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https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
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Merge pull request #3 from dtlnor/add-updated-content-2
Add updated content 2
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commit
70841438a1
@ -18,7 +18,6 @@
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"Train": "训练",
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"Create aesthetic embedding": "生成美术风格",
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"Image Browser": "图库浏览器",
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"History": "历史记录",
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"Settings": "设置",
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"Prompt": "提示词",
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"Negative prompt": "反向提示词",
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@ -87,10 +86,8 @@
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"X/Y plot": "X/Y 图表",
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"Source embedding to convert": "用于转换的源 Embedding",
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"Embedding token": "Embedding 的 token (关键词)",
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"Output directory": "输出目录",
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"Put variable parts at start of prompt": "把变量部分放在提示词文本的开头",
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"Show Textbox": "显示文本框",
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"File with inputs": "含输入内容的文件",
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"Prompts": "提示词",
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"Iterate seed every line": "每行输入都换一个种子",
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"List of prompt inputs": "提示词输入列表",
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"Upload prompt inputs": "上传提示词输入文件",
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@ -119,7 +116,6 @@
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"Draw legend": "在图表中包括轴标题",
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"Include Separate Images": "包括独立的图像",
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"Keep -1 for seeds": "保持随机种子为-1",
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"Drop Image Here": "拖拽图像到此",
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"Save": "保存",
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"Send to img2img": ">> 图生图",
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"Send to inpaint": ">> 内补绘制",
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@ -131,6 +127,7 @@
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"Inpaint": "内补绘制",
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"Batch img2img": "批量图生图",
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"Image for img2img": "图生图的图像",
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"Drop Image Here": "拖拽图像到此",
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"Image for inpainting with mask": "用于内补绘制蒙版内容的图像",
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"Mask": "蒙版",
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"Mask blur": "蒙版模糊",
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@ -149,9 +146,7 @@
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"Inpaint at full resolution padding, pixels": "以完整分辨率进行内补绘制 - 填补像素",
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"Process images in a directory on the same machine where the server is running.": "在服务器主机上的目录中处理图像",
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"Use an empty output directory to save pictures normally instead of writing to the output directory.": "指定一个空的文件夹为输出目录而非默认的 output 文件夹为输出目录",
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"Disabled when launched with --hide-ui-dir-config.": "启动 --hide-ui-dir-config 时禁用",
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"Input directory": "输入目录",
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"Output directory": "输出目录",
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"Resize mode": "缩放模式",
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"Just resize": "拉伸",
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"Crop and resize": "裁剪",
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@ -185,6 +180,7 @@
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"Color variation": "色彩变化",
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"Will upscale the image to twice the dimensions; use width and height sliders to set tile size": "将图像放大到两倍尺寸; 使用宽度和高度滑块设置图块尺寸(tile size)",
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"Tile overlap": "图块重叠的像素(Tile overlap)",
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"Upscaler": "Upscaler",
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"Lanczos": "Lanczos",
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"LDSR": "LDSR",
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"BSRGAN 4x": "BSRGAN 4x",
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@ -202,14 +198,11 @@
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"Scale to": "指定尺寸缩放",
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"Resize": "缩放",
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"Crop to fit": "裁剪以适应",
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"Upscaler 1": "放大算法 1",
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"Upscaler 2": "放大算法 2",
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"Upscaler 2 visibility": "放大算法 2 可见度",
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"GFPGAN visibility": "GFPGAN 可见度",
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"CodeFormer visibility": "CodeFormer 可见度",
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"CodeFormer weight (0 = maximum effect, 1 = minimum effect)": "CodeFormer 权重 (0 = 最大效果, 1 = 最小效果)",
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"Upscale Before Restoring Faces": "放大后再进行面部修复",
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"Open output directory": "打开输出目录",
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"Send to txt2img": ">> 文生图",
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"A merger of the two checkpoints will be generated in your": "合并后的模型(ckpt)会生成在你的",
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"checkpoint": "模型(ckpt)",
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@ -227,7 +220,6 @@
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"wiki": "帮助",
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"for detailed explanation.": "以了解详细说明",
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"Create embedding": "生成 embedding",
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"Create aesthetic images embedding": "生成美术风格图集 embedding",
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"Create hypernetwork": "生成 hypernetwork",
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"Preprocess images": "图像预处理",
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"Name": "名称",
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@ -283,7 +275,6 @@
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"prepend": "放前面",
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"append": "放后面",
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"Create flipped copies": "生成镜像副本",
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"Split oversized images into two": "将过大的图像分为两份",
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"Split oversized images": "分割过大的图像",
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"Auto focal point crop": "自动焦点裁切",
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"Use BLIP for caption": "使用 BLIP 生成说明文字(自然语言描述)",
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@ -295,13 +286,11 @@
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"Focal point edges weight": "焦点线条权重",
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"Create debug image": "生成调试(debug)图片",
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"Preprocess": "预处理",
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"Train an embedding; must specify a directory with a set of 1:1 ratio images": "训练 embedding; 必须指定一组具有 1:1 比例图像的目录",
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"Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images": "训练 embedding 或者 hypernetwork; 必须指定一组具有 1:1 比例图像的目录",
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"[wiki]": "[帮助]",
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"Embedding": "Embedding",
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"Embedding Learning rate": "Embedding 学习率",
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"Hypernetwork Learning rate": "Hypernetwork 学习率",
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"Learning rate": "学习率",
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"Dataset directory": "数据集目录",
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"Log directory": "日志目录",
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"Prompt template file": "提示词模版文件",
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@ -314,25 +303,15 @@
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"Train Embedding": "训练 Embedding",
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"Create an aesthetic embedding out of any number of images": "从任意数量的图像中创建美术风格 embedding",
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"Create images embedding": "生成图集 embedding",
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"txt2img history": "文生图历史记录",
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"img2img history": "图生图历史记录",
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"extras history": "更多选项卡的历史记录",
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"Renew Page": "刷新页面",
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"extras": "更多",
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"favorites": "已保存",
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"others": "其他",
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"custom fold": "自定义文件夹",
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"Load": "载入",
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"Favorites": "已保存",
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"Others": "其他",
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"Images directory": "图像目录",
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"Dropdown": "下拉列表",
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"Prev batch": "上一批",
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"Next batch": "下一批",
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"First Page": "首页",
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"Prev Page": "上一页",
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"Page Index": "页数",
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"Next Page": "下一页",
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"End Page": "尾页",
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"number of images to delete consecutively next": "接下来要连续删除的图像数",
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"delete next": "删除下一张",
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"Delete": "删除",
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"sort by": "排序方式",
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@ -341,9 +320,8 @@
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"keyword": "搜索",
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"Generate Info": "生成信息",
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"File Name": "文件名",
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"Collect": "保存",
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"Refresh page": "刷新页面",
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"Date to": "日期至",
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"Move to favorites": "移动到已保存",
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"Renew Page": "刷新页面",
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"Number": "数量",
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"set_index": "设置索引",
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"load_switch": "载入开关",
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@ -400,7 +378,6 @@
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"Always print all generation info to standard output": "始终将所有生成信息输出到 standard output (一般为控制台)",
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"Add a second progress bar to the console that shows progress for an entire job.": "向控制台添加第二个进度条,显示整个作业的进度",
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"Training": "训练",
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"Unload VAE and CLIP from VRAM when training": "训练时从显存(VRAM)中取消 VAE 和 CLIP 的加载",
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"Move VAE and CLIP to RAM when training hypernetwork. Saves VRAM.": "训练时将 VAE 和 CLIP 从显存(VRAM)移放到内存(RAM),节省显存(VRAM)",
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"Filename word regex": "文件名用词的正则表达式",
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"Filename join string": "文件名连接用字符串",
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@ -463,9 +440,7 @@
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"Preload images at startup": "在启动时预加载图像",
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"Number of columns on the page": "每页列数",
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"Number of rows on the page": "每页行数",
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"Number of pictures displayed on each page": "每页显示的图像数量",
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"Minimum number of pages per load": "每次加载的最小页数",
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"Number of grids in each row": "每行显示多少格",
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"Wildcards": "通配符",
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"Use same seed for all images": "为所有图像使用同一个随机种子",
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"Request browser notifications": "请求浏览器通知",
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@ -520,7 +495,6 @@
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"Result = A * (1 - M) + B * M": "结果 = A * (1 - M) + B * M",
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"Result = A + (B - C) * M": "结果 = A + (B - C) * M",
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"1st and last digit must be 1. ex:'1, 2, 1'": "第一个和最后一个数字必须是 1。例:'1, 2, 1'",
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"how fast should the training go. Low values will take longer to train, high values may fail to converge (not generate accurate results) and/or may break the embedding (This has happened if you see Loss: nan in the training info textbox. If this happens, you need to manually restore your embedding from an older not-broken backup).\n\nYou can set a single numeric value, or multiple learning rates using the syntax:\n\n rate_1:max_steps_1, rate_2:max_steps_2, ...\n\nEG: 0.005:100, 1e-3:1000, 1e-5\n\nWill train with rate of 0.005 for first 100 steps, then 1e-3 until 1000 steps, then 1e-5 for all remaining steps.": "训练应该多快。低值将需要更长的时间来训练,高值可能无法收敛(无法产生准确的结果)以及/也许可能会破坏 embedding(如果你在训练信息文本框中看到 Loss: nan 就会发生这种情况。如果发生这种情况,你需要从较旧的未损坏的备份手动恢复 embedding)\n\n你可以使用以下语法设置单个数值或多个学习率:\n\n 率1:步限1, 率2:步限2, ...\n\n如: 0.005:100, 1e-3:1000, 1e-5\n\n即前 100 步将以 0.005 的速率训练,接着直到 1000 步为止以 1e-3 训练,然后剩余所有步以 1e-5 训练",
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"Path to directory with input images": "带有输入图像的路径",
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"Path to directory where to write outputs": "进行输出的路径",
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"Input images directory": "输入图像目录",
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@ -533,9 +507,38 @@
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"Only applies to inpainting models. Determines how strongly to mask off the original image for inpainting and img2img. 1.0 means fully masked, which is the default behaviour. 0.0 means a fully unmasked conditioning. Lower values will help preserve the overall composition of the image, but will struggle with large changes.": "仅适用于内补绘制专用的模型。 决定了蒙版在内补绘制以及图生图中屏蔽原图内容的强度。 1.0 表示完全屏蔽,这是默认行为。 0.0 表示完全不屏蔽。 较低的值将有助于保持图像的整体构图,但很难遇到较大的变化。",
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"List of setting names, separated by commas, for settings that should go to the quick access bar at the top, rather than the usual setting tab. See modules/shared.py for setting names. Requires restarting to apply.": "设置名称列表,以逗号分隔,设置应转到顶部的快速访问栏,而不是通常的设置选项卡。有关设置名称,请参见 modules/shared.py。需要重新启动才能应用",
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"If this values is non-zero, it will be added to seed and used to initialize RNG for noises when using samplers with Eta. You can use this to produce even more variation of images, or you can use this to match images of other software if you know what you are doing.": "如果这个值不为零,它将被添加到随机种子中,并在使用带有 Eta 的采样器时用于初始化随机噪声。你可以使用它来产生更多的图像变化,或者你可以使用它来模仿其他软件生成的图像,如果你知道你在做什么",
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"Autocomplete options": "自动补全选项",
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"Enable Autocomplete": "开启Tag补全",
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"Append commas": "附加逗号",
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"Allowed categories for random artists selection when using the Roll button": "使用抽选艺术家按钮时将会随机的艺术家类别",
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"Roll three": "抽三位出来",
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"Generate forever": "无限生成",
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"Cancel generate forever": "停止无限生成"
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}
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"Cancel generate forever": "停止无限生成",
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"History": "历史记录",
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"Show Textbox": "显示文本框",
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"File with inputs": "含输入内容的文件",
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"Prompts": "提示词",
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"Disabled when launched with --hide-ui-dir-config.": "启动 --hide-ui-dir-config 时禁用",
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"Upscaler 1": "放大算法 1",
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"Upscaler 2": "放大算法 2",
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"Open output directory": "打开输出目录",
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"Create aesthetic images embedding": "生成美术风格图集 embedding",
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"Split oversized images into two": "将过大的图像分为两份",
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"Train an embedding; must specify a directory with a set of 1:1 ratio images": "训练 embedding; 必须指定一组具有 1:1 比例图像的目录",
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"Learning rate": "学习率",
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"txt2img history": "文生图历史记录",
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"img2img history": "图生图历史记录",
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"extras history": "更多选项卡的历史记录",
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"extras": "更多",
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"custom fold": "自定义文件夹",
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"Load": "载入",
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"Prev batch": "上一批",
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"Next batch": "下一批",
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"number of images to delete consecutively next": "接下来要连续删除的图像数",
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"Date to": "日期至",
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"Refresh page": "刷新页面",
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"Unload VAE and CLIP from VRAM when training": "训练时从显存(VRAM)中取消 VAE 和 CLIP 的加载",
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"Number of pictures displayed on each page": "每页显示的图像数量",
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"Number of grids in each row": "每行显示多少格",
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"how fast should the training go. Low values will take longer to train, high values may fail to converge (not generate accurate results) and/or may break the embedding (This has happened if you see Loss: nan in the training info textbox. If this happens, you need to manually restore your embedding from an older not-broken backup).\n\nYou can set a single numeric value, or multiple learning rates using the syntax:\n\n rate_1:max_steps_1, rate_2:max_steps_2, ...\n\nEG: 0.005:100, 1e-3:1000, 1e-5\n\nWill train with rate of 0.005 for first 100 steps, then 1e-3 until 1000 steps, then 1e-5 for all remaining steps.": "训练应该多快。低值将需要更长的时间来训练,高值可能无法收敛(无法产生准确的结果)以及/也许可能会破坏 embedding(如果你在训练信息文本框中看到 Loss: nan 就会发生这种情况。如果发生这种情况,你需要从较旧的未损坏的备份手动恢复 embedding)\n\n你可以使用以下语法设置单个数值或多个学习率:\n\n 率1:步限1, 率2:步限2, ...\n\n如: 0.005:100, 1e-3:1000, 1e-5\n\n即前 100 步将以 0.005 的速率训练,接着直到 1000 步为止以 1e-3 训练,然后剩余所有步以 1e-5 训练"
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}
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