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Andrew Z 2022-11-29 08:58:00 -05:00
parent e08a2e977c
commit 00c6abaea5
4 changed files with 21 additions and 21 deletions
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2
applicationFeed-lastUpdated.json
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@ -1,3 +1,3 @@
{
"last_updated_timestamp": 1669729612
"last_updated_timestamp": 1669730277
}

8
applicationFeed-raw.json
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@ -175560,7 +175560,7 @@
"Overview": "HDHomeRun emulator for Plex/Jellyfin/Emby DVR to connect to Tvheadend.[br][br]\n To run this container, [b]first create a config.yml on the config folder[/b] with the following lines (changing to the IPs, ports and tuner count of your system)[br][br]\n tvheadend_url: http://user:pas@X.X.X.X:9981[br][br]\n antennas_url: http://X.X.X.X:5004[br][br]\n tuner_count: 4",
"Requires": "<br>&nbsp;&nbsp;&nbsp;&nbsp;To run this container, first create a config.yml on the config folder with the following lines (changing to the IPs, ports and tuner count of your system)<br>&nbsp;&nbsp;&nbsp;&nbsp;tvheadend_url: http://user:pas@X.X.X.X:9981<br>&nbsp;&nbsp;&nbsp;&nbsp;antennas_url: http://X.X.X.X:5004<br>&nbsp;&nbsp;&nbsp;&nbsp;tuner_count: 4 <br> ",
"WebUI": "http://[IP]:[PORT:5004]",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/main/yayitazale/antennas.xml",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/-/raw/main/yayitazale/antennas.xml",
"Icon": "https://raw.githubusercontent.com/yayitazale/unraid-templates/main/antennas.png",
"Networking": {
"Mode": "bridge"
@ -175648,7 +175648,7 @@
"Project": "https://docs.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.\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 RTMP to reduce the number of connections to your camera\r\n\r\n[b]A config.yml file must exist in the config directory.[/b]\r\nSee the documentation for more details.",
"WebUI": "http://[IP]:[PORT:5000]",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/main/yayitazale/frigate.xml",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/-/raw/main/yayitazale/frigate.xml",
"Icon": "https://raw.githubusercontent.com/yayitazale/unraid-templates/main/frigate.png",
"ExtraParams": "--shm-size=256mb --mount type=tmpfs,target=/tmp/cache,tmpfs-size=1000000000",
"Requires": "Note: If you are using a PCI Coral instead of a USB one, you must install first the needed drivers going to the CA APP and searching for Coral-Driver (thanks to @ich777)\r<br>\r<br>If you want to use a nvidia card to image decoding, you must add the &quot;--gpus all&quot; extra parameter. If you have multiple GPUs in your system with some allocated to VMs, you instead must 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.",
@ -175817,7 +175817,7 @@
"Support": "https://forums.unraid.net/topic/118806-support-grafana-grafana-image-renderer/",
"Project": "https://github.com/grafana/grafana-image-renderer/blob/master/docs/remote_rendering_using_docker.md",
"Overview": "A Grafana remote image renderer that handles rendering panels &amp; dashboards to PNGs using headless chrome.\r\n[br][br]\r\nRead Grafana Image Renderer documentation and see usage instructions at [b][u][a \"https://github.com/grafana/grafana-image-renderer/blob/master/docs/remote_rendering_using_docker.md\"]projects page[/a][/b][/u].\r\n[br][br]\r\nIn order to use this as a plugin of your Grafana docker instance you [b]must[/b] add this enviromental arguments to that container:\r\n[br][br]\r\n- GF_RENDERING_SERVER_URL: http://renderer-ip:8081/render[br]\r\n- GF_RENDERING_CALLBACK_URL: http://grafana-ip:3000/\r\n[br][br]\r\nChange the IP (and the ports) to suit your configuration.",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/main/yayitazale/grafana-image-renderer.xml",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/-/raw/main/yayitazale/grafana-image-renderer.xml",
"Icon": "https://github.com/atribe/unRAID-docker/raw/master/icons/grafana.png",
"Networking": {
"Mode": "bridge"
@ -175888,7 +175888,7 @@
"Support": "https://forums.unraid.net/topic/128633-support-steffo99-greed/",
"Project": "https://github.com/Steffo99/greed",
"Overview": "A customizable, multilanguage Telegram shop bot with Telegram Payments support!\r\n\r\nPlease refer to docs to learn how to activate it and how to use it. This container is not working by itself. Brief installing instructions:\r\n\r\n1. Donwload and run the container\r\n2. Edit the configuration file *config.toml* that was created in the *config* directory, adding your bot and payment tokens to it.\r\n3. Optional: customize the files in the strings folder for custom messages.\r\n4. Start the bot using the console of the container and the following command: *python -OO core.py*\r\n5. Open Telegram, and send a */start* command to your bot to be automatically promoted to \ud83d\udcbc Manager.\r\n6. Stop the bot by pressing Ctrl+C.\r\n7. Restart the container.",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/main/yayitazale/greed.xml",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/-/raw/main/yayitazale/greed.xml",
"Icon": "https://raw.githubusercontent.com/yayitazale/unraid-templates/main/greed.png",
"DonateText": "Donate",
"DonateLink": "https://ko-fi.com/steffo",

12
applicationFeed.json
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@ -1,7 +1,7 @@
{
"apps": 1897,
"last_updated_timestamp": 1669729612,
"last_updated": "2022-11-29 08:46",
"last_updated_timestamp": 1669730277,
"last_updated": "2022-11-29 08:57",
"categories": [
{
"Cat": "Backup:",
@ -175722,7 +175722,7 @@
"Overview": "HDHomeRun emulator for Plex/Jellyfin/Emby DVR to connect to Tvheadend.[br][br]\n To run this container, [b]first create a config.yml on the config folder[/b] with the following lines (changing to the IPs, ports and tuner count of your system)[br][br]\n tvheadend_url: http://user:pas@X.X.X.X:9981[br][br]\n antennas_url: http://X.X.X.X:5004[br][br]\n tuner_count: 4",
"Requires": "<br>&nbsp;&nbsp;&nbsp;&nbsp;To run this container, first create a config.yml on the config folder with the following lines (changing to the IPs, ports and tuner count of your system)<br>&nbsp;&nbsp;&nbsp;&nbsp;tvheadend_url: http://user:pas@X.X.X.X:9981<br>&nbsp;&nbsp;&nbsp;&nbsp;antennas_url: http://X.X.X.X:5004<br>&nbsp;&nbsp;&nbsp;&nbsp;tuner_count: 4 <br> ",
"WebUI": "http://[IP]:[PORT:5004]",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/main/yayitazale/antennas.xml",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/-/raw/main/yayitazale/antennas.xml",
"Icon": "https://raw.githubusercontent.com/yayitazale/unraid-templates/main/antennas.png",
"Networking": {
"Mode": "bridge"
@ -175810,7 +175810,7 @@
"Project": "https://docs.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.\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 RTMP to reduce the number of connections to your camera\r\n\r\n[b]A config.yml file must exist in the config directory.[/b]\r\nSee the documentation for more details.",
"WebUI": "http://[IP]:[PORT:5000]",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/main/yayitazale/frigate.xml",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/-/raw/main/yayitazale/frigate.xml",
"Icon": "https://raw.githubusercontent.com/yayitazale/unraid-templates/main/frigate.png",
"ExtraParams": "--shm-size=256mb --mount type=tmpfs,target=/tmp/cache,tmpfs-size=1000000000",
"Requires": "Note: If you are using a PCI Coral instead of a USB one, you must install first the needed drivers going to the CA APP and searching for Coral-Driver (thanks to @ich777)\r<br>\r<br>If you want to use a nvidia card to image decoding, you must add the &quot;--gpus all&quot; extra parameter. If you have multiple GPUs in your system with some allocated to VMs, you instead must 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.",
@ -175979,7 +175979,7 @@
"Support": "https://forums.unraid.net/topic/118806-support-grafana-grafana-image-renderer/",
"Project": "https://github.com/grafana/grafana-image-renderer/blob/master/docs/remote_rendering_using_docker.md",
"Overview": "A Grafana remote image renderer that handles rendering panels &amp; dashboards to PNGs using headless chrome.\r\n[br][br]\r\nRead Grafana Image Renderer documentation and see usage instructions at [b][u][a \"https://github.com/grafana/grafana-image-renderer/blob/master/docs/remote_rendering_using_docker.md\"]projects page[/a][/b][/u].\r\n[br][br]\r\nIn order to use this as a plugin of your Grafana docker instance you [b]must[/b] add this enviromental arguments to that container:\r\n[br][br]\r\n- GF_RENDERING_SERVER_URL: http://renderer-ip:8081/render[br]\r\n- GF_RENDERING_CALLBACK_URL: http://grafana-ip:3000/\r\n[br][br]\r\nChange the IP (and the ports) to suit your configuration.",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/main/yayitazale/grafana-image-renderer.xml",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/-/raw/main/yayitazale/grafana-image-renderer.xml",
"Icon": "https://github.com/atribe/unRAID-docker/raw/master/icons/grafana.png",
"Networking": {
"Mode": "bridge"
@ -176050,7 +176050,7 @@
"Support": "https://forums.unraid.net/topic/128633-support-steffo99-greed/",
"Project": "https://github.com/Steffo99/greed",
"Overview": "A customizable, multilanguage Telegram shop bot with Telegram Payments support!\r\n\r\nPlease refer to docs to learn how to activate it and how to use it. This container is not working by itself. Brief installing instructions:\r\n\r\n1. Donwload and run the container\r\n2. Edit the configuration file *config.toml* that was created in the *config* directory, adding your bot and payment tokens to it.\r\n3. Optional: customize the files in the strings folder for custom messages.\r\n4. Start the bot using the console of the container and the following command: *python -OO core.py*\r\n5. Open Telegram, and send a */start* command to your bot to be automatically promoted to \ud83d\udcbc Manager.\r\n6. Stop the bot by pressing Ctrl+C.\r\n7. Restart the container.",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/main/yayitazale/greed.xml",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/-/raw/main/yayitazale/greed.xml",
"Icon": "https://raw.githubusercontent.com/yayitazale/unraid-templates/main/greed.png",
"DonateText": "Donate",
"DonateLink": "https://ko-fi.com/steffo",

20
old-applicationFeed-raw.json
View File

@ -39872,8 +39872,8 @@
],
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"stars": 1,
"LastUpdate": 1455210504,
"LastUpdateScan": 1669727044,
"LastUpdate": 1455210504,
"FirstSeen": 1455166800
},
{
@ -41047,8 +41047,8 @@
"MediaServer-Video"
],
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},
{
@ -120319,7 +120319,6 @@
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95003775
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"topTrending": 1.663,
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@ -124110,7 +124110,6 @@
],
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1.002,
@ -124140,6 +124139,7 @@
10236983
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@ -175560,7 +175560,7 @@
"Overview": "HDHomeRun emulator for Plex/Jellyfin/Emby DVR to connect to Tvheadend.[br][br]\n To run this container, [b]first create a config.yml on the config folder[/b] with the following lines (changing to the IPs, ports and tuner count of your system)[br][br]\n tvheadend_url: http://user:pas@X.X.X.X:9981[br][br]\n antennas_url: http://X.X.X.X:5004[br][br]\n tuner_count: 4",
"Requires": "<br>&nbsp;&nbsp;&nbsp;&nbsp;To run this container, first create a config.yml on the config folder with the following lines (changing to the IPs, ports and tuner count of your system)<br>&nbsp;&nbsp;&nbsp;&nbsp;tvheadend_url: http://user:pas@X.X.X.X:9981<br>&nbsp;&nbsp;&nbsp;&nbsp;antennas_url: http://X.X.X.X:5004<br>&nbsp;&nbsp;&nbsp;&nbsp;tuner_count: 4 <br> ",
"WebUI": "http://[IP]:[PORT:5004]",
"TemplateURL": "https://raw.githubusercontent.com/yayitazale/unraid-templates/master/yayitazale/antennas.xml",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/main/yayitazale/antennas.xml",
"Icon": "https://raw.githubusercontent.com/yayitazale/unraid-templates/main/antennas.png",
"Networking": {
"Mode": "bridge"
@ -175648,7 +175648,7 @@
"Project": "https://docs.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.\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 RTMP to reduce the number of connections to your camera\r\n\r\n[b]A config.yml file must exist in the config directory.[/b]\r\nSee the documentation for more details.",
"WebUI": "http://[IP]:[PORT:5000]",
"TemplateURL": "https://raw.githubusercontent.com/yayitazale/unraid-templates/master/yayitazale/frigate.xml",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/main/yayitazale/frigate.xml",
"Icon": "https://raw.githubusercontent.com/yayitazale/unraid-templates/main/frigate.png",
"ExtraParams": "--shm-size=256mb --mount type=tmpfs,target=/tmp/cache,tmpfs-size=1000000000",
"Requires": "Note: If you are using a PCI Coral instead of a USB one, you must install first the needed drivers going to the CA APP and searching for Coral-Driver (thanks to @ich777)\r<br>\r<br>If you want to use a nvidia card to image decoding, you must add the &quot;--gpus all&quot; extra parameter. If you have multiple GPUs in your system with some allocated to VMs, you instead must 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.",
@ -175817,7 +175817,7 @@
"Support": "https://forums.unraid.net/topic/118806-support-grafana-grafana-image-renderer/",
"Project": "https://github.com/grafana/grafana-image-renderer/blob/master/docs/remote_rendering_using_docker.md",
"Overview": "A Grafana remote image renderer that handles rendering panels &amp; dashboards to PNGs using headless chrome.\r\n[br][br]\r\nRead Grafana Image Renderer documentation and see usage instructions at [b][u][a \"https://github.com/grafana/grafana-image-renderer/blob/master/docs/remote_rendering_using_docker.md\"]projects page[/a][/b][/u].\r\n[br][br]\r\nIn order to use this as a plugin of your Grafana docker instance you [b]must[/b] add this enviromental arguments to that container:\r\n[br][br]\r\n- GF_RENDERING_SERVER_URL: http://renderer-ip:8081/render[br]\r\n- GF_RENDERING_CALLBACK_URL: http://grafana-ip:3000/\r\n[br][br]\r\nChange the IP (and the ports) to suit your configuration.",
"TemplateURL": "https://raw.githubusercontent.com/yayitazale/unraid-templates/master/yayitazale/grafana-image-renderer.xml",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/main/yayitazale/grafana-image-renderer.xml",
"Icon": "https://github.com/atribe/unRAID-docker/raw/master/icons/grafana.png",
"Networking": {
"Mode": "bridge"
@ -175888,7 +175888,7 @@
"Support": "https://forums.unraid.net/topic/128633-support-steffo99-greed/",
"Project": "https://github.com/Steffo99/greed",
"Overview": "A customizable, multilanguage Telegram shop bot with Telegram Payments support!\r\n\r\nPlease refer to docs to learn how to activate it and how to use it. This container is not working by itself. Brief installing instructions:\r\n\r\n1. Donwload and run the container\r\n2. Edit the configuration file *config.toml* that was created in the *config* directory, adding your bot and payment tokens to it.\r\n3. Optional: customize the files in the strings folder for custom messages.\r\n4. Start the bot using the console of the container and the following command: *python -OO core.py*\r\n5. Open Telegram, and send a */start* command to your bot to be automatically promoted to \ud83d\udcbc Manager.\r\n6. Stop the bot by pressing Ctrl+C.\r\n7. Restart the container.",
"TemplateURL": "https://raw.githubusercontent.com/yayitazale/unraid-templates/master/yayitazale/greed.xml",
"TemplateURL": "https://gitlab.com/yayitazale/unraid-templates/main/yayitazale/greed.xml",
"Icon": "https://raw.githubusercontent.com/yayitazale/unraid-templates/main/greed.png",
"DonateText": "Donate",
"DonateLink": "https://ko-fi.com/steffo",
@ -210971,8 +210971,8 @@
"Crypto"
],
"downloads": 1340,
"LastUpdate": 1630747610,
"LastUpdateScan": 1669727044,
"LastUpdate": 1630747610,
"FirstSeen": 1630757005
},
{
@ -225877,7 +225877,6 @@
],
"downloads": 18224145,
"stars": 36,
"LastUpdate": 1652890112,
"trending": 2.621,
"trends": [
4.013,
@ -225907,6 +225906,7 @@
18224145
],
"LastUpdateScan": 1669727045,
"LastUpdate": 1652890112,
"FirstSeen": 1638551021,
"topTrending": -1.392,
"topPerforming": 2.621