Merge branch 'pr/3915' into add-updated-content-3

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dtlnor 2022-11-03 14:33:17 +09:00
commit 934fdd0408

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@ -502,7 +502,7 @@
"keep whatever was there originally": "保留原来的图像,不进行预处理",
"fill it with latent space noise": "用潜空间的噪声填充它",
"fill it with latent space zeroes": "用潜空间的零填充它",
"Upscale masked region to target resolution, do inpainting, downscale back and paste into original image": "将蒙版区域放大到目标分辨率,做局部重绘,缩小后粘贴到原始图像中。请注意,填补像素 仅对 全分辨率局部重绘 生效。",
"Upscale masked region to target resolution, do inpainting, downscale back and paste into original image": "将蒙版区域放大到目标分辨率,做局部重绘,缩小后粘贴到原始图像中。\n请注意,填补像素 仅对 全分辨率局部重绘 生效。",
"Resize image to target resolution. Unless height and width match, you will get incorrect aspect ratio.": "将图像大小调整为目标分辨率。除非高度和宽度匹配,否则你将获得不正确的纵横比",
"Resize the image so that entirety of target resolution is filled with the image. Crop parts that stick out.": "调整图像大小,使整个目标分辨率都被图像填充。裁剪多出来的部分",
"Resize the image so that entirety of image is inside target resolution. Fill empty space with image's colors.": "调整图像大小,使整个图像在目标分辨率内。用图像的颜色填充空白区域",
@ -560,6 +560,7 @@
"Unload VAE and CLIP from VRAM when training": "训练时从显存(VRAM)中取消 VAE 和 CLIP 的加载",
"Number of pictures displayed on each page": "每页显示的图像数量",
"Number of grids in each row": "每行显示多少格",
"Start drawing": "开始绘制",
"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",
"Separate prompts into parts using vertical pipe character (|) and the script will create a picture for every combination of them (except for the first part, which will be present in all combinations)": "用竖线分隔符(|)将提示词分成若干部分,脚本将为它们的每一个组合创建一幅图片(除了被分割的第一部分,所有的组合都会包含这部分)",
@ -569,5 +570,22 @@
"favorites": "收藏夹(已保存)",
"others": "其他",
"Collect": "收藏(保存)",
"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)"
"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)",
"How many times to improve the generated image iteratively; higher values take longer; very low values can produce bad results": "迭代改进生成的图像多少次;更高的值需要更长的时间;非常低的值会产生不好的结果",
"Draw a mask over an image, and the script will regenerate the masked area with content according to prompt": "在图像上画一个蒙版,脚本会根据提示重新生成蒙版区域的内容",
"Upscale image normally, split result into tiles, improve each tile using img2img, merge whole image back": "正常提升图像将结果分割成瓦片用img2img改进每个瓦片将整个图像合并回来",
"Create a grid where images will have different parameters. Use inputs below to specify which parameters will be shared by columns and rows": "创建一个网格,图像将有不同的参数。使用下面的输入来指定哪些参数将由列和行共享",
"Run Python code. Advanced user only. Must run program with --allow-code for this to work": "运行Python代码。仅限高级用户。必须用 --allow-code 来运行程序,这样才能工作。",
"Separate a list of words with commas, and the first word will be used as a keyword: script will search for this word in the prompt, and replace it with others": "用逗号隔开一个单词列表,第一个单词将被用作关键词:脚本将在提示中搜索这个单词,并用其他单词替换它。",
"Separate a list of words with commas, and the script will make a variation of prompt with those words for their every possible order": "用逗号分开一个单词列表,脚本将用这些单词的每一个可能的顺序制作一个变体的提示。",
"Reconstruct prompt from existing image and put it into the prompt field.": "从现有的图像中重构提示,并将其放入提示字段。",
"Set the maximum number of words to be used in the [prompt_words] option; ATTENTION: If the words are too long, they may exceed the maximum length of the file path that the system can handle": "在[prompt_words]选项中设置要使用的最大字数;注意:如果字数太长,可能会超过系统可处理的文件路径的最大长度",
"Process an image, use it as an input, repeat.": "处理一张图片,将其作为输入,重复。",
"Insert selected styles into prompt fields": "在提示字段中插入选定的样式",
"Save current prompts as a style. If you add the token {prompt} to the text, the style use that as placeholder for your prompt when you use the style in the future.": "将当前的提示语保存为样式。如果你在文本中添加标记{prompt},当你将来使用该样式时,该样式会将其作为你的提示的占位符。",
"Loads weights from checkpoint before making images. You can either use hash or a part of filename (as seen in settings) for checkpoint name. Recommended to use with Y axis for less switching.": "在制作图像之前从检查点加载权重。你可以使用哈希值或文件名的一部分如设置中所示作为检查点名称。建议与Y轴一起使用以减少切换。",
"Torch active: Peak amount of VRAM used by Torch during generation, excluding cached data.\nTorch reserved: Peak amount of VRAM allocated by Torch, including all active and cached data.\nSys VRAM: Peak amount of VRAM allocation across all applications / total GPU VRAM (peak utilization%).": "Torch active: 在生成过程中Torch使用的显存(VRAM)峰值,不包括缓存的数据。\nTorch reserved: Torch分配的显存(VRAM)的峰值量,包括所有活动和缓存数据。\nSys VRAM: 所有应用程序的显存(VRAM)分配的峰值量 / GPU的总显存(VRAM)(峰值利用率%)。",
"Uscale the image in latent space. Alternative is to produce the full image from latent representation, upscale that, and then move it back to latent space.": "缩放潜在空间中的图像。另一种方法是,从潜在表示中产生完整的图像,提高其比例,然后再将其移回潜在空间。",
"----": "----"
}