2021-01-26

解决无法将回调函数中的值赋给定义的变量


本人目标:需要将通过bold转成的base64给自己所定义的变量赋值(说白了就是回调函数之外获取base64)

// 回调中base64 赋值 定义的变量 ,无法在回调之外获取变量
var reader = new window.FileReader();
        reader.readAsDataURL(bold);
        reader.onloadend = function() {
          var base64=reader.result.split(',')[1];
        }

此处的问题:

1.为了一个base64一直在回调内部掉函数。(代码不是很易懂)
2.当逻辑需要多个bold同时转base64,向后台传送一个base64的list。(显然有点恶心)

解决办法:

Promise 对象

个人理解:是一个能接受异步的消息,并获取异步结果(以下为Promise详细介绍地址)

详细地址:https://www.runoob.com/w3cnote/javascript-promise-object.html

使用Promise实现bold转base64

  blobToBase64(blob) {
      return new Promise((resolve, reject) => {
        const fileReader = new FileReader();
        fileReader.onload = (e) => {
          resolve(e.target.result.split(',')[1]);
        };
        // readAsDataURL
        fileReader.readAsDataURL(blob);
         fileReader.onerror = () => {
           reject(new Error('blobToBase64 error'));
         };
      });
    },
2021-03-26 20:54:33,596 - Model - INFO - Epoch 1 (1/200): 2021-03-26 20:57:40,380 - Model - INFO - Train Instance Accuracy: 0.571037 2021-03-26 20:58:16,623 - Model - INFO - Test Instance Accuracy: 0.718528, Class Accuracy: 0.627357 2021-03-26 20:58:16,623 - Model - INFO - Best Instance Accuracy: 0.718528, Class Accuracy: 0.627357 2021-03-26 20:58:16,623 - Model - INFO - Save model... 2021-03-26 20:58:16,623 - Model - INFO - Saving at log/classification/pointnet2_msg_normals/checkpoints/best_model.pth 2021-03-26 20:58:16,698 - Model - INFO - Epoch 2 (2/200): 2021-03-26 21:01:26,685 - Model - INFO - Train Instance Accuracy: 0.727947 2021-03-26 21:02:03,642 - Model - INFO - Test Instance Accuracy: 0.790858, Class Accuracy: 0.702316 2021-03-26 21:02:03,642 - Model - INFO - Best Instance Accuracy: 0.790858, Class Accuracy: 0.702316 2021-03-26 21:02:03,642 - Model - INFO - Save model... 2021-03-26 21:02:03,643 - Model - INFO - Saving at log/classification/pointnet2_msg_normals/checkpoints/best_model.pth 2021-03-26 21:02:03,746 - Model - INFO - Epoch 3 (3/200): 2021-03-26 21:05:15,349 - Model - INFO - Train Instance Accuracy: 0.781606 2021-03-26 21:05:51,538 - Model - INFO - Test Instance Accuracy: 0.803641, Class Accuracy: 0.738575 2021-03-26 21:05:51,538 - Model - INFO - Best Instance Accuracy: 0.803641, Class Accuracy: 0.738575 2021-03-26 21:05:51,539 - Model - INFO - Save model... 2021-03-26 21:05:51,539 - Model - INFO - Saving at log/classification/pointnet2_msg_normals/checkpoints/best_model.pth 我有类似于这样的一段txt文件,请你帮我写一段代码来可视化这些训练结果
02-06
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值