The Changes in Our School

校园变化记
本文讲述了作者所在中学发生的变化,包括学校规模扩大、操场变得更加宽敞美丽,学生们更加尊重老师且学习积极性提高等内容。

  Now our school is more beautiful, we are more polite to our teachers and we like to study very much. I think our school has changed in many ways.

  The playground is much bigger and more beautiful than before. Many boys play football there after school.And many girls play games there.They are very happy.

I’m a student in a middle school. I want to tell you that our school has changed a lot . Our school is much bigger than before. There also is a big garden now.And many trees and flowers are there. we can sit and relax ourselves there.

  Now we are in Grade 3, we have to study harder than before. Students do their homework in their free time.I think it is good, but taking some exercise is important, too.

Frame-independent movement If you run everything we have done so far, you will be able to move the circle, but it won't move uniformly. It will probably be very fast, because currently we have done the movement in a very naive way. Right now your computer will be running the update() function as fast as it can, which means it will probably call it a couple of hundreds of times each second, if not more. If we move the shape by one pixel for every frame, this can count up to several 100 pixels every second, making our little player fly all over the screen. You cannot just change the movement value to something lower, as it will only fix the problem for your computer. If you move to a slower or faster computer, the speed will change again. So how do we solve this? Well, let's look at the problem we are facing. We are having a problem because our movement is frame-dependent. We want to provide the speed in a way that changes depending on the time a frame takes. There is a simple formula you should remember from your old school days. It's the formula that goes: distance = speed * time. Now why is this relevant for us? Because with this formula we can calculate a relevant speed for every frame, so that the circle always travels exactly the distance we want it to travel over one second, no matter what computer we are sitting on. So let's modify the function to what we actually need to make this work. void Game::update(sf::Time deltaTime) { sf::Vector2f movement(0.f, 0.f); if (mIsMovingUp) movement.y -= PlayerSpeed; if (mIsMovingDown) movement.y += PlayerSpeed; if (mIsMovingLeft) movement.x -= PlayerSpeed; if (mIsMovingRight) movement.x += PlayerSpeed; mPlayer.move(movement * deltaTime.asSeconds()); } The major difference we have made here is that we now receive a time value every time we call the update. We calculate the distance we want to travel every frame, depending on how much time has elapsed. We call the time that has elapsed since the last frame delta time (or time step), and often abbreviate it as dt in the code. But how do we get this time? We are lucky because SFML provides the utilities for it.翻译
03-08
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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