fix(l10n): Update translations from Transifex

Signed-off-by: Nextcloud bot <bot@nextcloud.com>

Author: nextcloud-bot

l10n/en_GB.js

@@ -2,9 +2,27 @@ OC.L10N.register(
     "recognize",
     {
     "Recognize" : "Recognise",
+    "Audio classification" : "Audio classification",
+    "Classify audios into categories." : "Classify audios into categories.",
+    "Audios" : "Audios",
+    "Provide audios to classify" : "Provide audios to classify",
     "Categories" : "Categories",
+    "The classified categories. Each input audio is mapped to a text containing a comma separated list of categories." : "The classified categories. Each input audio is mapped to a text containing a comma separated list of categories.",
+    "Image classification" : "Image classification",
+    "Classify images into categories." : "Classify images into categories.",
     "Images" : "Images",
+    "Provide images to classify" : "Provide images to classify",
+    "The classified categories. Each input image is mapped to a text containing a comma separated list of categories." : "The classified categories. Each input image is mapped to a text containing a comma separated list of categories.",
+    "Image face recognition" : "Image face recognition",
+    "Recognize faces in images and return embedding vectors for each face." : "Recognize faces in images and return embedding vectors for each face.",
+    "Provide images to recognize faces in" : "Provide images to recognize faces in",
+    "Faces" : "Faces",
+    "The detected faces. Each input image is mapped to a text containing JSON-encoded face descriptions ({x,y,width,height,score,vector,angle} ) separated by line breaks." : "The detected faces. Each input image is mapped to a text containing JSON-encoded face descriptions ({x,y,width,height,score,vector,angle} ) separated by line breaks.",
+    "Video classification" : "Video classification",
+    "Classify videos into categories." : "Classify videos into categories.",
     "Videos" : "Videos",
+    "Provide videos to classify" : "Provide videos to classify",
+    "The classified categories. Each input video is mapped to a text containing a comma separated list of categories." : "The classified categories. Each input video is mapped to a text containing a comma separated list of categories.",
     "Smart media tagging and face recognition with on-premises machine learning models" : "Smart media tagging and face recognition with on-premises machine learning models",
     "Smart media tagging and face recognition with on-premises machine learning models.\nThis app goes through your media collection and adds fitting tags, automatically categorizing your photos and music.\n\n* 📷 👪 Recognizes faces from contact photos\n* 📷 🏔 Recognizes animals, landscapes, food, vehicles, buildings and other objects\n* 📷 🗼 Recognizes landmarks and monuments\n* 👂 🎵 Recognizes music genres\n* 🎥 🤸 Recognizes human actions on video\n\n⚡ Tagging works via Nextcloud's Collaborative Tags\n  * 👂 listen to your tagged music with the audioplayer app\n  * 📷 view your tagged photos and videos with the photos app\n\nModel sizes:\n\n * Object recognition: 1GB\n * Landmark recognition: 300MB\n * Video action recognition: 50MB\n * Music genre recognition: 50MB\n\n## Ethical AI Rating\n### Rating for Photo object detection: 🟢\n\nPositive:\n* the software for training and inference of this model is open source\n* the trained model is freely available, and thus can be run on-premises\n* the training data is freely available, making it possible to check or correct for bias or optimise the performance and CO2 usage.\n\n### Rating for Photo face recognition: 🟢\n\nPositive:\n* the software for training and inference of this model is open source\n* the trained model is freely available, and thus can be run on-premises\n* the training data is freely available, making it possible to check or correct for bias or optimise the performance and CO2 usage.\n\n### Rating for Video action recognition: 🟢\n\nPositive:\n* the software for training and inferencing of this model is open source\n* the trained model is freely available, and thus can be ran on-premises\n* the training data is freely available, making it possible to check or correct for bias or optimise the performance and CO2 usage.\n\n## Ethical AI Rating\n### Rating Music genre recognition: 🟡\n\nPositive:\n* the software for training and inference of this model is open source\n* the trained model is freely available, and thus can be run on-premises\n\nNegative:\n* the training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model’s performance and CO2 usage.\n\nLearn more about the Nextcloud Ethical AI Rating [in our blog](https://nextcloud.com/blog/nextcloud-ethical-ai-rating/).\n\nAfter installation, you can enable tagging in the admin settings.\n\nRequirements:\n- php 7.4 and above\n- App \"collaborative tags\" enabled\n- For native speed:\n  - Processor: x86 64-bit (with support for AVX instructions)\n  - System with glibc (usually the norm on Linux; FreeBSD, Alpine linux and thus also the official Nextcloud Docker container and Nextcloud AIO are *not* such systems)\n- For sub-native speed (using WASM mode)\n  - Processor: x86 64-bit, arm64, armv7l (no AVX needed)\n  - System with glibc or musl (incl. Alpine linux and thus also the official Nextcloud Docker container and also Nextcloud AIO)\n- ~4GB of free RAM (if you're cutting it close, make sure you have some swap available)\n\nThe app does not send any sensitive data to cloud providers or similar services. All processing is done on your Nextcloud machine, using Tensorflow.js running in Node.js." : "Smart media tagging and face recognition with on-premises machine learning models.\nThis app goes through your media collection and adds fitting tags, automatically categorizing your photos and music.\n\n* 📷 👪 Recognizes faces from contact photos\n* 📷 🏔 Recognizes animals, landscapes, food, vehicles, buildings and other objects\n* 📷 🗼 Recognizes landmarks and monuments\n* 👂 🎵 Recognizes music genres\n* 🎥 🤸 Recognizes human actions on video\n\n⚡ Tagging works via Nextcloud's Collaborative Tags\n  * 👂 listen to your tagged music with the audioplayer app\n  * 📷 view your tagged photos and videos with the photos app\n\nModel sizes:\n\n * Object recognition: 1GB\n * Landmark recognition: 300MB\n * Video action recognition: 50MB\n * Music genre recognition: 50MB\n\n## Ethical AI Rating\n### Rating for Photo object detection: 🟢\n\nPositive:\n* the software for training and inference of this model is open source\n* the trained model is freely available, and thus can be run on-premises\n* the training data is freely available, making it possible to check or correct for bias or optimise the performance and CO2 usage.\n\n### Rating for Photo face recognition: 🟢\n\nPositive:\n* the software for training and inference of this model is open source\n* the trained model is freely available, and thus can be run on-premises\n* the training data is freely available, making it possible to check or correct for bias or optimise the performance and CO2 usage.\n\n### Rating for Video action recognition: 🟢\n\nPositive:\n* the software for training and inferencing of this model is open source\n* the trained model is freely available, and thus can be ran on-premises\n* the training data is freely available, making it possible to check or correct for bias or optimise the performance and CO2 usage.\n\n## Ethical AI Rating\n### Rating Music genre recognition: 🟡\n\nPositive:\n* the software for training and inference of this model is open source\n* the trained model is freely available, and thus can be run on-premises\n\nNegative:\n* the training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model’s performance and CO2 usage.\n\nLearn more about the Nextcloud Ethical AI Rating [in our blog](https://nextcloud.com/blog/nextcloud-ethical-ai-rating/).\n\nAfter installation, you can enable tagging in the admin settings.\n\nRequirements:\n- php 7.4 and above\n- App \"collaborative tags\" enabled\n- For native speed:\n  - Processor: x86 64-bit (with support for AVX instructions)\n  - System with glibc (usually the norm on Linux; FreeBSD, Alpine linux and thus also the official Nextcloud Docker container and Nextcloud AIO are *not* such systems)\n- For sub-native speed (using WASM mode)\n  - Processor: x86 64-bit, arm64, armv7l (no AVX needed)\n  - System with glibc or musl (incl. Alpine linux and thus also the official Nextcloud Docker container and also Nextcloud AIO)\n- ~4GB of free RAM (if you're cutting it close, make sure you have some swap available)\n\nThe app does not send any sensitive data to cloud providers or similar services. All processing is done on your Nextcloud machine, using Tensorflow.js running in Node.js.",
     "Your server does not support AVX instructions" : "Your server does not support AVX instructions",
@@ -23,6 +41,11 @@ OC.L10N.register(
     "Background Jobs are not executed via cron. Recognize requires background jobs to be executed via cron." : "Background Jobs are not executed via cron. Recognise requires background jobs to be executed via cron.",
     "The app is installed and will automatically classify files in background processes." : "The app is installed and will automatically classify files in background processes.",
     "None of the tagging options below are currently selected. The app will currently do nothing." : "None of the tagging options below are currently selected. The app will currently do nothing.",
+    "Classifier backend" : "Classifier backend",
+    "The recognize_backend ExApp is installed; TaskProcessing mode is recommended." : "The recognize_backend ExApp is installed; TaskProcessing mode is recommended.",
+    "TaskProcessing mode is enabled, but no recognize_backend ExApp was detected. Make sure a TaskProcessing provider for the recognize task types is installed and enabled." : "TaskProcessing mode is enabled, but no recognize_backend ExApp was detected. Make sure a TaskProcessing provider for the recognize task types is installed and enabled.",
+    "Use Nextcloud TaskProcessing for classification" : "Use Nextcloud TaskProcessing for classification",
+    "When enabled, Recognize hands files off to a Nextcloud TaskProcessing provider (typically the recognize_backend ExApp) instead of running TensorFlow locally. Hardware checks and Node.js / FFmpeg requirements no longer apply in this mode." : "When enabled, Recognize hands files off to a Nextcloud TaskProcessing provider (typically the recognize_backend ExApp) instead of running TensorFlow locally. Hardware checks and Node.js / FFmpeg requirements no longer apply in this mode.",
     "Face recognition" : "Face recognition",
     "Face recognition is working. " : "Face recognition is working. ",
     "An error occurred during face recognition, please check the Nextcloud logs." : "An error occurred during face recognition, please check the Nextcloud logs.",
@@ -115,6 +138,8 @@ OC.L10N.register(
     "Nice value to set the priority of the Node.js processes. The value can only be from 0 to 19 since the Node.js process runs without superuser privileges. The higher the nice value, the lower the priority of the process." : "Nice value to set the priority of the Node.js processes. The value can only be from 0 to 19 since the Node.js process runs without superuser privileges. The higher the Nice value, the lower the priority of the process.",
     "Terminal commands" : "Terminal commands",
     "To download all models preliminary to executing the classification jobs, run the following command on the server terminal." : "To download all models preliminary to executing the classification jobs, run the following command on the server terminal.",
+    "To trigger a full classification run in the background, run the following command on the server terminal. (The classification will run in multiple background jobs which can run in parallel.)" : "To trigger a full classification run in the background, run the following command on the server terminal. (The classification will run in multiple background jobs which can run in parallel.)",
+    "To run a full classification run on the terminal, run the following. (The classification will run in sequence inside your terminal; doesn't work with task processing mode)" : "To run a full classification run on the terminal, run the following. (The classification will run in sequence inside your terminal; doesn't work with task processing mode)",
     "Before running a full initial classification run on the terminal, you should stop all background processing that Recognize scheduled upon installation to avoid interference." : "Before running a full initial classification run on the terminal, you should stop all background processing that Recognize scheduled upon installation to avoid interference.",
     "To run a face clustering run on for each user in the terminal, run the following. Consider adding the parameter --batch-size 10000 for large libraries to avoid PHP memory exhaustion. (The clustering will run in sequence inside your terminal.)" : "To run a face clustering run on for each user in the terminal, run the following. Consider adding the parameter --batch-size 10000 for large libraries to avoid PHP memory exhaustion. (The clustering will run in sequence inside your terminal.)",
     "To remove all face clusters but keep the raw detected faces run the following on the terminal:" : "To remove all face clusters but keep the raw detected faces run the following on the terminal:",