Ubuntu
155 lines
4.1 KiB
Markdown
155 lines
4.1 KiB
Markdown
# paper-recognizer — 微信小程序尿检试纸识别
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纯 JavaScript 实现，零依赖，约 40KB。复制即用。
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## 文件说明
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```
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miniapp/
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├── paper-recognizer.js # 核心识别引擎（唯一必需文件）
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└── README.md
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```
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## 快速集成
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### 1. 复制文件
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将 `paper-recognizer.js` 放入小程序项目的 `utils/` 目录。
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### 2. 页面引入
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```javascript
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// pages/recognize/recognize.js
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const { PaperRecognizer } = require('../../utils/paper-recognizer.js');
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const recognizer = new PaperRecognizer();
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```
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### 3. 拍照识别
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```javascript
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Page({
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data: { result: null },
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// 拍照
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onTakePhoto() {
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wx.chooseImage({
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count: 1,
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sourceType: ['camera'],
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success: (res) => this.doRecognize(res.tempFilePaths[0])
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});
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},
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// 识别
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doRecognize(filePath) {
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wx.getImageInfo({
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src: filePath,
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success: (info) => {
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// 建议长边超过 1500px 时先缩放，保证性能
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const maxLen = 1500;
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let w = info.width, h = info.height;
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if (Math.max(w, h) > maxLen) {
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const scale = maxLen / Math.max(w, h);
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w = Math.round(w * scale);
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h = Math.round(h * scale);
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}
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// 离屏 Canvas 获取像素
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const ctx = wx.createCanvasContext('offscreenCanvas', this);
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ctx.drawImage(filePath, 0, 0, w, h);
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ctx.draw(false, () => {
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wx.canvasGetImageData({
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canvasId: 'offscreenCanvas',
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x: 0, y: 0, width: w, height: h,
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success: (res) => {
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const rgba = new Uint8Array(res.data);
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const result = this.recognizer.recognize(rgba, w, h);
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if (result.success) {
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console.log('试纸类型:', result.paperType);
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console.log('色块数量:', result.itemCount);
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console.log('定位块颜色:', result.locatorColor);
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console.log('颜色数据:', result.colors);
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} else {
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console.error('识别失败:', result.errorCode, result.errorMessage);
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}
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}
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});
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});
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}
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});
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}
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});
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```
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### 3. 相册选图识别
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```javascript
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wx.chooseImage({
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count: 1,
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sourceType: ['album'],
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success: (res) => this.doRecognize(res.tempFilePaths[0])
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});
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```
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## 识别结果字段
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| 字段 | 类型 | 说明 |
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|------|------|------|
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| `success` | boolean | 是否成功 |
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| `errorCode` | number | 错误码（成功为 0） |
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| `errorMessage` | string | 错误描述 |
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| `paperType` | string | 试纸类型，如 "14_S", "11_L" |
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| `itemCount` | number | 色块数量 |
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| `locatorColor` | string | 定位块颜色 "Red"/"Green"/"Blue" |
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| `smallLocatorOnLeft` | boolean | 小定位块是否在左侧 |
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| `blurLevel` | string | 清晰度 "None"/"Slight"/"Severe" |
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| `blurScore` | number | 清晰度分数（越高越清晰，>300 为 None） |
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| `colors` | array | 色块颜色数组 `[{id, r, g, b}, ...]` |
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## 错误码
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| 码 | 含义 |
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|----|------|
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| 0 | 成功 |
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| -1 | 未找到定位块 |
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| -2 | 定位块配对失败 |
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| -3 | 定位块颜色不一致 |
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| -4 | 未找到匹配的试纸配置 |
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| -5 | 未知试纸类型 |
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## 性能参考
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| 图片分辨率 | 预估耗时 | 建议 |
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|-----------|---------|------|
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| < 800×100 | < 20ms | 直接处理 |
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| ~1100×400 | ~150ms | 直接处理 |
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| ~2500×1100 | ~600ms | 建议缩放到 1500px |
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| > 3000px | > 1s | 必须缩放 |
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## 注意事项
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1. **Canvas 必须存在于 WXML 中** — 即使隐藏也要声明：
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```html
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<canvas canvas-id="offscreenCanvas"
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style="position:fixed;top:-9999px;left:-9999px;width:750px;height:750px;">
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</canvas>
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```
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2. **拍照时保持试纸平整** — 严重透视变形或大角度旋转可能导致识别失败。
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3. **光照均匀** — 算法使用 HSV 颜色分割，极端光照（强反光、暗光）下定位块可能漏检。
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4. **仅支持 14/11/8 项试纸** — 支持短型(S)和长型(L)两种规格。
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## 试纸类型清单
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| paperType | itemCount | 说明 |
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|-----------|-----------|------|
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| 14_S | 14 | 14 项短型 |
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| 14_L | 14 | 14 项长型 |
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| 11_S | 11 | 11 项短型 |
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| 11_L | 11 | 11 项长型 |
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| 8_S | 8 | 8 项短型 |
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| 8_L | 8 | 8 项长型 |
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