=> 458 ,'attack_type'=> 1 ,'defense'=> 0 ,'anger...=> 418 ,'attack_type'=> 1 ,'defense'=> 0 ,'anger...=> 474 ,'attack_type'=> 1 ,'defense'=> 0 ,'anger...=> 456 ,'attack_type'=> 1 ,'defense'=> 0 ,'anger...=> 442 ,'attack_type'=> 1 ,'defense'=> 0 ,'anger
} js...//这里设定重力加速度为0.2/一帧 var gravity = 0.2; var speed_x_x, //横向加速度 speed_x_y, //纵向加速度 wind_anger...var eachAnger = 0.017453293; //获得风向的角度 wind_anger = OPTS.wind_direction * eachAnger; //...获得横向加速度 speed_x = this.speed * Math.cos(wind_anger); //获得纵向加速度 speed_y = - this.speed *...Math.sin(wind_anger); //绑定一个速度实例 this.vel = new Vector(wind_x, wind_y); }; Drop对象的update方法
图片和对应的xml) 图片数量(jpg文件个数):8279 标注数量(xml文件个数):8279 标注类别数:8 标注类别名称:["fear","sad","surprised","contempt","anger..."happy"] 每个类别标注的框数: fear count = 1035 sad count = 1035 surprised count = 1035 contempt count = 1035 anger...格式的txt文件,仅仅包含jpg图片和对应的xml) 图片数量(jpg文件个数):8197 标注数量(xml文件个数):8197 标注类别数:8 标注类别名称:["sad","disgust","anger...surprised","happy","fear","contempt","neutral"] 每个类别标注的框数: sad count = 1024 disgust count = 1025 anger...仅仅包含jpg图片和对应的xml) 图片数量(jpg文件个数):8038 标注数量(xml文件个数):8038 标注类别数:8 标注类别名称:["surprised","contempt","anger
Fear + Disgust print('情绪词语列表整理完成') print(Anger) 比如输出Anger生气的情绪词语,如下图所示。...情绪包括anger、disgust、fear、sadness、surprise、good、happy。...: anger+=freq anger_list.append(word) if word in Disgust:...: anger+=freq anger_list.append(word) tlist.append("anger")...Emotion Word Num 133 anger 气愤 1 382 anger 报仇 3 disgust Emotion Word Num 3
train['emotions'].apply(lambda x: [int(_i) for _i in x.split(',')]) train[['love', 'joy', 'fright', 'anger...) joy = self.out_joy(pooled_output) fright = self.out_fright(pooled_output) anger...pooled_output) return { 'love': love, 'joy': joy, 'fright': fright, 'anger...': anger, 'fear': fear, 'sorrow': sorrow, } 6.4 模型训练 回归损失函数直接选取 nn.MSELoss() EPOCHS = 1 # 训练轮数...= criterion(outputs['anger'], sample['anger'].to(device)) loss_fear = criterion(outputs['fear
We define the anger of the ii-th person as the number of people between him and the person , who makes...If there is no one who makes him angry , his anger is -1−1 ....Please calculate the anger of every team member ....Output A row of nn integers separated by spaces , representing the anger of every member .
标注数量(xml文件个数):9400 标注数量(txt文件个数):9400 标注类别数:8 标注类别名称(注意yolo格式类别顺序不和这个对应,而以labels文件夹classes.txt为准):["anger...","content","disgust","fear","happy","neutral","sad","surprise"] 每个类别标注的框数: anger 框数 = 1191 content 框数
为此,我们整理并清洗了一个包含 七种典型人脸表情 的数据集,覆盖了惊讶(Surprise)、恐惧(Fear)、厌恶(Disgust)、高兴(Happiness)、悲伤(Sadness)、愤怒(Anger...# Classes nc: 7 names: ["Surprise", "Fear", "Disgust", "Happiness", "Sadness", "Anger", "Neutral"] 数据集概述...22.6%) # Classes 配置文件(data.yaml) nc: 7 names: ["Surprise", "Fear", "Disgust", "Happiness", "Sadness", "Anger...数据集详情 | 表情类别 | | --------- | | Surprise | | Fear | | Disgust | | Happiness | | Sadness | | Anger
4066标注数量(xml文件个数):4066标注数量(txt文件个数):4066标注类别数:8标注类别名称(注意yolo格式类别顺序不和这个对应,而以labels文件夹classes.txt为准):["anger...","beg","frightened","happy","scare","sick","sleepy","wonder"]每个类别标注的框数:anger 框数 = 501beg 框数 = 422frightened
数据集使用了AffectNet表情数据集,支持五种表情识别,分别是: ('neutral', 'happy', 'sad', 'surprise', 'anger') 输入格式:NCHW=1x3x64x64...9model_bin = "emotions-recognition-retail-0003.bin" 10 11labels = ['neutral', 'happy', 'sad', 'surprise', 'anger...'] 12emotion_labels = ["neutral","anger","disdain","disgust","fear","happy","sad","surprise"] 13 14emotion_net
暂时先不管他了 将ty_sentiment <- get_nrc_sentiment((lyrics_text))运行完得到了一个数据框 > head(ty_sentiment) anger anticipation...sentimentscores) rownames(sentimentscores) <- NULL 最终的数据集长这个样子 > sentimentscores sentiment Score 1 anger..."#009E73", "2012" = "#CC79A7", "2014" = "#D55E00", "2017" = "#00D6C9", "anger
In [37]: prompt = f""" Is the writer of the following review expressing anger?...Format the Anger value as a boolean....lamp_review}''' """ response = get_completion(prompt) print(response) { "Sentiment": "positive", "Anger...将您的响应格式化为 JSON 对象,以 “Sentiment”、“Anger”、“Item” 和 “Brand” 作为键。 如果信息不存在,请使用 “未知” 作为值。 让你的回应尽可能简短。...将 Anger 值格式化为布尔值。
double disgust = emotion.getDouble("disgust"); 62 mapp.put("厌恶", disgust); 63 double anger...= emotion.getDouble("anger"); 64 mapp.put("愤怒", anger); 65 double happiness = emotion.getDouble...="display:none;"/> 48 49 50 51 js.../jquery-1.11.3.min.js"> 52 js/sg.js"> 53 js/sgutil.js..."> 54 js"> 55 <script type
abandon fear ## 3 abandon negative ## 4 abandon sadness ## 5 abandoned anger...abandoned fear ## 7 abandoned negative ## 8 abandoned sadness ## 9 abandonment anger...source sentiment total_words words ## ## 1 Android anger...parameter conf.low ## (chr) (dbl) (dbl) (dbl) (dbl) (dbl) ## 1 anger
JS加密、JS混淆,是一回事吗?是的!在国内,JS加密,其实就是指JS混淆。...1、当人们提起JS加密时,通常是指对JS代码进行混淆加密处理,而不是指JS加密算法(如xor加密算法、md5加密算法、base64加密算法,等等...)2、而“JS混淆”这个词,来源于国外的称呼,在国外称为...所以,有的人用国外的翻译名称,称为js混淆。3、无论是js加密,还是js混淆,他们的功能,都是对js代码进行保护,使可读的明文js代码变的不可读,防护自己写的js代码被他人随意阅读、分析、复制盗用。...,js是直接执行源码、对外发布也是源码),所以,为了提升js代码安全性,就有了js加密、js混淆操作。...加密后的js代码,不一定能保证100%安全了,但肯定比不加密强,很简单的道理。6、怎样进行js加密、js混淆?
* * 粒子半径 */ private float radius; /** * 粒子初始位置的角度 */ private double anger...且一个粒子具有随机的半径,透明度,速度等,通过init()方法,实现初始化粒子如下 public void init(Random random, float viewRadius) { anger...random.nextFloat() * 2F; radius = random.nextInt(6) + 5; mX = (float) (viewRadius * Math.cos(anger...)); mY = (float) (viewRadius * Math.sin(anger)); //随机偏移角度-30°~30° randomAnger...random, float viewRadius) { //每一帧偏移的像素大小 float distance = 1F; double moveAnger = anger
如何在 JavaScript 中引用 JS 脚本 在 JavaScript 中引用外部 JS 脚本有两种主要方法: 使用 标签 这是最简单的方法,通过在 HTML 页面中插入... 标签来引用 JS 脚本: 其中 src 属性指定要引用的脚本文件的路径。...动态创建并插入 元素: const script = document.createElement("script"); script.src = "script.js
还是在ajax的过程中调用这个对象的属性 发现属性的值并不会随着cookie的变化而变话 还是保持老值