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| author | dtlnor <dtlnor@hotmail.com> | 2022-10-24 04:22:43 +0900 |
|---|---|---|
| committer | AUTOMATIC1111 <16777216c@gmail.com> | 2022-10-26 13:17:21 +0300 |
| commit | f9b20482fc5f71a5efead408a4006e73471fa1bc (patch) | |
| tree | ba1ebe2605b7d8883e8cf29ec4e9a3b91bd305b0 | |
| parent | c7e000bedde0d8fbf50ecd7601cb8344f0ec2202 (diff) | |
Update zh-hans.json
| -rw-r--r-- | localizations/zh-hans.json | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/localizations/zh-hans.json b/localizations/zh-hans.json index 6276f573..e206da88 100644 --- a/localizations/zh-hans.json +++ b/localizations/zh-hans.json @@ -55,7 +55,7 @@ "Width": "宽度", "Height": "高度", "Restore faces": "面部修复", - "Tiling": "分块(Tiling)", + "Tiling": "可平铺(Tiling)", "Highres. fix": "高分辨率修复", "Firstpass width": "第一遍的宽度", "Firstpass height": "第一遍的高度", @@ -427,7 +427,7 @@ "Which algorithm to use to produce the image": "使用哪种算法生成图像", "Euler Ancestral - very creative, each can get a completely different picture depending on step count, setting steps to higher than 30-40 does not help": "Euler Ancestral - 非常有创意，可以根据迭代步数获得完全不同的图像，将迭代步数设置为高于 30-40 不会有正面作用", "Denoising Diffusion Implicit Models - best at inpainting": "Denoising Diffusion Implicit models - 最擅长内补绘制", - "Produce an image that can be tiled.": "生成可以分块(Tiling)的图像", + "Produce an image that can be tiled.": "生成可用于平铺(tiled)的图像", "Use a two step process to partially create an image at smaller resolution, upscale, and then improve details in it without changing composition": "使用两步处理的时候以较小的分辨率生成初步图像、接着放大图像，然后在不更改构图的情况下改进其中的细节", "Determines how little respect the algorithm should have for image's content. At 0, nothing will change, and at 1 you'll get an unrelated image. With values below 1.0, processing will take less steps than the Sampling Steps slider specifies.": "决定算法对图像内容的影响程度。设置 0 时，什么都不会改变，而在 1 时，你将获得不相关的图像。值低于 1.0 时，处理的迭代步数将少于“采样迭代步数”滑块指定的步数", "How many batches of images to create": "创建多少批次的图像", |