439 lines
19 KiB
Java
439 lines
19 KiB
Java
package com.rj.service.impl;
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import com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;
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import com.rj.entity.FaceDetectLog;
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import com.rj.mapper.FaceDetectLogMapper;
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import com.rj.service.IFaceDetectLogService;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.beans.factory.annotation.Value;
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import org.springframework.http.*;
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import org.springframework.stereotype.Service;
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import org.springframework.web.client.RestTemplate;
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import org.springframework.web.client.HttpClientErrorException;
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import org.springframework.web.client.HttpServerErrorException;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import com.fasterxml.jackson.databind.JsonNode;
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import java.time.LocalDateTime;
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import java.util.HashMap;
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import java.util.Map;
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import java.util.UUID;
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/**
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* 图像检测日志服务实现
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*/
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@Slf4j
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@Service
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public class FaceDetectLogServiceImpl extends ServiceImpl<FaceDetectLogMapper, FaceDetectLog> implements IFaceDetectLogService {
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private static final String API_URL = "https://dashscope.aliyuncs.com/api/v1/services/aigc/image2video/face-detect";
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private static final String API_URL_AA = "https://dashscope.aliyuncs.com/api/v1/services/aigc/image2video/aa-detect";
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@Value("${dashscope.api.key:}")
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private String apiKey;
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private final RestTemplate restTemplate;
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private final ObjectMapper objectMapper;
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public FaceDetectLogServiceImpl() {
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this.restTemplate = new RestTemplate();
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this.objectMapper = new ObjectMapper();
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}
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@Override
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public boolean saveFaceDetectLog(FaceDetectLog faceDetectLog) {
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try {
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return save(faceDetectLog);
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} catch (Exception e) {
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log.error("保存图像检测日志失败: {}", e.getMessage(), e);
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return false;
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}
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}
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/**
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* 执行图像检测并保存日志
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*/
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public FaceDetectLog detectFaceAndSave(String imageUrl) {
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return detectFaceAndSave(imageUrl, null, null, null);
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}
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/**
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* 执行图像检测并保存日志（带扩展信息）
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*/
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public FaceDetectLog detectFaceAndSave(String imageUrl, String ownerName, String ownerPhone, String avatarName) {
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return detectFaceAndSave(imageUrl, ownerName, ownerPhone, avatarName, null);
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}
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/**
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* 执行图像检测并保存日志（带扩展信息和模型名）
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*/
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public FaceDetectLog detectFaceAndSave(String imageUrl, String ownerName, String ownerPhone, String avatarName, String model) {
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if (apiKey == null || apiKey.trim().isEmpty()) {
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log.error("DASHSCOPE_API_KEY未配置");
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return createErrorLog(imageUrl, "DASHSCOPE_API_KEY未配置", ownerName, ownerPhone, avatarName);
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}
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// 创建日志记录
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FaceDetectLog faceDetectLog = new FaceDetectLog();
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String requestId = UUID.randomUUID().toString();
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LocalDateTime requestTime = LocalDateTime.now();
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faceDetectLog.setRequestId(requestId);
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// 设置模型名称，如果未提供则使用默认值
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String modelName = (model != null && !model.trim().isEmpty()) ? model : "liveportrait-detect";
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faceDetectLog.setModel(modelName);
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log.info("使用模型: {}", modelName);
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faceDetectLog.setImageUrl(imageUrl);
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faceDetectLog.setOwnerName(ownerName);
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faceDetectLog.setOwnerPhone(ownerPhone);
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faceDetectLog.setAvatarName(avatarName);
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faceDetectLog.setRequestTime(requestTime);
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long startTime = System.currentTimeMillis();
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try {
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// 创建请求体
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Map<String, Object> requestBody = new HashMap<>();
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requestBody.put("model", modelName);
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if (modelName.equals("emo-detect-v1") || modelName.equals("emoji-detect-v1")){
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Map<String, Object> ratioo = new HashMap<>();
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ratioo.put("ratio", "1:1");
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requestBody.put("parameters", ratioo);
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}
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Map<String, String> input = new HashMap<>();
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input.put("image_url", imageUrl);
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requestBody.put("input", input);
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// 设置请求头
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HttpHeaders headers = new HttpHeaders();
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headers.setContentType(MediaType.APPLICATION_JSON);
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headers.setBearerAuth(apiKey);
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log.info("发送图像检测请求，requestBody : {}, 请求参数headers: {}", requestBody , headers);
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// 创建请求实体 parameters.ratio 希望检测确认的画幅，可选 "1:1"或"3:4"。默认值为"1:1"。
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HttpEntity<Map<String, Object>> requestEntity = new HttpEntity<>(requestBody, headers);
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ResponseEntity<String> response = null;
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if ( modelName.equals("animate-anyone-detect-gen2")){
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response = restTemplate.exchange(
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API_URL_AA,
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HttpMethod.POST,
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requestEntity,
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String.class
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);
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}else {
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response = restTemplate.exchange(
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API_URL,
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HttpMethod.POST,
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requestEntity,
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String.class
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);
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}
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// 发送请求
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log.info("发送图像检测请求，response {}, 图片URL: {}", response, imageUrl);
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// 计算处理时间
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long endTime = System.currentTimeMillis();
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long processingTime = endTime - startTime;
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// 更新日志记录
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faceDetectLog.setResponseTime(LocalDateTime.now());
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faceDetectLog.setStatusCode(response.getStatusCode().value());
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faceDetectLog.setProcessingTimeMs(processingTime);
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faceDetectLog.setResponseData(response.getBody());
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// 处理响应
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log.info("图像检测响应，response: {}, 处理时间: {}ms", response.toString(), processingTime);
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// 解析JSON响应
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if (response.getStatusCode() == HttpStatus.OK) {
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faceDetectLog.setSuccess( true);
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JsonNode jsonResponse = objectMapper.readTree(response.getBody());
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// 根据pass字段判断是否成功
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boolean isSuccess = false;
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if (jsonResponse.has("output") && jsonResponse.get("output").has("pass")) {
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isSuccess = jsonResponse.get("output").get("pass").asBoolean();
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faceDetectLog.setSuccess(isSuccess);
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log.info("图像检测结果 - 头像 pass: {}", isSuccess);
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}
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if (jsonResponse.has("output") && jsonResponse.get("output").has("check_pass")) {
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isSuccess = jsonResponse.get("output").get("check_pass").asBoolean();
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faceDetectLog.setSuccess(isSuccess);
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log.info("图像检测结果 (animate-anyone-detect-gen2 舞动人像 )- check_pass: {}", isSuccess);
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}
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// 检查是否有检测到图像
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int faceCount = 0;
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if (jsonResponse.has("output")) {
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JsonNode output = jsonResponse.get("output");
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// 根据pass字段判断是否检测到图像
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if (output.has("pass")) {
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boolean pass = output.get("pass").asBoolean();
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faceDetectLog.setFaceCount(1);
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log.info("图像检测结果 - pass: {}, 检测到图像数量: {}", pass, faceDetectLog.getFaceCount());
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// 记录message信息
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if (output.has("message")) {
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String message = output.get("message").asText();
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log.info("检测消息: {}", message);
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}
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}
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// 解析图像区域坐标（如果API返回中包含）
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if (output.has("face_bbox")) {
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JsonNode faceBbox = output.get("face_bbox");
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if (faceBbox.isArray()) {
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String faceBboxStr = faceBbox.toString();
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faceDetectLog.setFaceBbox(faceBboxStr);
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log.info("图像区域坐标: {}", faceBboxStr);
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}
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}
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// 解析动态区域坐标（如果API返回中包含）
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if (output.has("ext_bbox")) {
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JsonNode extBbox = output.get("ext_bbox");
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if (extBbox.isArray()) {
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String extBboxStr = extBbox.toString();
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faceDetectLog.setExtBbox(extBboxStr);
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log.info("动态区域坐标: {}", extBboxStr);
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}
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}
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}
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//emoji 开始
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if (jsonResponse.has("output") && jsonResponse.get("output").has("ext_bbox_face")) {
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String ext_bbox = jsonResponse.get("output").get("ext_bbox_face").toString();
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faceDetectLog.setExtBbox(ext_bbox);
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}
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if (jsonResponse.has("output") && jsonResponse.get("output").has("bbox_face")) {
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String bboxFace = jsonResponse.get("output").get("bbox_face").toString();
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faceDetectLog.setFaceBbox(bboxFace);
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}
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//emoji 结束
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// 记录请求ID
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if (jsonResponse.has("request_id")) {
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String apiRequestId = jsonResponse.get("request_id").asText();
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log.info("API请求ID: {}", apiRequestId);
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}
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// 记录使用情况
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if (jsonResponse.has("usage")) {
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JsonNode usage = jsonResponse.get("usage");
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if (usage.has("image_count")) {
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int imageCount = usage.get("image_count").asInt();
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log.info("处理的图片数量: {}", imageCount);
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// 可以将image_count保存到数据库字段中，如果有的话
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faceDetectLog.setFaceCount(imageCount);
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}
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// 记录其他usage信息
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log.info("使用情况: {}", usage.toString());
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}
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} else {
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// HTTP状态码不是200，直接标记为失败
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faceDetectLog.setSuccess(false);
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}
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// 保存到数据库
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boolean saved = saveFaceDetectLog(faceDetectLog);
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if (saved) {
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log.info("图像检测日志已保存，请求ID: {}", requestId);
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} else {
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log.error("保存图像检测日志失败，请求ID: {}", requestId);
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}
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return faceDetectLog;
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} catch (HttpClientErrorException e) {
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return handleError(faceDetectLog, e, "客户端错误 (4xx): " + e.getStatusCode(), startTime);
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} catch (HttpServerErrorException e) {
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return handleError(faceDetectLog, e, "服务器错误 (5xx): " + e.getStatusCode(), startTime);
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} catch (Exception e) {
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return handleError(faceDetectLog, e, "图像检测请求失败: " + e.getMessage(), startTime);
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}
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}
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/**
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* 处理错误并保存到数据库
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*/
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private FaceDetectLog handleError(FaceDetectLog faceDetectLog, Exception e, String errorMessage, long startTime) {
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long endTime = System.currentTimeMillis();
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long processingTime = endTime - startTime;
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faceDetectLog.setResponseTime(LocalDateTime.now());
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faceDetectLog.setSuccess(false);
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faceDetectLog.setProcessingTimeMs(processingTime);
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faceDetectLog.setErrorMessage(errorMessage);
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if (e instanceof HttpClientErrorException) {
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faceDetectLog.setStatusCode(((HttpClientErrorException) e).getStatusCode().value());
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faceDetectLog.setResponseData(((HttpClientErrorException) e).getResponseBodyAsString());
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} else if (e instanceof HttpServerErrorException) {
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faceDetectLog.setStatusCode(((HttpServerErrorException) e).getStatusCode().value());
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faceDetectLog.setResponseData(((HttpServerErrorException) e).getResponseBodyAsString());
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}
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log.error("图像检测失败: {}", errorMessage);
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log.error("错误详情: {}", e.getMessage());
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// 保存错误日志到数据库
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try {
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saveFaceDetectLog(faceDetectLog);
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log.info("错误日志已保存，请求ID: {}", faceDetectLog.getRequestId());
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} catch (Exception saveException) {
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log.error("保存错误日志失败: {}", saveException.getMessage());
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}
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return faceDetectLog;
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}
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/**
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* 创建错误日志
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*/
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private FaceDetectLog createErrorLog(String imageUrl, String errorMessage) {
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return createErrorLog(imageUrl, errorMessage, null, null, null);
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}
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/**
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* 创建错误日志（带扩展信息）
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*/
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private FaceDetectLog createErrorLog(String imageUrl, String errorMessage, String ownerName, String ownerPhone, String avatarName) {
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FaceDetectLog faceDetectLog = new FaceDetectLog();
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faceDetectLog.setRequestId(UUID.randomUUID().toString());
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faceDetectLog.setModel("liveportrait-detect");
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faceDetectLog.setImageUrl(imageUrl);
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faceDetectLog.setOwnerName(ownerName);
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faceDetectLog.setOwnerPhone(ownerPhone);
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faceDetectLog.setAvatarName(avatarName);
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faceDetectLog.setRequestTime(LocalDateTime.now());
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faceDetectLog.setResponseTime(LocalDateTime.now());
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faceDetectLog.setSuccess(false);
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faceDetectLog.setErrorMessage(errorMessage);
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faceDetectLog.setFaceCount(0);
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try {
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saveFaceDetectLog(faceDetectLog);
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} catch (Exception e) {
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log.error("保存错误日志失败: {}", e.getMessage());
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}
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return faceDetectLog;
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}
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/**
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* 分页查询图像检测日志
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*/
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@Override
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public com.baomidou.mybatisplus.extension.plugins.pagination.Page<FaceDetectLog> getPageList(
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Integer current, Integer size, Boolean success, String startTime, String endTime,
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String ownerName, String ownerPhone, String avatarName) {
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com.baomidou.mybatisplus.extension.plugins.pagination.Page<FaceDetectLog> page =
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new com.baomidou.mybatisplus.extension.plugins.pagination.Page<>(current, size);
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com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper<FaceDetectLog> queryWrapper =
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new com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper<>();
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// 添加查询条件
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if (success != null) {
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queryWrapper.eq(FaceDetectLog::getSuccess, success);
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}
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if (startTime != null && !startTime.trim().isEmpty()) {
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queryWrapper.ge(FaceDetectLog::getRequestTime, startTime);
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}
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if (endTime != null && !endTime.trim().isEmpty()) {
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queryWrapper.le(FaceDetectLog::getRequestTime, endTime);
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}
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if (ownerName != null && !ownerName.trim().isEmpty()) {
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queryWrapper.like(FaceDetectLog::getOwnerName, ownerName);
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}
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if (ownerPhone != null && !ownerPhone.trim().isEmpty()) {
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queryWrapper.like(FaceDetectLog::getOwnerPhone, ownerPhone);
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}
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if (avatarName != null && !avatarName.trim().isEmpty()) {
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queryWrapper.like(FaceDetectLog::getAvatarName, avatarName);
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}
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// 按请求时间倒序排列
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queryWrapper.orderByDesc(FaceDetectLog::getRequestTime);
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return page(page, queryWrapper);
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}
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/**
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* 获取统计信息
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*/
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@Override
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public Map<String, Object> getStatistics(String startTime, String endTime) {
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Map<String, Object> statistics = new HashMap<>();
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// 构建查询条件
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com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper<FaceDetectLog> queryWrapper =
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new com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper<>();
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// 时间范围筛选
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if (startTime != null && !startTime.trim().isEmpty()) {
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queryWrapper.ge(FaceDetectLog::getRequestTime, startTime);
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}
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if (endTime != null && !endTime.trim().isEmpty()) {
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queryWrapper.le(FaceDetectLog::getRequestTime, endTime);
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}
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// 查询总数
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long totalCount = count(queryWrapper);
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// 查询成功数
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com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper<FaceDetectLog> successWrapper =
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new com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper<>();
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// 时间范围筛选
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if (startTime != null && !startTime.trim().isEmpty()) {
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successWrapper.ge(FaceDetectLog::getRequestTime, startTime);
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}
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if (endTime != null && !endTime.trim().isEmpty()) {
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successWrapper.le(FaceDetectLog::getRequestTime, endTime);
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}
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successWrapper.eq(FaceDetectLog::getSuccess, true);
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long successCount = count(successWrapper);
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// 查询失败数
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long failureCount = totalCount - successCount;
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// 计算成功率
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double successRate = totalCount > 0 ? (double) successCount / totalCount * 100 : 0;
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// 查询平均处理时间
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java.util.List<FaceDetectLog> logs = list(queryWrapper);
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double avgProcessingTime = logs.stream()
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.filter(log -> log.getProcessingTimeMs() != null)
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.mapToLong(FaceDetectLog::getProcessingTimeMs)
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.average()
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.orElse(0.0);
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// 查询总图像数量
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int totalFaceCount = logs.stream()
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.filter(log -> log.getFaceCount() != null)
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.mapToInt(FaceDetectLog::getFaceCount)
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.sum();
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// 构建统计结果
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statistics.put("totalCount", totalCount);
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statistics.put("successCount", successCount);
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statistics.put("failureCount", failureCount);
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statistics.put("successRate", Math.round(successRate * 100.0) / 100.0);
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statistics.put("avgProcessingTimeMs", Math.round(avgProcessingTime));
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statistics.put("totalFaceCount", totalFaceCount);
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log.info("统计信息查询完成，总数: {}, 成功数: {}, 失败数: {}, 成功率: {}%",
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totalCount, successCount, failureCount, successRate);
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return statistics;
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}
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} |