model_train_dm/backend/apps/algorithms/templates/time_predict.html
2026-07-27 17:51:49 +08:00

58 lines
2.2 KiB
HTML

<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>API Result</title>
</head>
<body>
<h1>某机场乘客数量变化趋势预测</h1>
<!-- Container for the image result -->
<div id="result-container"></div>
<script>
// Function to make a GET request to the API using Fetch
function fetchData() {
fetch('http://192.168.1.13:8000/server/time_predict/')
.then(response => {
if (!response.ok) {
throw new Error('网络响应不正常');
}
return response.json();
})
.then(data => {
// 记录整个响应对象
console.log(data);
// 解析 JSON 数据
let data1 = JSON.parse(data);;
// 获取结果容器
const resultContainer = document.getElementById('result-container');
// 检查 data.image 是否已定义
if (data1 && data1.image) {
// 创建一个图像容器,并将 base64 编码的图像添加到容器中
const imageContainer = document.createElement('div');
imageContainer.innerHTML = `<img src="data:image/png;base64, ${data1.image}"
style="width: auto; height: auto; max-width: 100%;" alt="检测结果" onclick="openModal(this)">`;
// 将图像容器添加到结果容器中
resultContainer.appendChild(imageContainer);
} else {
console.error("响应结果中没有 'image' 属性或 'image' 属性值为空。");
}
})
.catch(error => {
console.error('在获取操作中发生错误:', error);
});
}
// Call the fetchData function when the page loads
fetchData();
</script>
</body>
</html>