined camera view of all tracked cameras.\r\n\r\n[b]A config.yml file must exist in the config directory.[/b]\r\nSee the documentation for more details.",
"Overview": "A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras.\r\n\r\nUse of a Google Coral Accelerator is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead. There is another frigate app version 'frigate-nvidia' prepared to use a NVIDIA GPU as a detector\r\n\r\n- Tight integration with Home Assistant via a custom component\r\n- Designed to minimize resource use and maximize performance by only looking for objects when and where it is necessary\r\n- Leverages multiprocessing heavily with an emphasis on realtime over processing every frame\r\n- Uses a very low overhead motion detection to determine where to run object detection\r\n- Object detection with TensorFlow runs in separate processes for maximum FPS\r\n- Communicates over MQTT for easy integration into other systems\r\n- Records video with retention settings based on detected objects\r\n- 24/7 recording\r\n- Re-streaming via RTSP to reduce the number of connections to your camera\r\n- A dynamic combined camera view of all tracked cameras.\r\n\r\n[b]A config.yml file must exist in the config directory.[/b]\r\nSee the documentation for more details (https://deploy-preview-4055--frigate-docs.netlify.app/).",
"WebUI": "http://[IP]:[PORT:5000]",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/-/raw/main/yayitazale/frigate-beta.xml",
"Icon": "https://raw.githubusercontent.com/yayitazale/unraid-templates/main/frigate.png",
@ -178291,7 +178290,7 @@
"Required": "true",
"Mask": "false"
},
"value": "/mnt/user/appdata/frigate"
"value": "/mnt/user/appdata/frigate-beta"
},
{
"@attributes": {
@ -178458,41 +178457,33 @@
],
"downloads": 6501451,
"stars": 90,
"LastUpdate": 1672687885,
"LastUpdateScan": 1672916675,
"LastUpdate": 1672687885,
"FirstSeen": 1672916675
},
{
"TemplatePath": "/tmp/appFeed/templates/yayitazalesRepository/yayitazale/frigate-nvidia.xml",
"errors": [
"Premature end of data in tag Container line 2"
],
"LastUpdateScan": 1672470236,
"FirstSeen": null
},
{
"Name": "FrigateTensorrtModels",
"Repository": "nvcr.io/nvidia/tensorrt:22.07-py3",
"Registry": "https://registry.hub.docker.com/r/nvcr.io/nvidia/tensorrt",
"Name": "frigate-nvidia-beta",
"Repository": "blakeblackshear/frigate:0.12.0-beta1-tensorrt",
"Registry": "https://hub.docker.com/r/blakeblackshear/frigate/",
"Network": "bridge",
"Shell": "sh",
"Privileged": "false",
"Privileged": "true",
"Support": "https://forums.unraid.net/topic/98064-support-blakeblackshear-frigate/",
"Project": "https://frigate.video/",
"Overview": "It is a one-time use container to create the required models to use NVidia GPUs for object detection using the TensorRT libraries on Frigate APP. \r\n\r\nThe models used for TensorRT must be preprocessed on the same hardware platform that they will run on. This means that each user must run additional setup to generate these model files for the TensorRT library. A script is provided that will build several common models.\r\n\r\nDue to the size of the additional libraries, the NVidia TensorRT detector is only provided in the specific 'frigate-nvidia' app so that once this container is launched to create the TensorRT models, you will have to use that app to be able to use them.\r\n\r\nThe detector is designed to work with Yolo models for object detection. Specific models can be selected by passing an environment variable to the docker run command. Use the form 'yolov4-416,yolov4-tiny-416' to select one or more model names. The models available are shown here (https://deploy-preview-4055--frigate-docs.netlify.app/configuration/detectors#generate-models).",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/-/raw/main/yayitazale/FrigateTensorrtModels.xml",
"Icon": "https://gitlab.com/yayitazale/unraid-templates/-/raw/main/tensorrt.png",
"ExtraParams": "--gpus=all",
"PostArgs": "/tensorrt_models.sh",
"Overview": "A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras.\r\n\r\nNVidia GPUs may be used for object detection using the TensorRT libraries. Due to the size of the additional libraries, this detector is only provided in this app that is configured for use with an NVidia graphics card. This detector is designed to work with Yolo models for object detection.\r\n\r\nPlease read the docs to be sure that you meet with the Minimum Hardware Support (https://deploy-preview-4055--frigate-docs.netlify.app/configuration/detectors#nvidia-tensorrt-detector). \r\n\r\nBefore launching this container you must create the models using the 'tensorrt-models' app from community apps and following the defined steps there.\r\n\r\n- Tight integration with Home Assistant via a custom component\r\n- Designed to minimize resource use and maximize performance by only looking for objects when and where it is necessary\r\n- Leverages multiprocessing heavily with an emphasis on realtime over processing every frame\r\n- Uses a very low overhead motion detection to determine where to run object detection\r\n- Object detection with TensorFlow runs in separate processes for maximum FPS\r\n- Communicates over MQTT for easy integration into other systems\r\n- Records video with retention settings based on detected objects\r\n- 24/7 recording\r\n- Re-streaming via RTSP to reduce the number of connections to your camera\r\n- A dynamic combined camera view of all tracked cameras.\r\n\r\nA config.yml file and must exist in the config directory.\r\nA model file (.trt) and label file (.txt) muxt exist in the trt-models directory.\r\nSee the documentation for more details (https://deploy-preview-4055--frigate-docs.netlify.app/).",
"WebUI": "http://[IP]:[PORT:5000]",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/-/raw/main/yayitazale/frigate-nvidia-beta.xml",
"Icon": "https://raw.githubusercontent.com/yayitazale/unraid-templates/main/frigate.png",
"ExtraParams": "--gpus=all --shm-size=256mb --mount type=tmpfs,target=/tmp/cache,tmpfs-size=1000000000 --restart unless-stopped",
"DonateText": "If you like my work please consider Donating.",
"DonateLink": "https://paypal.me/JosebaEgiaLarrinaga",
"Requires": "To generate the model files with this container follow the steps:\r<br>\r<br>- Create a new folder to save the models (for example on /appdata/trt-models)\r<br>- Download the script and save it in the previusly creater path (https://raw.githubusercontent.com/blakeblackshear/frigate/dev/docker/tensorrt_models.sh)\r<br>- Open the unraid console and launch the following commad without quotes(pointing to your script path): 'chmod +x /mnt/user/appdata/trt-models/tensorrt_models.sh\r<br>- Then launch the container that will run the script and stop then container at the end. \r<br>\r<br>You can open the container logs page to track the model creation and/or catch any error.",
"Requires": "If you have multiple GPUs in your system with some allocated to VMs, you instead must delete &quot;--gpus all&quot; extra parameter and add &quot;--runtime=nvidia&quot; as extra parameter and set the NVIDIA_DRIVER_CAPABILITIES and NVIDIA_VISIBLE_DEVICES variables to only give the container access to selected GPUs.",
"Config": [
{
"@attributes": {
"Name": "TRT-models folder path",
"Target": "/tensorrt_models",
"Default": "/",
"Name": "Config Path",
"Target": "/config",
"Default": "",
"Mode": "rw",
"Description": "",
"Type": "Path",
@ -178500,13 +178491,125 @@
"Required": "true",
"Mask": "false"
},
"value": "/mnt/user/appdata/trt-models/"
"value": "/mnt/user/appdata/frigate-nvidia-beta"
},
{
"@attributes": {
"Name": "Script path",
"Target": "/tensorrt_models.sh",
"Name": "Media path",
"Target": "/media/frigate",
"Default": "",
"Mode": "rw",
"Description": "",
"Type": "Path",
"Display": "always",
"Required": "true",
"Mask": "false"
},
"value": "/mnt/user/Media/frigate-nvidia"
},
{
"@attributes": {
"Name": "HTTP port",
"Target": "5000",
"Default": "",
"Mode": "tcp",
"Description": "",
"Type": "Port",
"Display": "always",
"Required": "true",
"Mask": "false"
},
"value": "5000"
},
{
"@attributes": {
"Name": "RTSP port",
"Target": "8554",
"Default": "",
"Mode": "tcp",
"Description": "",
"Type": "Port",
"Display": "always",
"Required": "true",
"Mask": "false"
},
"value": "8554"
},
{
"@attributes": {
"Name": "Frigate RTSP Password",
"Target": "FRIGATE_RTSP_PASSWORD",
"Default": "",
"Mode": "",
"Description": "",
"Type": "Variable",
"Display": "always",
"Required": "true",
"Mask": "false"
},
"value": "enterpassword"
},
{
"@attributes": {
"Name": "Frigate+ API key",
"Target": "PLUS_API_KEY",
"Default": "",
"Mode": "",
"Description": "Optional: Enter the frigate+ API key or delete this if you are not using it",
"Type": "Variable",
"Display": "always",
"Required": "false",
"Mask": "false"
},
"value": "YOUR_PLUS_API_KEY"
},
{
"@attributes": {
"Name": "WebRTC port",
"Target": "8555",
"Default": "",
"Mode": "tcp",
"Description": "If you are not going to use WebRCT you can delete all the WebRTC entrys",
"Type": "Port",
"Display": "always",
"Required": "false",
"Mask": "false"
},
"value": "8555"
},
{
"@attributes": {
"Name": "WebRTC go2rtc config file path",
"Target": "/config/frigate-go2rtc.yaml",
"Default": "",
"Mode": "ro",
"Description": "If you are goint to use WebRTC you must create this file following the instructions on the docs",
"Type": "Path",
"Display": "always",
"Required": "false",
"Mask": "false"
},
"value": "/mnt/user/appdata/frigatebeta/frigate-go2rtc.yaml"
},
{
"@attributes": {
"Name": "WebRTC go2rtc server port",
"Target": "1984",
"Default": "",
"Mode": "tcp",
"Description": "For Home Assistant WebRTC integration",
"Type": "Port",
"Display": "always",
"Required": "false",
"Mask": "false"
},
"value": "1984"
},
{
"@attributes": {
"Name": "TRT-Models path",
"Target": "/trt-models",
"Default": "/mnt/user/appdata/trt-models",
"Mode": "ro",
"Description": "",
"Type": "Path",
@ -178514,31 +178617,36 @@
"Required": "true",
"Mask": "false"
},
"value": "/mnt/user/appdata/trt-models/tensorrt_models.sh"
"value": "/mnt/user/appdata/trt-models"
},
{
"@attributes": {
"Name": "Yolo Models",
"Target": "YOLO_MODELS",
"Default": "yolov4-tiny-288,yolov4-tiny-416,yolov7-tiny-416",
"Mode": "",
"Description": "If you want to use specific models you must fill this. Otherwise delete this entry and default models will be used (yolov4-tiny-288,yolov4-tiny-416,yolov7-tiny-416)",
"Type": "Variable",
"Display": "always",
"Required": "false",
"Name": "Localtime",
"Target": "/etc/localtime",
"Default": "",
"Mode": "rw",
"Description": "",
"Type": "Path",
"Display": "advanced-hide",
"Required": "true",
"Mask": "false"
},
"value": "yolov4-tiny-288,yolov4-tiny-416,yolov7-tiny-416"
"value": "/etc/localtime"
}
],
"Repo": "yayitazale's Repository",
"Beta": "true",
"templatePath": "/tmp/GitHub/AppFeed/templates/yayitazalesRepository/yayitazale/FrigateTensorrtModels.xml",
"CAComment": "This template is set up to run as Privileged. This is a possible security risk and usually does not need to be enabled. Note that some applications require privileged in order to operate correctly",
"templatePath": "/tmp/GitHub/AppFeed/templates/yayitazalesRepository/yayitazale/frigate-nvidia-beta.xml",
"CategoryList": [
"Other"
"HomeAutomation",
"Security"
],
"LastUpdateScan": 1672916675,
"FirstSeen": 1672916675
"downloads": 6501803,
"stars": 90,
"LastUpdate": 1672687885,
"LastUpdateScan": 1672923894,
"FirstSeen": 1672923894
},
{
"Name": "Grafana-Image-Renderer",
@ -178678,6 +178786,77 @@
"LastUpdateScan": 1671714255,
"FirstSeen": 1663920216
},
{
"Name": "tensorrt-models",
"Repository": "nvcr.io/nvidia/tensorrt:22.07-py3",
"Registry": "https://registry.hub.docker.com/r/nvcr.io/nvidia/tensorrt",
"Network": "bridge",
"Shell": "sh",
"Privileged": "false",
"Support": "https://forums.unraid.net/topic/98064-support-blakeblackshear-frigate/",
"Project": "https://frigate.video/",
"Overview": "It is a one-time use container to create the required models to use NVidia GPUs for object detection using the TensorRT libraries on Frigate APP. \r\n\r\nThe models used for TensorRT must be preprocessed on the same hardware platform that they will run on. This means that each user must run additional setup to generate these model files for the TensorRT library. A script is provided that will build several common models.\r\n\r\nDue to the size of the additional libraries, the NVidia TensorRT detector is only provided in the specific 'frigate-nvidia' app so that once this container is launched to create the TensorRT models, you will have to use that app to be able to use them.\r\n\r\nThe detector is designed to work with Yolo models for object detection. Specific models can be selected by passing an environment variable to the docker run command. Use the form 'yolov4-416,yolov4-tiny-416' to select one or more model names. The models available are shown here (https://deploy-preview-4055--frigate-docs.netlify.app/configuration/detectors#generate-models).",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/-/raw/main/yayitazale/tensorrt-models.xml",
"Icon": "https://gitlab.com/yayitazale/unraid-templates/-/raw/main/tensorrt.png",
"ExtraParams": "--gpus=all",
"PostArgs": "/tensorrt_models.sh",
"DonateText": "If you like my work please consider Donating.",
"DonateLink": "https://paypal.me/JosebaEgiaLarrinaga",
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