上传Base64格式的工件图片和物料草图,进行AI识别并返回统计结果
完整 URL
http://8.148.151.8:4001/api/process_image分类
| 字段名 | 类型 | 必填 | 说明 | 示例 |
|---|---|---|---|---|
| documentNumber | string | 是 | 批次号,唯一标识一次识别任务 | DOC20250117001 |
| workImage | string | 是 | 工件图片,Base64 编码,格式:data:image/jpeg;base64,... | data:image/jpeg;base64,/9j/4AAQSkZJRg... |
| materials | array | 是 | 物料列表,包含草图和理论数量 | [{"materialCode":"8884X-120","simpleImage":"data:image/jpeg;base64,...","theoreticalQuantity":100}] |
| 字段名 | 类型 | 必填 | 说明 | 示例 |
|---|---|---|---|---|
| materialCode | string | 是 | 物料编号/型号 | 8884X-120 |
| simpleImage | string | 是 | 草图,Base64 编码 | data:image/jpeg;base64,iVBORw0KGgo... |
| theoreticalQuantity | number | 是 | 理论数量 | 100 |
{
"documentNumber": "DOC20250117001",
"visualizationImagePath": "out_imgs/visualization/1.jpg",
"processedResults": [
{
"materialCode": "8884X-120",
"theoreticalQuantity": 100,
"actualQuantity": 95
}
]
}// POST 请求示例
const response = await fetch('http://8.148.151.8:4001/api/process_image', {
method: 'POST',
headers: {
'Content-Type': 'application/json'
},
body: JSON.stringify({
"documentNumber": "DOC20250117001",
"workImage": "data:image/jpeg;base64,/9j/4AAQSkZJRg...",
"materials": [
{
"materialCode": "8884X-120",
"simpleImage": "data:image/jpeg;base64,...",
"theoreticalQuantity": 100
}
]
})
});
const data = await response.json();
console.log(data);