Diff Two Arrays

数组差集计算
本文介绍了一个简单的JavaScript函数,用于计算两个数组之间的差集,并通过一个示例展示了其使用方法。
function diff(arr1, arr2) {
  var newArr = [];
  // Same, same; but different.
  var a = arr1.filter(function(e){
    return arr2.indexOf(e) < 0;
  });
  var b = arr2.filter(function(e){
    return arr1.indexOf(e) < 0;
  });
  newArr = a.concat(b);
  return newArr;
}

diff([1, 2, 3, 5], [1, 2, 3, 4, 5]);

 

转载于:https://www.cnblogs.com/mengruying/p/6186200.html

Objectives of this Assignment 1. Declare arrays of different types dynamically. 2. Iterate through arrays, processing all of the elements. 3. Write methods with arrays as parameters and return values In this assignment you will create your own class and write the methods in it. The class you write is called P7_2 and it has four methods that build arrays and four methods that process arrays. All methods should be public and static. Create a project called P7_2 and a class named Main in a file called Main.java, then follow the instructions below exactly: 1.Write a method named createDoubles that builds an array of floating point values that represent the squares of the numbers from start to end, in steps of 0.5, inclusive of both boundaries. The numbers start and end should be readed from the starndard input.See the sample input for details. The method has no parameters and returns an array of doubles. You should calculate the length of this array. 2.Write a method called findLargest that takes an array of doubles as a parameter, and returns a double equal to the largest element in the array. 3.Add a main method with the usual signature that instantiates the Main class and tests its methods as follow: public static void main(String[] args) { // Create arrays double[] doubleArray = createDoubles(); // Test processing System.out.printf("%.1f", findLargest(doubleArray)); } Input Specification: enter two numbers which indicates the start number and the end number. Output Specification: For each case, output the largest number in the created array. Sample Input: 10.0 13.0 Sample Ouput: 169.0
03-10
一、数据采集层:多源人脸数据获取 该层负责从不同设备 / 渠道采集人脸原始数据,为后续模型训练与识别提供基础样本,核心功能包括: 1. 多设备适配采集 实时摄像头采集: 调用计算机内置摄像头(或外接 USB 摄像头),通过OpenCV的VideoCapture接口实时捕获视频流,支持手动触发 “拍照”(按指定快捷键如Space)或自动定时采集(如每 2 秒采集 1 张),采集时自动框选人脸区域(通过Haar级联分类器初步定位),确保样本聚焦人脸。 支持采集参数配置:可设置采集分辨率(如 640×480、1280×720)、图像格式(JPG/PNG)、单用户采集数量(如默认采集 20 张,确保样本多样性),采集过程中实时显示 “已采集数量 / 目标数量”,避免样本不足。 本地图像 / 视频导入: 支持批量导入本地人脸图像文件(支持 JPG、PNG、BMP 格式),自动过滤非图像文件;导入视频文件(MP4、AVI 格式)时,可按 “固定帧间隔”(如每 10 帧提取 1 张图像)或 “手动选择帧” 提取人脸样本,适用于无实时摄像头场景。 数据集对接: 支持接入公开人脸数据集(如 LFW、ORL),通过预设脚本自动读取数据集目录结构(按 “用户 ID - 样本图像” 分类),快速构建训练样本库,无需手动采集,降低系统开发与测试成本。 2. 采集过程辅助功能 人脸有效性校验:采集时通过OpenCV的Haar级联分类器(或MTCNN轻量级模型)实时检测图像中是否包含人脸,若未检测到人脸(如遮挡、侧脸角度过大),则弹窗提示 “未识别到人脸,请调整姿态”,避免无效样本存入。 样本标签管理:采集时需为每个样本绑定 “用户标签”(如姓名、ID 号),支持手动输入标签或从 Excel 名单批量导入标签(按 “标签 - 采集数量” 对应),采集完成后自动按 “标签 - 序号” 命名文件(如 “张三
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