update chinese i18n (#17450)

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GuoQing Liu 2025-03-30 18:55:26 +08:00 committed by GitHub
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3 changed files with 16 additions and 8 deletions

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@ -16,6 +16,7 @@
"createFaceLibrary": {
"title": "创建人脸库",
"desc": "创建一个新的人脸库",
"new": "新建人脸",
"nextSteps": "建议使用“训练”选项卡为每个检测到的人选择并训练图像。在打好基础前,强烈建议训练仅使用正面图像。而不是从摄像机中识别到的角度拍摄的人脸图像。"
},
"train": {

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@ -87,9 +87,15 @@
"title": "语义搜索",
"desc": "Frigate的语义搜索能够让你使用自然语言根据图像本身、自定义的文本描述或自动生成的描述来搜索视频。",
"readTheDocumentation": "阅读文档(英文)",
"reindexOnStartup": {
"label": "启动时重新索引",
"desc": "每次启动将重新索引并重新处理所有缩略图和描述。<em>关闭该设置后不要忘记重启!</em>"
"reindexNow": {
"label": "立即重建索引",
"desc": "重建索引将为所有跟踪对象重新生成特征向量。该过程将在后台运行可能会使CPU满载所需时间取决于跟踪对象的数量。",
"confirmTitle": "确认重建索引",
"confirmDesc": "确定要为所有跟踪对象重建特征向量索引吗此过程将在后台运行但可能会导致CPU满载并耗费较长时间。您可以在探索页面查看进度。",
"confirmButton": "重建索引",
"success": "重建索引已成功启动。",
"alreadyInProgress": "重建索引已在执行中。",
"error": "启动重建索引失败:{{errorMessage}}"
},
"modelSize": {
"label": "模型大小",
@ -113,11 +119,11 @@
"desc": "用于人脸识别的模型尺寸。",
"small": {
"title": "小模型",
"desc": "使用<em>小模型</em>将采用OpenCV的局部二值模式直方图(LBPH)算法可在大多数CPU上高效运行。"
"desc": "使用<em>小模型</em>将采用FaceNet人脸特征提取模型可在大多数CPU上高效运行。"
},
"large": {
"title": "大模型",
"desc": "使用<em>大模型</em>将采用ArcFace人脸嵌入模型若适用将自动在GPU上运行。"
"desc": "使用<em>大模型</em>将采用ArcFace人脸特征提取模型若条件允许将自动使用GPU运行。"
}
}
},

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@ -3,7 +3,7 @@
"cameras": "摄像头统计 - Frigate",
"storage": "存储统计 - Frigate",
"general": "常规统计 - Frigate",
"features": "功能统计 - Frigate",
"enrichments": "增强功能统计 - Frigate",
"logs": {
"frigate": "Frigate 日志 - Frigate",
"go2rtc": "Go2RTC 日志 - Frigate",
@ -144,8 +144,9 @@
"healthy": "系统运行正常",
"reindexingEmbeddings": "正在重新索引嵌入(已完成 {{processed}}%"
},
"features": {
"title": "功能",
"enrichments": {
"title": "增强功能",
"infPerSecond": "每秒推理次数",
"embeddings": {
"image_embedding_speed": "图像特征提取速度",
"face_embedding_speed": "人脸特征提取速度",