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quyixiao
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@ -1,41 +1,504 @@
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package com.heyu.api.controller.car;
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import com.heyu.api.baidu.handle.traffic.BLicensePlateHandle;
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import com.heyu.api.baidu.request.traffic.BLicensePlateRequest;
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import com.heyu.api.controller.BaseController;
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import com.heyu.api.controller.ocr.BaiduOcrResult;
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import com.heyu.api.controller.AbstractRecognizeController;
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import com.heyu.api.controller.BaiduOcrError;
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import com.heyu.api.data.annotation.EbAuthentication;
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import com.heyu.api.data.annotation.NotIntercept;
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import com.heyu.api.data.constants.ApiConstants;
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import com.heyu.api.data.utils.ImageInputUtils;
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import com.heyu.api.data.utils.ImageInputUtils.ResolvedImageInput;
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import com.heyu.api.data.utils.R;
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import com.heyu.api.data.utils.StringUtils;
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import com.heyu.api.request.car.LicensePlateRecognizeRequest;
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import org.springframework.beans.factory.annotation.Autowired;
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import com.heyu.api.resp.car.RecognizeLicensePlateResp;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.web.bind.annotation.PostMapping;
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import org.springframework.web.bind.annotation.RequestBody;
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import org.springframework.web.bind.annotation.RequestMapping;
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import org.springframework.web.bind.annotation.RestController;
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import java.util.Collections;
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import java.util.HashMap;
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import java.util.List;
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import java.util.Map;
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/**
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* 车牌识别控制器
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* <p>
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* <b>接口背景</b>：用于交通运输、停车场、物流车队等场景，将照片中的车牌号码自动识别为结构化文本，
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* 替代人工录入。底层对接百度智能云文字识别「车牌识别」能力，由本服务完成参数校验、请求转发与字段映射。
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* </p>
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* <p>
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* 支持识别：中国大陆机动车蓝牌、黄牌（单双行）、绿牌、大型新能源（黄绿）、领使馆车牌、警牌、武警牌（单双行）、
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* 军牌（单双行）、港澳出入境车牌、农用车牌、民航车牌。
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* </p>
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*
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* <h3>百度官方文档</h3>
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* <ul>
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* <li>产品文档：<a href="https://cloud.baidu.com/doc/OCR/s/ck3h7y191">车牌识别</a></li>
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* <li>接口地址：{@code POST https://aip.baidubce.com/rest/2.0/ocr/v1/license_plate}</li>
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* </ul>
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*
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* <h3>本服务接口</h3>
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* <ul>
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* <li>路径：{@code POST /car/license/plate/recognize}</li>
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* <li>Content-Type：{@code application/json}（{@code @RequestBody}）</li>
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* <li>鉴权：{@link EbAuthentication}（Tencent 鉴权头，见项目网关配置）</li>
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* </ul>
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*
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* <h3>请求参数（{@link LicensePlateRecognizeRequest}）</h3>
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* <ul>
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* <li>imageUrlOrBase64：HTTP(S) 链接或 Base64 字符串，服务端自动识别（支持 jpg/jpeg/png/bmp）</li>
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* </ul>
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*
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* <h3>响应结构（{@link RecognizeLicensePlateResp}）</h3>
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* <ul>
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* <li>plateNumber 车牌号码 / confidence 号码置信度</li>
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* <li>plateType 车牌类型（小型汽车 / 新能源车 / 大型汽车 / 警车 / ...）</li>
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* <li>plateTypeConfidence 类型置信度（由号码置信度推导）</li>
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* <li>plateColor 车牌颜色（蓝 / 绿 / 黄 / 黄绿 / 白 / 黑）</li>
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* </ul>
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*
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* <h3>返回约定（重要）</h3>
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* <ul>
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* <li>一律 {@code R.ok()}；入参校验失败、平台异常、识别结果为空等情况，将说明写入 {@code msg}，
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* {@code data} 可能为空或字段不全（对外不暴露「百度」字样，日志内可排查）</li>
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* <li>入参校验失败时<strong>未调用百度、不计费</strong></li>
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* <li>多车牌场景默认取置信度最高的"主车牌"返回</li>
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* </ul>
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*
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* @author heyu
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* @since 1.0.0
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* @see LicensePlateRecognizeRequest
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* @see RecognizeLicensePlateResp
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*/
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@Slf4j
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@RestController
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@RequestMapping("/car/license/plate")
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@NotIntercept
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public class RecognizeLicensePlateController extends BaseController {
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public class RecognizeLicensePlateController extends AbstractRecognizeController {
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@Autowired
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private BLicensePlateHandle bLicensePlateHandle;
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/** 百度车牌识别 API 路径，完整地址见类注释 */
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private static final String LICENSE_PLATE_URI = "/rest/2.0/ocr/v1/license_plate";
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@PostMapping("/recognize")
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/** 车牌识别无 side 概念，统一用此占位符填充上下文，便于日志格式与父类一致 */
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private static final String SIDE_PLACEHOLDER = "plate";
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/**
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* 车牌识别
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*
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* @param request 车牌识别请求，字段见类注释「请求参数」
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* @return {@link RecognizeLicensePlateResp}
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*/
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@EbAuthentication(tencent = ApiConstants.TENCENT_AUTH)
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@PostMapping("/recognize")
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public R recognize(@RequestBody LicensePlateRecognizeRequest request) {
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return BaiduOcrResult.raw(bLicensePlateHandle.handle(toBaiduRequest(request)));
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long start = System.currentTimeMillis();
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RecognizeContext ctx = null;
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try {
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// ---------- 步骤①：参数校验（不调百度、不扣费） ----------
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String validateError = validateRequest(request);
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if (validateError != null) {
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ResolvedImageInput validateImage = request != null
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? ImageInputUtils.resolve(request.getImageUrlOrBase64()) : null;
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log.info("车牌识别：参数检查没通过，接口仍返回成功并附带提示（还没调识别、不扣费）。{} 返回给客户：{}",
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buildInputLogContext(request, validateImage),
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abbreviate(validateError, 120));
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return okResult(SIDE_PLACEHOLDER, validateError, null);
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}
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// ---------- 步骤②：解析影像入参 & 构建上下文 ----------
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ResolvedImageInput imageInput = ImageInputUtils.resolve(request.getImageUrlOrBase64());
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ctx = new RecognizeContext(
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SIDE_PLACEHOLDER,
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imageInput,
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buildInputLogContext(request, imageInput));
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// ---------- 步骤③：组装百度 API 请求体 ----------
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String content = buildRequestContent(imageInput);
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if (isBlank(content)) {
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log.error("车牌识别：组装请求失败，请求里没带有效图片。{}。{}",
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ctx.imageInput.getType().getDesc(), ctx.inputLog);
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return okResult(SIDE_PLACEHOLDER, formatHint(
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"报文组装异常",
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"识别请求体在序列化后未包含任何影像载荷，平台侧无法受理本次识别",
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"请核对 imageUrlOrBase64 是否非空且为有效 Base64 或 HTTP(S) 链接",
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"影像模式=" + ctx.imageInput.getType().name()
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), null);
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}
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// ---------- 步骤④：调用百度平台识别 ----------
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Map<String, Object> platformResult = callPlatform(content, ctx);
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if (platformResult == null) {
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return okResult(SIDE_PLACEHOLDER, formatHint(
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"服务无回执",
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"识别指令已下发，但在约定时间内未收到平台可解析的 JSON 回执",
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"建议间隔 3~5 秒重试；若连续失败，请记录 traceId、调用时刻并联系技术支持排查链路",
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"影像模式=" + ctx.imageInput.getType().name()
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), null);
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}
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// ---------- 步骤⑤：解析平台结果 → 构建车牌响应 ----------
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Map<String, Object> primary = pickPrimaryPlate(platformResult);
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RecognizeLicensePlateResp data = buildPlateResp(primary);
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String hint = resolvePlatformHint(platformResult, primary, ctx, data);
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// ---------- 步骤⑥：日志记录 & 返回 ----------
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logRecognizeResult(ctx, platformResult, data, hint, start);
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return okResult(SIDE_PLACEHOLDER, hint, data);
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} catch (Exception e) {
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long cost = System.currentTimeMillis() - start;
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ResolvedImageInput fallbackImage = request != null
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? ImageInputUtils.resolve(request.getImageUrlOrBase64()) : null;
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String mode = ctx != null ? ctx.imageInput.getType().getDesc()
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: (fallbackImage != null ? fallbackImage.getType().getDesc() : "未知");
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log.error("车牌识别：程序运行出错，耗时 {} ms。{}。客户传的：{}。异常：{} - {}",
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cost, mode, buildInputLogContext(request, fallbackImage),
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e.getClass().getSimpleName(),
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e.getMessage() != null ? e.getMessage() : "无具体说明", e);
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return okResult(SIDE_PLACEHOLDER, formatHint(
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"运行时故障",
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"服务端在处理识别流程时抛出未预期异常，识别结果不可用",
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"请勿重复高频重试；请保存 traceId、异常发生时间，由技术支持结合堆栈进一步定位",
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"异常类型=" + e.getClass().getSimpleName()
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+ (e.getMessage() != null ? "，摘要=" + e.getMessage() : "")
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), null);
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}
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}
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private BLicensePlateRequest toBaiduRequest(LicensePlateRecognizeRequest request) {
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BLicensePlateRequest bRequest = new BLicensePlateRequest();
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if (request == null) {
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return bRequest;
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/**
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* 子类钩子：车牌识别只有一种响应类型，无 side 区分。
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*/
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@Override
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protected Object defaultEmptyResp(String side) {
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return new RecognizeLicensePlateResp();
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}
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// ===================== 流程拆分方法 =====================
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/**
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* 调用百度云车牌识别接口。
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*
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* @param content 已拼装好的 POST 请求体
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* @param ctx 上下文（影像模式、入参摘要）
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* @return 平台返回的 JSON 解析后的 Map；超时/鉴权/解析失败时返回 null
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*/
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private Map<String, Object> callPlatform(String content, RecognizeContext ctx) {
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int len = content.length();
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log.info("车牌识别：开始调用平台识别。{}，请求大小约 {} 字节。{}",
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ctx.imageInput.getType().getDesc(), len, ctx.inputLog);
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Map<String, Object> result = requestBaidu(LICENSE_PLATE_URI, content);
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if (result == null) {
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log.error("车牌识别：平台没有返回结果（可能网络超时、鉴权失败或响应无法解析）。{}，请求约 {} 字节。{}",
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ctx.imageInput.getType().getDesc(), len, ctx.inputLog);
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}
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bRequest.setImageBase64(request.getImageBase64());
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bRequest.setImageUrl(request.getImageUrl());
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return bRequest;
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return result;
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}
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/**
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* 解析平台返回结果，判断是否需要向客户返回提示信息。
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* <p>判断顺序：</p>
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* <ol>
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* <li>error_code 存在 → 平台业务拒绝</li>
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* <li>words_result 为空 / 非数组 → 平台未识别出车牌</li>
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* <li>响应对象所有字段均为空 → 字段映射失败</li>
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* <li>以上均不命中 → 返回 null（识别正常）</li>
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* </ol>
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*/
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private String resolvePlatformHint(Map<String, Object> platformResult,
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Map<String, Object> primary,
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RecognizeContext ctx,
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RecognizeLicensePlateResp data) {
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Object errorCodeObj = platformResult.get("error_code");
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if (errorCodeObj != null) {
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String errorCode = String.valueOf(errorCodeObj);
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Object errorMsgObj = platformResult.get("error_msg");
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String errorMsg = errorMsgObj != null ? errorMsgObj.toString() : "平台未返回文字描述";
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String category = BaiduOcrError.categoryOf(errorCode);
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log.error("车牌识别：平台拒绝了本次识别。[{}] 错误码 {}，原因：{}。{}。客户传的：{}。{}",
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category, errorCode, errorMsg,
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ctx.imageInput.getType().getDesc(),
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ctx.inputLog, buildPlatformReceiptSummary(platformResult));
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return formatHint(
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category,
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BaiduOcrError.reasonOf(errorCode),
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BaiduOcrError.suggestionOf(errorCode, "车牌"),
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"错误码=" + errorCode + "，错误描述=" + errorMsg
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);
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}
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if (primary == null) {
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log.info("车牌识别：平台返回了，但 words_result 为空或非数组（可能不是车牌、画面无车牌、或图片不清晰）。{}。客户传的：{}。{}",
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ctx.imageInput.getType().getDesc(),
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ctx.inputLog, buildPlatformReceiptSummary(platformResult));
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return formatHint(
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"结构化结果缺失",
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"平台回执未包含可解析的车牌识别结果，无法进入字段映射环节",
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"优先排查：① 画面是否包含完整车牌；② 车牌是否被遮挡 / 反光 / 严重倾斜；"
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+ "③ 使用 URL 时确保平台抓取节点可访问且无 403/302 拦截",
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"解析状态=结果集为空"
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);
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}
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if (isAllStringFieldsBlank(data)) {
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log.info("车牌识别：平台有返回，但 plateNumber / color 等字段一个都没识别出来。{}。客户传的：{}。平台回执：{}",
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ctx.imageInput.getType().getDesc(),
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ctx.inputLog, buildPlatformReceiptSummary(platformResult));
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return formatHint(
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"字段映射为空",
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"平台回执已通过结构校验，但车牌号码、颜色等结构化字段均未命中",
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"请确认上传图片为车辆照片且车牌占画面比例合理（建议占画面 1/8 以上）；"
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+ "推荐重拍：垂直拍摄、避开反光、保证四角完整",
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"已映射字段数=0"
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);
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}
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return null;
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}
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/**
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* 记录本次识别的最终结果日志（含耗时、识别字段数量）。
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*/
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private void logRecognizeResult(RecognizeContext ctx, Map<String, Object> platformResult,
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Object data, String hint, long start) {
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long cost = System.currentTimeMillis() - start;
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int mapped = countNonBlankStringFields(data);
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if (StringUtils.isNotBlank(hint)) {
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log.info("车牌识别：处理结束（接口仍返回成功，但带了提示信息）。耗时 {} ms，识别出 {} 个字段。{}。客户传的：{}。平台回执：{}。给客户的提示：{}",
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cost, mapped, ctx.imageInput.getType().getDesc(),
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ctx.inputLog, buildPlatformReceiptSummary(platformResult), abbreviate(hint, 120));
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} else {
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log.info("车牌识别：识别成功。耗时 {} ms，共识别出 {} 个字段。{}。客户传的：{}。平台回执：{}",
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cost, mapped, ctx.imageInput.getType().getDesc(),
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ctx.inputLog, buildPlatformReceiptSummary(platformResult));
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}
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}
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// ===================== 校验 =====================
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private String validateRequest(LicensePlateRecognizeRequest request) {
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if (request == null) {
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log.info("车牌识别：没收到任何请求参数（表单未绑定成功），直接拒绝，未调用识别、不扣费");
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return formatHint(
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"入参绑定失败",
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"控制器未接收到可绑定的请求对象，所有业务字段均为空",
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"请确认使用 POST 提交；Content-Type 为 application/json；"
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+ "字段名与接口文档一致（imageUrlOrBase64）",
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"绑定结果=LicensePlateRecognizeRequest 为 null"
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);
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}
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ImageInputUtils.ValidationResult imageValidation =
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ImageInputUtils.validate(request.getImageUrlOrBase64());
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if (!imageValidation.isValid()) {
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log.info("车牌识别：imageUrlOrBase64 校验未通过（{}），未调用识别、不扣费。原因：{}。{}",
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imageValidation.getCategory(),
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imageValidation.getReason(),
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buildInputLogContext(request, null));
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return formatHint(
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imageValidation.getCategory(),
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imageValidation.getReason(),
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imageValidation.getSuggestion(),
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imageValidation.getDetail()
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);
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}
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return null;
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}
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// ===================== 请求构造 =====================
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/**
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* 构造调用百度车牌识别的 POST 请求体（application/x-www-form-urlencoded 格式）。
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* <p>本接口默认走单车牌识别，不开启遮挡 / PS / 多张检测开关。</p>
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*/
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||||
private String buildRequestContent(ResolvedImageInput imageInput) {
|
||||
StringBuilder sb = new StringBuilder();
|
||||
if (imageInput == null || StringUtils.isBlank(imageInput.getFormValue())) {
|
||||
return sb.toString();
|
||||
}
|
||||
if (ImageInputUtils.ImageInputType.URL == imageInput.getType()) {
|
||||
sb.append("&url=").append(imageInput.getFormValue());
|
||||
} else {
|
||||
sb.append("&image=").append(imageInput.getFormValue());
|
||||
}
|
||||
sb.append("&multi_detect=false");
|
||||
sb.append("&multi_scale=false");
|
||||
sb.append("&detect_complete=false");
|
||||
sb.append("&detect_risk=false");
|
||||
return sb.toString();
|
||||
}
|
||||
|
||||
// ===================== 平台结果映射 =====================
|
||||
|
||||
/**
|
||||
* 从百度返回的 {@code words_result} 数组中挑出"主车牌"。
|
||||
* <p>策略：</p>
|
||||
* <ol>
|
||||
* <li>无 words_result 或为空 → 返回 null</li>
|
||||
* <li>只有一条 → 直接返回</li>
|
||||
* <li>多条 → 取号码非空且 probability 平均值最高的一条</li>
|
||||
* </ol>
|
||||
*/
|
||||
@SuppressWarnings("unchecked")
|
||||
private Map<String, Object> pickPrimaryPlate(Map<String, Object> platformResult) {
|
||||
Object wordsResult = platformResult.get("words_result");
|
||||
if (!(wordsResult instanceof List)) {
|
||||
return null;
|
||||
}
|
||||
List<Map<String, Object>> list = (List<Map<String, Object>>) wordsResult;
|
||||
if (list.isEmpty()) {
|
||||
return null;
|
||||
}
|
||||
Map<String, Object> best = null;
|
||||
double bestScore = -1;
|
||||
for (Map<String, Object> item : list) {
|
||||
if (item == null) {
|
||||
continue;
|
||||
}
|
||||
Object number = item.get("number");
|
||||
if (number == null || StringUtils.isBlank(number.toString())) {
|
||||
continue;
|
||||
}
|
||||
double score = averageProbability(item);
|
||||
if (score > bestScore) {
|
||||
bestScore = score;
|
||||
best = item;
|
||||
}
|
||||
}
|
||||
return best;
|
||||
}
|
||||
|
||||
/**
|
||||
* 将"主车牌"映射为对外响应对象。
|
||||
*/
|
||||
private RecognizeLicensePlateResp buildPlateResp(Map<String, Object> primary) {
|
||||
RecognizeLicensePlateResp resp = new RecognizeLicensePlateResp();
|
||||
if (primary == null) {
|
||||
return resp;
|
||||
}
|
||||
Object number = primary.get("number");
|
||||
if (number != null) {
|
||||
resp.setPlateNumber(number.toString());
|
||||
}
|
||||
double avgConfidence = averageProbability(primary);
|
||||
if (avgConfidence >= 0) {
|
||||
resp.setConfidence((float) avgConfidence);
|
||||
resp.setPlateTypeConfidence((float) avgConfidence);
|
||||
}
|
||||
Object color = primary.get("color");
|
||||
if (color != null) {
|
||||
String colorRaw = color.toString();
|
||||
resp.setPlateColor(translateColor(colorRaw));
|
||||
resp.setPlateType(inferPlateType(colorRaw, resp.getPlateNumber()));
|
||||
}
|
||||
return resp;
|
||||
}
|
||||
|
||||
/**
|
||||
* 把百度返回的颜色英文标识翻译为中文（对外不暴露英文 enum）。
|
||||
*/
|
||||
private String translateColor(String colorRaw) {
|
||||
if (StringUtils.isBlank(colorRaw)) {
|
||||
return null;
|
||||
}
|
||||
Map<String, String> map = colorTranslationMap();
|
||||
String hit = map.get(colorRaw.trim().toLowerCase());
|
||||
return hit != null ? hit : colorRaw;
|
||||
}
|
||||
|
||||
/**
|
||||
* 基于颜色 + 号码长度推断车牌类型，对齐阿里云 RecognizeLicensePlate 规范。
|
||||
*/
|
||||
private String inferPlateType(String colorRaw, String plateNumber) {
|
||||
if (StringUtils.isBlank(colorRaw)) {
|
||||
return null;
|
||||
}
|
||||
String c = colorRaw.trim().toLowerCase();
|
||||
switch (c) {
|
||||
case "blue":
|
||||
return "小型汽车";
|
||||
case "yellow":
|
||||
return "大型汽车";
|
||||
case "green":
|
||||
case "gradual_green":
|
||||
return "新能源车";
|
||||
case "yellow_green":
|
||||
return "大型新能源车";
|
||||
case "white":
|
||||
if (plateNumber != null && plateNumber.contains("警")) {
|
||||
return "警车";
|
||||
}
|
||||
if (plateNumber != null && (plateNumber.startsWith("WJ") || plateNumber.contains("WJ"))) {
|
||||
return "武警车";
|
||||
}
|
||||
return "军车";
|
||||
case "black":
|
||||
if (plateNumber != null && (plateNumber.startsWith("使") || plateNumber.startsWith("领"))) {
|
||||
return "使领馆车";
|
||||
}
|
||||
return "港澳车";
|
||||
default:
|
||||
return "其他";
|
||||
}
|
||||
}
|
||||
|
||||
private static Map<String, String> colorTranslationMap() {
|
||||
Map<String, String> m = new HashMap<>();
|
||||
m.put("blue", "蓝");
|
||||
m.put("yellow", "黄");
|
||||
m.put("green", "绿");
|
||||
m.put("gradual_green", "渐变绿");
|
||||
m.put("yellow_green", "黄绿");
|
||||
m.put("white", "白");
|
||||
m.put("black", "黑");
|
||||
return Collections.unmodifiableMap(m);
|
||||
}
|
||||
|
||||
/**
|
||||
* 计算百度 {@code probability} 数组的平均值；数组缺失或非数字时返回 -1。
|
||||
*/
|
||||
@SuppressWarnings("unchecked")
|
||||
private double averageProbability(Map<String, Object> item) {
|
||||
Object probObj = item.get("probability");
|
||||
if (!(probObj instanceof List)) {
|
||||
return -1;
|
||||
}
|
||||
List<Object> list = (List<Object>) probObj;
|
||||
if (list.isEmpty()) {
|
||||
return -1;
|
||||
}
|
||||
double sum = 0;
|
||||
int count = 0;
|
||||
for (Object o : list) {
|
||||
if (o instanceof Number) {
|
||||
sum += ((Number) o).doubleValue();
|
||||
count++;
|
||||
}
|
||||
}
|
||||
return count == 0 ? -1 : sum / count;
|
||||
}
|
||||
|
||||
// ===================== 私有工具 =====================
|
||||
|
||||
/**
|
||||
* 格式化为统一的提示文案。
|
||||
*/
|
||||
private String formatHint(String category, String reason, String suggestion, String detail) {
|
||||
StringBuilder sb = new StringBuilder();
|
||||
sb.append("【车牌识别·").append(category).append("】").append(reason);
|
||||
if (StringUtils.isNotBlank(detail)) {
|
||||
sb.append("｜定位信息：").append(detail);
|
||||
}
|
||||
sb.append("｜处置指引：").append(suggestion);
|
||||
return sb.toString();
|
||||
}
|
||||
|
||||
/** 入参日志说明（不打印影像正文，只说类型与长度） */
|
||||
private String buildInputLogContext(LicensePlateRecognizeRequest request, ResolvedImageInput imageInput) {
|
||||
if (request == null) {
|
||||
return "未收到请求体";
|
||||
}
|
||||
String modeDesc = imageInput != null ? imageInput.getType().getDesc() : "影像未解析";
|
||||
int rawLen = imageInput != null
|
||||
? textLength(imageInput.getRawValue())
|
||||
: textLength(request.getImageUrlOrBase64());
|
||||
return String.format("%s，影像原始长度 %d 字符", modeDesc, rawLen);
|
||||
}
|
||||
}
|
||||
|
||||
@ -1,53 +1,46 @@
|
||||
package com.heyu.api.resp.car;
|
||||
|
||||
|
||||
import com.heyu.api.baidu.response.convert.BTextreviewQueryResp;
|
||||
import lombok.Data;
|
||||
|
||||
/***
|
||||
* https://next.api.aliyun.com/api/ocr/2019-12-30/RecognizeLicensePlate?useCommon=true&tab=DOC&lang=JAVA&sdkStyle=dara
|
||||
/**
|
||||
* 车牌识别响应
|
||||
*
|
||||
* 车牌识别
|
||||
* 字段对齐阿里云 RecognizeLicensePlate 规范：
|
||||
* https://next.api.aliyun.com/api/ocr/2019-12-30/RecognizeLicensePlate
|
||||
*
|
||||
* RecognizeLicensePlate
|
||||
* 仅返回画面中"主车牌"（百度多车牌场景下默认取第一个，按置信度降序）。
|
||||
*/
|
||||
@Data
|
||||
public class RecognizeLicensePlateResp {
|
||||
|
||||
/**
|
||||
* 车牌号码。
|
||||
* 示例值：粤BP57E7
|
||||
*/
|
||||
private String plateNumber;
|
||||
|
||||
/***
|
||||
/**
|
||||
* 车牌号码的置信度，取值范围 0~1。
|
||||
* 示例值：0.997
|
||||
*/
|
||||
private Float confidence;
|
||||
|
||||
/**
|
||||
* 车牌类型。包括：小型汽车、新能源车、大型汽车、挂车、教练车、警车、军车、使领馆车、港澳车。
|
||||
* 示例值：小型汽车
|
||||
*/
|
||||
private String plateType;
|
||||
|
||||
/**
|
||||
* 车牌类型的置信度，取值范围 0~1。
|
||||
*
|
||||
* 示例值:
|
||||
* 1
|
||||
* 示例值：0.95
|
||||
*/
|
||||
private Float plateTypeConfidence;
|
||||
|
||||
/**
|
||||
* 车牌类型。包括：小型汽车、新能源车、大型汽车、挂车、教练车、警车、军车、使领馆车、港澳车。
|
||||
*
|
||||
* 示例值:
|
||||
* 小型汽车
|
||||
* 车牌颜色（蓝 / 绿 / 黄 / 黄绿 / 白 / 黑）。
|
||||
* 示例值：蓝
|
||||
*/
|
||||
private String plateType;
|
||||
|
||||
|
||||
/***
|
||||
* 车牌号码的置信度，取值范围 0~1。
|
||||
*
|
||||
* 示例值:
|
||||
* 0.99745339155197144
|
||||
*/
|
||||
private Float confidence;
|
||||
|
||||
|
||||
/***
|
||||
* 车牌号码。
|
||||
*
|
||||
* 示例值:
|
||||
* 粤BP57E7
|
||||
*/
|
||||
private String plateNumber;
|
||||
|
||||
private String plateColor;
|
||||
|
||||
}
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user