package com.ycl.calculate;
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import com.ycl.platform.domain.entity.CheckIndexFace;
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import com.ycl.platform.domain.result.HK.FaceDeviceSamplingResult;
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import com.ycl.platform.domain.vo.TMonitorVO;
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import com.ycl.platform.mapper.CheckIndexFaceMapper;
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import com.ycl.platform.mapper.TMonitorMapper;
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import com.ycl.platform.service.ICheckIndexFaceService;
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import constant.ApiConstants;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.stereotype.Component;
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import org.springframework.util.CollectionUtils;
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import utils.DateUtils;
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import java.math.BigDecimal;
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import java.util.ArrayList;
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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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import java.util.function.Function;
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import java.util.stream.Collectors;
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/**
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* 计算人脸抓拍图片合格性、大图可用性
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* 人脸数据抽检接口
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* 获取分省厅、区域的map<k,v> k为deptId或者Province_deptId
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* 更新或新增
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*/
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@Component
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@Slf4j
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public class FaceDeviceSampleCalculation extends IndexCalculationServe<FaceDeviceSamplingResult, FaceDeviceSampleCalculation.AreaStats> implements CalculationStrategy<FaceDeviceSamplingResult> {
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@Autowired
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private CheckIndexFaceMapper checkIndexFaceMapper;
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@Autowired
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private ICheckIndexFaceService checkIndexFaceService;
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//区域车辆抽检指标
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protected static class AreaStats {
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int totalSites = 0;
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//图片合格的点位数
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int picQualifySites = 0;
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//图片可用的点位数
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int picUsabilitySites = 0;
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//图片总点位数
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int picSites = 0;
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}
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@Override
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public void calculate(List<FaceDeviceSamplingResult> list) {
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//获取分区域的指标数量
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Map<String, FaceDeviceSampleCalculation.AreaStats> areaStatsMap = getAreaStatsMap(list,Boolean.FALSE);
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if (areaStatsMap == null) return;
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// 查询是否index表已经存在今日数据
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List<CheckIndexFace> checkIndexFaceList = checkIndexFaceMapper.selectToday(DateUtils.getDate());
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List<CheckIndexFace> checkIndexFaces = new ArrayList<>();
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areaStatsMap.forEach((deptId, stats) -> {
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if (stats.totalSites > 0) {
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CheckIndexFace checkIndexFace = createOrUpdateCheckIndexFace(deptId, stats, checkIndexFaceList);
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if (checkIndexFace != null) {
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checkIndexFaces.add(checkIndexFace);
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}
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}
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});
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checkIndexFaceService.saveOrUpdateBatch(checkIndexFaces);
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}
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/**
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* 累计抓拍数据准确设备数和设备总数
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*/
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@Override
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public void updateAreaStats(Map<String, AreaStats> areaStatsMap, String key, FaceDeviceSamplingResult result) {
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//返回对象的引用，如果不存在会放入新的key,value
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AreaStats stats = areaStatsMap.computeIfAbsent(key, k -> new AreaStats());
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FaceDeviceSamplingResult.BigUsefulness bigUseful = result.getBigUseful();
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FaceDeviceSamplingResult.FaceEligibility faceElig = result.getFaceEligibility();
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stats.totalSites++;
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//90%及以上数据合格则此人脸设备被视为图片合格
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if (faceElig != null) {
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if (faceElig.getFaceEligPercent() >= 0.9) {
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stats.picQualifySites++;
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}
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}
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//只计算抽检的
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if(bigUseful.getSampleCount() !=0){
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stats.picSites++;
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//大图可用率大于90%视为合格,
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if (bigUseful.getBigUsefulPercent() >= 0.9) {
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stats.picUsabilitySites++;
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}
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}
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}
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/**
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* 人脸图片合格率、大图可用性
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*/
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private CheckIndexFace createOrUpdateCheckIndexFace(String key, AreaStats stats, List<CheckIndexFace> checkIndexFaceList) {
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CheckIndexFace checkIndexFace = getCheckIndex(key, checkIndexFaceList, CheckIndexFace.class);
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if (checkIndexFace == null) {
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return null;
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}
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//调用图片合格率计算方法
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Map<String, Object> qualifyParam = new HashMap<>();
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qualifyParam.put("totalSites", stats.totalSites);
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qualifyParam.put("picQualifySites", stats.picQualifySites);
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BigDecimal dataQualify = dataQualify(qualifyParam);
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checkIndexFace.setFacePictureQualification(dataQualify);
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//调用大图可用性计算方法
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Map<String, Object> usabilityParam = new HashMap<>();
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usabilityParam.put("totalSites", stats.picSites);
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usabilityParam.put("picUsabilitySites", stats.picUsabilitySites);
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BigDecimal picUsability = picUsability(usabilityParam);
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checkIndexFace.setFacePictureAvailability(picUsability);
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return checkIndexFace;
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}
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}
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