i18n(ml): translate the new ML wrap-up training-services section (26 langs)

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

Author: kwagyeman

docs/locale/ar/LC_MESSAGES/openmvcam/tutorial/ml/wrap-up.po

@@ -10,7 +10,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: OpenMV MicroPython 1.28\n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2026-06-14 21:02-0700\n"
+"POT-Creation-Date: 2026-06-18 12:40-0700\n"
 "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
 "Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
 "Language-Team: ar <LL@li.org>\n"
@@ -19,7 +19,7 @@ msgstr ""
 "Content-Type: text/plain; charset=utf-8\n"
 "Content-Transfer-Encoding: 8bit\n"
 "Plural-Forms: nplurals=6; plural=(n==0 ? 0 : n==1 ? 1 : n==2 ? 2 : n%100>=3 && n%100<=10 ? 3 : n%100>=0 && n%100<=2 ? 4 : 5);\n"
-"Generated-By: Babel 2.18.0\n"
+"Generated-By: Babel 2.17.0\n"
 
 #: ../../openmvcam/tutorial/ml/wrap-up.rst:2
 msgid "Wrap up"
@@ -158,10 +158,50 @@ msgstr ""
 "الروافع الأربع، وقد غطّى الفصل كلًّا منها."
 
 #: ../../openmvcam/tutorial/ml/wrap-up.rst:77
+msgid "Training your own model"
+msgstr "تدريب نموذجك الخاص"
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:79
+msgid ""
+"This chapter started from a trained ``.tflite``. Producing one for a custom "
+"task -- a new set of object classes, a purpose-built classifier -- does not "
+"mean standing up a training pipeline by hand: two hosted services cover the "
+"whole loop, from collecting and labelling data through training to exporting"
+" a model the cam can load."
+msgstr ""
+"انطلق هذا الفصل من ملف ``.tflite`` مدرَّب مسبقاً. إنتاج ملف مماثل لمهمة "
+"مخصصة -- مجموعة جديدة من فئات الكائنات، أو مصنِّف مُصمَّم لغرض محدد -- لا "
+"يعني إنشاء خط أنابيب تدريب يدوياً: تغطي خدمتان مستضافتان الحلقة بأكملها، من "
+"جمع البيانات ووضع التسميات عليها، مروراً بالتدريب، وصولاً إلى تصدير نموذج "
+"يمكن للكاميرا تحميله."
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:86
+msgid ""
+":doc:`Edge Impulse <../tools/edge-impulse>` -- an end-to-end embedded-ML "
+"platform; capture data from the cam, label it, train, and export a quantized"
+" ``.tflite`` ready for the OpenMV inference engine."
+msgstr ""
+":doc:`Edge Impulse <../tools/edge-impulse>` -- منصة embedded-ML متكاملة من "
+"طرف إلى طرف؛ التقط البيانات من الكاميرا، وضع عليها التسميات، ودرِّب النموذج،"
+" ثم صدِّر ملف ``.tflite`` مُكمَّماً جاهزاً لمحرك الاستنتاج في OpenMV."
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:91
+msgid ""
+":doc:`Roboflow <../tools/roboflow/index>` -- dataset management and "
+"annotation with hosted training, geared toward object detection; export a "
+"YOLOv8 model that the :class:`~ml.postprocessing.ultralytics.YoloV8` post-"
+"processor decodes directly."
+msgstr ""
+":doc:`Roboflow <../tools/roboflow/index>` -- إدارة مجموعات البيانات والتعليق"
+" التوضيحي مع التدريب المستضاف، مُوجَّه نحو اكتشاف الكائنات؛ صدِّر نموذج "
+"YOLOv8 الذي يفككه معالج ما بعد التدريب "
+":class:`~ml.postprocessing.ultralytics.YoloV8` مباشرةً."
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:98
 msgid "ML composes with the rest of the cam"
 msgstr "تتكامل ML مع بقية أجزاء الكاميرا"
 
-#: ../../openmvcam/tutorial/ml/wrap-up.rst:79
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:100
 msgid ""
 "An inference rarely runs in isolation. The image module captures and pre-"
 "processes the frame, the ml module runs the network, and :mod:`ulab.numpy` "

docs/locale/cs/LC_MESSAGES/openmvcam/tutorial/ml/wrap-up.po

@@ -10,7 +10,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: OpenMV MicroPython 1.28\n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2026-06-14 21:02-0700\n"
+"POT-Creation-Date: 2026-06-18 12:40-0700\n"
 "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
 "Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
 "Language-Team: cs <LL@li.org>\n"
@@ -19,7 +19,7 @@ msgstr ""
 "Content-Type: text/plain; charset=utf-8\n"
 "Content-Transfer-Encoding: 8bit\n"
 "Plural-Forms: nplurals=3; plural=((n==1) ? 0 : (n>=2 && n<=4) ? 1 : 2);\n"
-"Generated-By: Babel 2.18.0\n"
+"Generated-By: Babel 2.17.0\n"
 
 #: ../../openmvcam/tutorial/ml/wrap-up.rst:2
 msgid "Wrap up"
@@ -163,10 +163,50 @@ msgstr ""
 "věnovala každé z nich."
 
 #: ../../openmvcam/tutorial/ml/wrap-up.rst:77
+msgid "Training your own model"
+msgstr "Trénink vlastního modelu"
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:79
+msgid ""
+"This chapter started from a trained ``.tflite``. Producing one for a custom "
+"task -- a new set of object classes, a purpose-built classifier -- does not "
+"mean standing up a training pipeline by hand: two hosted services cover the "
+"whole loop, from collecting and labelling data through training to exporting"
+" a model the cam can load."
+msgstr ""
+"Tato kapitola začínala od natrénovaného souboru ``.tflite``. Vytvořit "
+"vlastní soubor pro konkrétní úlohu -- novou sadu tříd objektů nebo účelový "
+"klasifikátor -- neznamená ručně budovat trénovací pipeline: dvě hostované "
+"služby pokrývají celý cyklus, od sběru a označování dat přes trénink až po "
+"export modelu, který kamera dokáže načíst."
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:86
+msgid ""
+":doc:`Edge Impulse <../tools/edge-impulse>` -- an end-to-end embedded-ML "
+"platform; capture data from the cam, label it, train, and export a quantized"
+" ``.tflite`` ready for the OpenMV inference engine."
+msgstr ""
+":doc:`Edge Impulse <../tools/edge-impulse>` -- komplexní platforma pro "
+"embedded-ML; zachyťte data z kamery, označte je, natrénujte model a "
+"exportujte kvantizovaný ``.tflite`` připravený pro inferenční engine OpenMV."
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:91
+msgid ""
+":doc:`Roboflow <../tools/roboflow/index>` -- dataset management and "
+"annotation with hosted training, geared toward object detection; export a "
+"YOLOv8 model that the :class:`~ml.postprocessing.ultralytics.YoloV8` post-"
+"processor decodes directly."
+msgstr ""
+":doc:`Roboflow <../tools/roboflow/index>` -- správa datových sad a anotace s"
+" hostovaným tréninkem, zaměřená na detekci objektů; exportujte model YOLOv8,"
+" který post-procesor :class:`~ml.postprocessing.ultralytics.YoloV8` dekóduje"
+" přímo."
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:98
 msgid "ML composes with the rest of the cam"
 msgstr "ML se skládá se zbytkem kamery"
 
-#: ../../openmvcam/tutorial/ml/wrap-up.rst:79
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:100
 msgid ""
 "An inference rarely runs in isolation. The image module captures and pre-"
 "processes the frame, the ml module runs the network, and :mod:`ulab.numpy` "

docs/locale/de/LC_MESSAGES/openmvcam/tutorial/ml/wrap-up.po

@@ -10,7 +10,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: OpenMV MicroPython 1.28\n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2026-06-14 21:02-0700\n"
+"POT-Creation-Date: 2026-06-18 12:40-0700\n"
 "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
 "Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
 "Language-Team: de <LL@li.org>\n"
@@ -19,7 +19,7 @@ msgstr ""
 "Content-Type: text/plain; charset=utf-8\n"
 "Content-Transfer-Encoding: 8bit\n"
 "Plural-Forms: nplurals=2; plural=(n != 1);\n"
-"Generated-By: Babel 2.18.0\n"
+"Generated-By: Babel 2.17.0\n"
 
 #: ../../openmvcam/tutorial/ml/wrap-up.rst:2
 msgid "Wrap up"
@@ -167,10 +167,52 @@ msgstr ""
 "behandelt."
 
 #: ../../openmvcam/tutorial/ml/wrap-up.rst:77
+msgid "Training your own model"
+msgstr "Eigenes Modell trainieren"
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:79
+msgid ""
+"This chapter started from a trained ``.tflite``. Producing one for a custom "
+"task -- a new set of object classes, a purpose-built classifier -- does not "
+"mean standing up a training pipeline by hand: two hosted services cover the "
+"whole loop, from collecting and labelling data through training to exporting"
+" a model the cam can load."
+msgstr ""
+"Dieses Kapitel ging von einer bereits trainierten ``.tflite``-Datei aus. "
+"Eine solche Datei für eine eigene Aufgabe zu erzeugen -- eine neue Menge von"
+" Objektklassen, einen zweckgebundenen Klassifikator -- bedeutet nicht, eine "
+"Trainingspipeline von Hand aufzubauen: Zwei gehostete Dienste decken den "
+"gesamten Ablauf ab, vom Erfassen und Beschriften der Daten über das Training"
+" bis hin zum Export eines Modells, das die Kamera laden kann."
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:86
+msgid ""
+":doc:`Edge Impulse <../tools/edge-impulse>` -- an end-to-end embedded-ML "
+"platform; capture data from the cam, label it, train, and export a quantized"
+" ``.tflite`` ready for the OpenMV inference engine."
+msgstr ""
+":doc:`Edge Impulse <../tools/edge-impulse>` -- eine durchgängige embedded-"
+"ML-Plattform; erfassen Sie Daten von der Kamera, beschriften Sie diese, "
+"trainieren Sie das Modell und exportieren Sie eine quantisierte "
+"``.tflite``-Datei, die für die OpenMV-Inferenz-Engine bereit ist."
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:91
+msgid ""
+":doc:`Roboflow <../tools/roboflow/index>` -- dataset management and "
+"annotation with hosted training, geared toward object detection; export a "
+"YOLOv8 model that the :class:`~ml.postprocessing.ultralytics.YoloV8` post-"
+"processor decodes directly."
+msgstr ""
+":doc:`Roboflow <../tools/roboflow/index>` -- Datensatzverwaltung und "
+"-annotation mit gehostetem Training, ausgerichtet auf Objekterkennung; "
+"exportieren Sie ein YOLOv8-Modell, das der Post-Prozessor "
+":class:`~ml.postprocessing.ultralytics.YoloV8` direkt dekodiert."
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:98
 msgid "ML composes with the rest of the cam"
 msgstr "ML lässt sich mit dem Rest der Kamera kombinieren"
 
-#: ../../openmvcam/tutorial/ml/wrap-up.rst:79
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:100
 msgid ""
 "An inference rarely runs in isolation. The image module captures and pre-"
 "processes the frame, the ml module runs the network, and :mod:`ulab.numpy` "

docs/locale/es/LC_MESSAGES/openmvcam/tutorial/ml/wrap-up.po

@@ -10,7 +10,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: OpenMV MicroPython 1.28\n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2026-06-14 21:02-0700\n"
+"POT-Creation-Date: 2026-06-18 12:40-0700\n"
 "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
 "Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
 "Language-Team: es <LL@li.org>\n"
@@ -19,7 +19,7 @@ msgstr ""
 "Content-Type: text/plain; charset=utf-8\n"
 "Content-Transfer-Encoding: 8bit\n"
 "Plural-Forms: nplurals=2; plural=(n != 1);\n"
-"Generated-By: Babel 2.18.0\n"
+"Generated-By: Babel 2.17.0\n"
 
 #: ../../openmvcam/tutorial/ml/wrap-up.rst:2
 msgid "Wrap up"
@@ -166,10 +166,52 @@ msgstr ""
 "de ellas."
 
 #: ../../openmvcam/tutorial/ml/wrap-up.rst:77
+msgid "Training your own model"
+msgstr "Entrenar tu propio modelo"
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:79
+msgid ""
+"This chapter started from a trained ``.tflite``. Producing one for a custom "
+"task -- a new set of object classes, a purpose-built classifier -- does not "
+"mean standing up a training pipeline by hand: two hosted services cover the "
+"whole loop, from collecting and labelling data through training to exporting"
+" a model the cam can load."
+msgstr ""
+"Este capítulo partió de un archivo ``.tflite`` ya entrenado. Generar uno "
+"para una tarea personalizada -- un nuevo conjunto de clases de objetos, un "
+"clasificador creado con un propósito específico -- no implica construir "
+"manualmente un pipeline de entrenamiento: dos servicios alojados cubren todo"
+" el ciclo, desde la recopilación y el etiquetado de datos hasta el "
+"entrenamiento y la exportación de un modelo que la cámara puede cargar."
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:86
+msgid ""
+":doc:`Edge Impulse <../tools/edge-impulse>` -- an end-to-end embedded-ML "
+"platform; capture data from the cam, label it, train, and export a quantized"
+" ``.tflite`` ready for the OpenMV inference engine."
+msgstr ""
+":doc:`Edge Impulse <../tools/edge-impulse>` -- una plataforma embedded-ML de"
+" extremo a extremo; capture datos de la cámara, etiquételos, entrene el "
+"modelo y exporte un archivo ``.tflite`` cuantizado listo para el motor de "
+"inferencia de OpenMV."
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:91
+msgid ""
+":doc:`Roboflow <../tools/roboflow/index>` -- dataset management and "
+"annotation with hosted training, geared toward object detection; export a "
+"YOLOv8 model that the :class:`~ml.postprocessing.ultralytics.YoloV8` post-"
+"processor decodes directly."
+msgstr ""
+":doc:`Roboflow <../tools/roboflow/index>` -- gestión de conjuntos de datos y"
+" anotación con entrenamiento alojado, orientado a la detección de objetos; "
+"exporte un modelo YOLOv8 que el postprocesador "
+":class:`~ml.postprocessing.ultralytics.YoloV8` decodifica directamente."
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:98
 msgid "ML composes with the rest of the cam"
 msgstr "El ML se combina con el resto de la cámara"
 
-#: ../../openmvcam/tutorial/ml/wrap-up.rst:79
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:100
 msgid ""
 "An inference rarely runs in isolation. The image module captures and pre-"
 "processes the frame, the ml module runs the network, and :mod:`ulab.numpy` "

docs/locale/fi/LC_MESSAGES/openmvcam/tutorial/ml/wrap-up.po

@@ -10,7 +10,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: OpenMV MicroPython 1.28\n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2026-06-14 21:02-0700\n"
+"POT-Creation-Date: 2026-06-18 12:40-0700\n"
 "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
 "Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
 "Language-Team: fi <LL@li.org>\n"
@@ -19,7 +19,7 @@ msgstr ""
 "Content-Type: text/plain; charset=utf-8\n"
 "Content-Transfer-Encoding: 8bit\n"
 "Plural-Forms: nplurals=2; plural=(n != 1);\n"
-"Generated-By: Babel 2.18.0\n"
+"Generated-By: Babel 2.17.0\n"
 
 #: ../../openmvcam/tutorial/ml/wrap-up.rst:2
 msgid "Wrap up"
@@ -162,10 +162,51 @@ msgstr ""
 " vipua, ja luku käsitteli jokaisen niistä."
 
 #: ../../openmvcam/tutorial/ml/wrap-up.rst:77
+msgid "Training your own model"
+msgstr "Oman mallin kouluttaminen"
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:79
+msgid ""
+"This chapter started from a trained ``.tflite``. Producing one for a custom "
+"task -- a new set of object classes, a purpose-built classifier -- does not "
+"mean standing up a training pipeline by hand: two hosted services cover the "
+"whole loop, from collecting and labelling data through training to exporting"
+" a model the cam can load."
+msgstr ""
+"Tässä luvussa lähtökohtana oli valmiiksi koulutettu ``.tflite``-tiedosto. "
+"Sellaisen tuottaminen omaa tehtävää varten -- uutta objektiluokkien joukkoa "
+"tai tarkoitusta varten rakennettua luokittelijaa varten -- ei tarkoita "
+"koulutusputken pystyttämistä käsin: kaksi pilvipalvelua kattaa koko ketjun "
+"datan keräämisestä ja merkitsemisestä koulutuksen kautta mallin viemiseen "
+"muotoon, jonka kamera voi ladata."
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:86
+msgid ""
+":doc:`Edge Impulse <../tools/edge-impulse>` -- an end-to-end embedded-ML "
+"platform; capture data from the cam, label it, train, and export a quantized"
+" ``.tflite`` ready for the OpenMV inference engine."
+msgstr ""
+":doc:`Edge Impulse <../tools/edge-impulse>` -- kattava embedded-ML-alusta; "
+"kerää dataa kamerasta, merkitse se, kouluta malli ja vie kvantisoitu "
+"``.tflite``-tiedosto, joka on valmis OpenMV:n päättelymoottorin käyttöön."
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:91
+msgid ""
+":doc:`Roboflow <../tools/roboflow/index>` -- dataset management and "
+"annotation with hosted training, geared toward object detection; export a "
+"YOLOv8 model that the :class:`~ml.postprocessing.ultralytics.YoloV8` post-"
+"processor decodes directly."
+msgstr ""
+":doc:`Roboflow <../tools/roboflow/index>` -- tietoaineistojen hallinta ja "
+"merkitseminen pilvipalvelukoulutuksella, suunnattu objektintunnistukseen; "
+"vie YOLOv8-malli, jonka jälkikäsittelijä "
+":class:`~ml.postprocessing.ultralytics.YoloV8` purkaa suoraan."
+
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:98
 msgid "ML composes with the rest of the cam"
 msgstr "ML yhdistyy muuhun kameraan"
 
-#: ../../openmvcam/tutorial/ml/wrap-up.rst:79
+#: ../../openmvcam/tutorial/ml/wrap-up.rst:100
 msgid ""
 "An inference rarely runs in isolation. The image module captures and pre-"
 "processes the frame, the ml module runs the network, and :mod:`ulab.numpy` "