建立m文件draw_rectangle.m. 其中p生成矩形的个数 function draw_rectangle(p) t = 1; x = rand(1)*10; y = rand(1)*10; w = rand(1)*10; h = rand(1)*10; b =[x y w h]; rectangle('Position', b) a{t} =b; flag =1; while flag ==1 x = rand(1)*10; y = rand(1)*10; w = rand(1)*10
A rectangle is represented as a list [x1, y1, x2, y2], where (x1, y1) are the coordinates of its bottom-left corner, and (x2, y2) are the coordinates of its top-right corner. Two rectangles overlap if the area of their intersection is positive. To b
Given a list of non-overlapping axis-aligned rectangles rects, write a function pick which randomly and uniformily picks an integer point in the space covered by the rectangles. Note: An integer point is a point that has integer coordinates. A point
FFMpeg ver 20160219-git-98a0053 滤镜中英文对照 2016.02.21 by 1CM T.. = Timeline support 支持时间轴 .S. = Slice threading 分段线程 ..C = Command support 支持命令传送 A = Audio input/output 音频 输入/输出 V = Video input/output 视频 输入/输出 N = Dynamic number and/or type of input/out
FFMpeg ver 20160213-git-588e2e3 滤镜中英文对照 2016.02.17 by 1CM T.. = Timeline support 支持时间轴 .S. = Slice threading 分段线程 ..C = Command support 支持命令传送 A = Audio input/output 音频 输入/输出 V = Video input/output 视频 输入/输出 N = Dynamic number and/or type of input/out
常见的一种决策树算法是ID3,ID3的做法是每次选择当前最佳的特征来分割数据,并按照该特征所有可能取值来切分,也就是说,如果一个特征有四种取值,那么数据将被切分成4份,一旦按某特征切分后,该特征在之后的算法执行过程中将不会在起作用,这种切分方法比较迅速,但是一个比较明显的缺点是不能直接处理连续型的特征,只有事先将连续型的数据转换成离散型才能再ID3算法中使用. CART(Classification And Regression Tree)算法采用一种二分递归分割的技术,将当前的样本集分为两个子