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"游戏图形与运行时", "origin": "explicit", "humanReviewed": true, "context": "Unity中的“Image & Raw Image”导航项", "citation": "https://www.pystone.net/notes/game-graphics-and-runtime/#unity" } ], "contentMarkdown": "# Image & Raw Image\n> 创建时间：2020/9/9 11:51\n\n## Image & Raw Image\n\n * Image & Raw Image\n * Image\n * 特点\n * 属性\n * Image Type\n * Simple\n * Sliced\n * Tilled\n * Filled\n * Raw Image\n * 特点\n * 属性\n * Ref\n\n## Image\n\n### 特点\n\n而Image提供了四种ImageType：Simple（普通）、Sliced（切割）、Tiled（平铺）、Filled（填充），而且它还是布局元素（ILayoutElement），可以被各种布局组（ILayoutGroup）所包含，将它和其他布局元素进行布局。\n\n### 属性\n\nSource Image：只支持Sprite类型的图片\nColor：给图片混合上颜色\nMaterial：材质(一些特殊情况需要使用材质)\nRaycast Target：是否接收射线检测\nImage Type：图片类型(普通，九宫切图，平铺，填充)\nPreserve Aspect：是否保持宽高比\nSet Native Size：设置元素为原本的像素大小\n\n#### Image Type\n\n##### Simple\n\n随意拉伸，会变形，可以勾选上PreserveAspect按原宽高比进行拉伸\n\n##### Sliced\n\n按照Sprite Editor中的九宫格进行拉伸处理\n\n![Alt text](assets/20200103131209912.png)\n\n1，3，7，9区域不会进行拉伸，2和8区域会横向拉伸，4和6区域会纵向拉伸，5区域横纵都会拉伸\n\n##### Tilled\n\n图片本身大小会保持不变，像铺地面砖那样填充满整个Image控件\n\n![Alt text](assets/20200103132414236.png)\n\n##### Filled\n\n图片以不同的方式呈现出来，例如技能冷却，血条，进度条\n\n## Raw Image\n\n> the Image control requires its Texture to be a Sprite\n> the Raw Image can accept any Texture.\n\n### 特点\n\nraw: 生的，未加工的\n支持任何一种贴图模式，包括Render Texture和Movie Texture\n只为我们提供了修改UV的方法，除此之外都是继承自MaskableGraphic的方法\n\n> DefaultTexture类型会将贴图宽和高转换为2的n次幂\n> Sprite类型不会对宽和高进行自动拉伸，可以在Inspector—Advanced—Non—Power of 2选择是否进行转换\n\n### 属性\n\nColor\nMaterial\nRaycast Target\nUV Rect：设置UV缩放和偏移(x和y属性用于控制UV左右、上下偏移，W和H属性用于控制UV的重复次数)\n\n> 可以在Import Settings中的Wrap Model设置循环的模式，Repeat模式可以用于2D游戏的背景图循环\n\nSet Native Size：设置元素为原本的像素大小\n\n## Ref\n\n\n[/article/details/103807887?utm_medium=distribute.pc_relevant.none-task-blog-BlogCommendFromMachineLearnPai2-3.channel_param&depth_1-utm_source=distribute.pc_relevant.none-task-blog-BlogCommendFromMachineLearnPai2-3.channel_param”>https://blog.csdn.net/LLLLL/article/details/103807887?utm_medium=distribute.pc_relevant.none-task-blog-BlogCommendFromMachineLearnPai2-3.channel_param&depth_1-utm_source=distribute.pc_relevant.none-task-blog-BlogCommendFromMachineLearnPai2-3.channel_param](http://\"https://blog.csdn.net/LLLLL