From e0af18b36385cdcef9e2a4d2aec6c80a784377c3 Mon Sep 17 00:00:00 2001 From: Yuanzq <1259216392@qq.com> Date: Fri, 16 Jan 2026 10:27:09 +0800 Subject: [PATCH] =?UTF-8?q?feat:=20=E6=96=B0=E5=A2=9E=E7=94=A8=E6=88=B7?= =?UTF-8?q?=E7=AE=A1=E7=90=86=20API=20=E6=8E=A5=E5=8F=A3=E3=80=81=E6=9C=8D?= =?UTF-8?q?=E5=8A=A1=E9=80=BB=E8=BE=91=E3=80=81=E5=B7=A5=E5=85=B7=E7=B1=BB?= =?UTF-8?q?=E3=80=81API=20=E6=B5=8B=E8=AF=95=E8=84=9A=E6=9C=AC=E5=92=8C?= =?UTF-8?q?=E6=96=87=E6=A1=A3=E3=80=82?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- API_DOCUMENTATION.md | 224 ++++++++++++++++++ .../face/controller/UserController.java | 19 ++ .../com/bonuos/face/service/UserService.java | 9 + .../face/service/impl/UserServiceImpl.java | 94 ++++++++ .../java/com/bonuos/face/util/FaceUtils.java | 58 +++++ .../face/controller/UserController.class | Bin 5406 -> 6111 bytes .../com/bonuos/face/service/UserService.class | Bin 975 -> 1110 bytes .../face/service/impl/UserServiceImpl.class | Bin 9045 -> 11558 bytes .../com/bonuos/face/util/FaceUtils$1.class | Bin 0 -> 611 bytes .../com/bonuos/face/util/FaceUtils.class | Bin 0 -> 2082 bytes quick_test_api.py | 103 ++++++++ verify_changes.py | 78 ++++++ 12 files changed, 585 insertions(+) create mode 100644 API_DOCUMENTATION.md create mode 100644 backend-java/src/main/java/com/bonuos/face/util/FaceUtils.java create mode 100644 backend-java/target/classes/com/bonuos/face/util/FaceUtils$1.class create mode 100644 backend-java/target/classes/com/bonuos/face/util/FaceUtils.class create mode 100644 quick_test_api.py create mode 100644 verify_changes.py diff --git a/API_DOCUMENTATION.md b/API_DOCUMENTATION.md new file mode 100644 index 0000000..2c5d226 --- /dev/null +++ b/API_DOCUMENTATION.md @@ -0,0 +1,224 @@ +# 人脸识别系统 API 接口文档 + +本文档详细说明了人脸识别系统的后端业务接口与算法服务接口，供开发人员集成使用。 + +## 1. 系统业务接口 (Java Backend) + +后端服务主要提供分组管理和人员信息管理功能。所有接口统一通过 HTTP 协议调用，返回 JSON 格式数据。 + +**基础路径**: `/api` (例如: `http://:/api`) + +### 1.1 分组管理 + +#### 1.1.1 创建/添加分组 +* **接口地址**: `/groups/add` +* **请求方式**: `POST` +* **请求类型**: `application/json` +* **请求参数**: + + | 参数名 | 类型 | 必填 | 说明 | + | :--- | :--- | :--- | :--- | + | name | String | 是 | 分组名称 | + | description | String | 否 | 分组描述 (如果有) | + + **请求示例**: + ```json + { + "name": "VIP人员", + "description": "重要客户分组" + } + ``` + +* **返回结果**: + ```json + { + "code": 200, + "msg": "success", + "data": { + "id": 1, + "name": "VIP人员", + "createTime": "2023-12-30T10:00:00" + } + } + ``` + +#### 1.1.2 获取分组列表 +* **接口地址**: `/groups/list` +* **请求方式**: `GET` +* **返回结果**: + ```json + { + "code": 200, + "msg": "success", + "data": [ + { + "id": 1, + "name": "默认分组" + }, + { + "id": 2, + "name": "员工分组" + } + ] + } + ``` + +--- + +### 1.2 人员管理 + +#### 1.2.1 新增人员 (带照片) +该接口用于注册新用户，同时上传人脸照片用于提取特征。 + +* **接口地址**: `/users/add` +* **请求方式**: `POST` +* **请求类型**: `multipart/form-data` (表单上传) +* **请求参数**: + + | 参数名 | 类型 | 必填 | 说明 | + | :--- | :--- | :--- | :--- | + | name | String | 是 | 人员姓名 | + | groupId | Long | 否 | 所属分组ID | + | photo | File | 是 | 人脸照片文件 (jpg/png) | + +* **返回结果**: + ```json + { + "code": 200, + "msg": "success", + "data": { + "id": 101, + "name": "张三", + "groupId": 2, + "feature": "..." // (内部可能不直接返回长特征，视具体实现而定) + } + } + ``` + +#### 1.2.2 编辑人员信息 +用于更新人员姓名、分组或重新上传人脸照片。 + +* **接口地址**: `/users/update/{id}` +* **请求方式**: `POST` +* **请求类型**: `multipart/form-data` +* **路径参数**: + * `id`: 人员ID (Long) + +* **请求参数**: + + | 参数名 | 类型 | 必填 | 说明 | + | :--- | :--- | :--- | :--- | + | name | String | 是 | 人员姓名 | + | groupId | Long | 否 | 所属分组ID (不传则不修改) | + | photo | File | 否 | 新的人脸照片 (不传则不修改) | + +* **返回结果**: + ```json + { + "code": 200, + "msg": "success", + "data": { ... } + } + ``` + +#### 1.2.3 获取人员列表 (查询) +* **接口地址**: `/users/list` +* **请求方式**: `GET` +* **请求参数**: + + | 参数名 | 类型 | 必填 | 说明 | + | :--- | :--- | :--- | :--- | + | name | String | 否 | 按姓名模糊查询 | + | groupId | Long | 否 | 按分组ID筛选 | + +* **返回结果**: + ```json + { + "code": 200, + "msg": "success", + "data": [ ...User Objects... ] + } + ``` + +#### 1.2.4 人脸搜索 (1:N 检索) +用于上传一张人脸照片，并在指定分组内检索最相似的人员。 + +* **接口地址**: `/users/search` +* **请求方式**: `POST` +* **请求类型**: `multipart/form-data` +* **请求参数**: + + | 参数名 | 类型 | 必填 | 说明 | + | :--- | :--- | :--- | :--- | + | photo | File | 是 | 待检索的人脸照片 | + | groupId | Long | 是 | 目标分组ID | + +* **返回结果**: + + **成功找到匹配**: + ```json + { + "code": 200, + "msg": "success", + "data": { + "id": 101, + "name": "张三", + "groupId": 2, + ... + } + } + ``` + + **未找到匹配 (相似度低于阈值 0.6)**: + ```json + { + "code": 404, + "msg": "未找到匹配用户" + } + ``` + +--- + +## 2. 算法服务接口 (Python - FaceFeatureExtractor) + +该接口通常由 Java 后端内部调用，但如果开发人员需要独立调试算法或进行集成，可直接调用该微服务。 + +**功能**: 接收图片，进行质量检测（人脸检测、模糊度、亮度、姿态等），合格后提取 1024 维人脸特征向量。 + +**默认端口**: `8000` (具体取决于 docker-compose 配置) + +### 2.1 提取人脸特征 +* **接口地址**: `/api/extract_feature` +* **请求方式**: `POST` +* **请求类型**: `multipart/form-data` +* **请求参数**: + + | 参数名 | 类型 | 必填 | 说明 | + | :--- | :--- | :--- | :--- | + | image | File | 是 | 图片文件 (支持 jpg, png 等常见格式) | + +* **返回结果 (JSON)**: + + **成功响应**: + ```json + { + "success": true, + "message": "Success", + "feature": [0.123, -0.456, ...], // 1024维浮点数组 + "feature_dim": 1024, + "processing_time": 0.045 + } + ``` + + **失败/质量不合格响应**: + ```json + { + "success": false, + "message": "No face detected" // 或 "Face quality check failed...", "Server error..." + } + ``` + +### 2.2 健康检查 +* **接口地址**: `/health` +* **请求方式**: `GET` +* **返回结果**: `{"status": "healthy", "service": "Face Feature Extractor"}` diff --git a/backend-java/src/main/java/com/bonuos/face/controller/UserController.java b/backend-java/src/main/java/com/bonuos/face/controller/UserController.java index 9821e7d..c0f732e 100644 --- a/backend-java/src/main/java/com/bonuos/face/controller/UserController.java +++ b/backend-java/src/main/java/com/bonuos/face/controller/UserController.java @@ -106,4 +106,23 @@ public class UserController { result.put("data", count); return result; } + + @PostMapping("/search") + public Map searchUser( + @RequestParam("photo") MultipartFile photo, + @RequestParam("groupId") Long groupId) { + + User user = userService.searchUser(photo, groupId); + + Map result = new HashMap<>(); + if (user != null) { + result.put("code", 200); + result.put("msg", "success"); + result.put("data", user); + } else { + result.put("code", 404); + result.put("msg", "未找到匹配用户"); + } + return result; + } } diff --git a/backend-java/src/main/java/com/bonuos/face/service/UserService.java b/backend-java/src/main/java/com/bonuos/face/service/UserService.java index 0a2ae99..641ad90 100644 --- a/backend-java/src/main/java/com/bonuos/face/service/UserService.java +++ b/backend-java/src/main/java/com/bonuos/face/service/UserService.java @@ -58,5 +58,14 @@ public interface UserService { * * @param id 用户ID */ + /** + * 人脸搜索 + * + * @param photo 人脸照片 + * @param groupId 分组ID + * @return 匹配的用户（如果匹配度过低返回null） + */ + User searchUser(MultipartFile photo, Long groupId); + void deleteUser(Long id); } diff --git a/backend-java/src/main/java/com/bonuos/face/service/impl/UserServiceImpl.java b/backend-java/src/main/java/com/bonuos/face/service/impl/UserServiceImpl.java index 8e8d7c5..b22ea5f 100644 --- a/backend-java/src/main/java/com/bonuos/face/service/impl/UserServiceImpl.java +++ b/backend-java/src/main/java/com/bonuos/face/service/impl/UserServiceImpl.java @@ -41,6 +41,8 @@ public class UserServiceImpl implements UserService { if (userGroupMapper.selectById(groupId) == null) { throw new RuntimeException("指定的用户分组不存在"); } + // 检查重名 + checkDuplicateName(name, groupId, null); } // 确保上传目录存在 @@ -142,6 +144,12 @@ public class UserServiceImpl implements UserService { throw new RuntimeException("指定的用户分组不存在"); } } + + // 如果修改了名字或分组，检查重名 + if (!user.getName().equals(name) || (groupId != null && !groupId.equals(user.getGroupId()))) { + checkDuplicateName(name, groupId != null ? groupId : user.getGroupId(), id); + } + user.setName(name); user.setGroupId(groupId); user.setUpdateTime(LocalDateTime.now()); @@ -220,4 +228,90 @@ public class UserServiceImpl implements UserService { } } } + + @Override + public User searchUser(MultipartFile photo, Long groupId) { + if (groupId == null) { + throw new RuntimeException("必须指定分组ID"); + } + + // 1. 保存上传的照片 (临时) + String fileName = IdUtil.fastSimpleUUID() + "_" + photo.getOriginalFilename(); + File uploadDir = new File(uploadPath); + if (!uploadDir.exists()) { + uploadDir.mkdirs(); + } + File dest = new File(uploadDir, fileName); + + try { + photo.transferTo(dest); + } catch (IOException e) { + throw new RuntimeException("照片处理失败", e); + } + + try { + // 2. 提取特征 + List targetFeature = faceFeatureExtractorClient.extractFeature(dest); + if (targetFeature == null || targetFeature.isEmpty()) { + throw new RuntimeException("未能从上传图片中提取到人脸特征"); + } + + // 3. 获取分组下所有用户 + List users = getUsers(null, groupId); + if (users == null || users.isEmpty()) { + return null; + } + + // 4. 比对特征 + User bestMatch = null; + float maxSimilarity = 0f; + float threshold = 0.6f; // 相似度阈值 + + for (User user : users) { + if (user.getFeatureData() == null) + continue; + + List dbFeature = com.bonuos.face.util.FaceUtils.parseFeatureData(user.getFeatureData()); + if (dbFeature != null) { + float similarity = com.bonuos.face.util.FaceUtils.cosineSimilarity(targetFeature, dbFeature); + if (similarity > maxSimilarity) { + maxSimilarity = similarity; + bestMatch = user; + } + } + } + + // 5. 返回结果 + if (maxSimilarity >= threshold) { + return bestMatch; + } + return null; // 未找到匹配 + + } catch (Exception e) { + throw new RuntimeException("人脸搜索失败: " + e.getMessage(), e); + } finally { + // 清理临时文件 + if (dest.exists()) { + dest.delete(); + } + } + } + + /** + * 检查分组下是否存在同名用户 + */ + private void checkDuplicateName(String name, Long groupId, Long excludeId) { + com.baomidou.mybatisplus.core.conditions.query.QueryWrapper wrapper = new com.baomidou.mybatisplus.core.conditions.query.QueryWrapper<>(); + wrapper.eq("group_id", groupId) + .eq("name", name) + .eq("status", 1); // 只检查有效用户 + + if (excludeId != null) { + wrapper.ne("id", excludeId); + } + + if (userMapper.selectCount(wrapper) > 0) { + throw new RuntimeException("该分组下已存在名为 [" + name + "] 的用户"); + } + } } diff --git a/backend-java/src/main/java/com/bonuos/face/util/FaceUtils.java b/backend-java/src/main/java/com/bonuos/face/util/FaceUtils.java new file mode 100644 index 0000000..9de2a47 --- /dev/null +++ b/backend-java/src/main/java/com/bonuos/face/util/FaceUtils.java @@ -0,0 +1,58 @@ +package com.bonuos.face.util; + +import com.fasterxml.jackson.core.type.TypeReference; +import com.fasterxml.jackson.databind.ObjectMapper; + +import java.util.List; + +public class FaceUtils { + + private static final ObjectMapper objectMapper = new ObjectMapper(); + + /** + * 计算两个特征向量的余弦相似度 + * + * @param feature1 特征向量1 + * @param feature2 特征向量2 + * @return 相似度 [-1, 1] + */ + public static float cosineSimilarity(List feature1, List feature2) { + if (feature1 == null || feature2 == null || feature1.size() != feature2.size() || feature1.isEmpty()) { + return -1f; + } + + float dotProduct = 0.0f; + float normA = 0.0f; + float normB = 0.0f; + + for (int i = 0; i < feature1.size(); i++) { + dotProduct += feature1.get(i) * feature2.get(i); + normA += Math.pow(feature1.get(i), 2); + normB += Math.pow(feature2.get(i), 2); + } + + if (normA == 0 || normB == 0) { + return 0.0f; + } + + return (float) (dotProduct / (Math.sqrt(normA) * Math.sqrt(normB))); + } + + /** + * 解析特征数据字符串 + * + * @param featureDataJson JSON字符串 [0.1, 0.2, ...] + * @return 特征列表 + */ + public static List parseFeatureData(String featureDataJson) { + if (featureDataJson == null || featureDataJson.isEmpty()) { + return null; + } + try { + return objectMapper.readValue(featureDataJson, new TypeReference>() { + }); + } catch (Exception e) { + return null; + } + } +} diff --git a/backend-java/target/classes/com/bonuos/face/controller/UserController.class b/backend-java/target/classes/com/bonuos/face/controller/UserController.class 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cv2.circle(img, (320, 240), 100, (255, 255, 255), -1) + cv2.imwrite(filename, img) + return filename + +def test_python_health(): + """测试 Python 算法服务健康检查""" + url = f"{PYTHON_ALGO_URL}/health" + print(f"\n[Testing] Python Algorithm Service Health ({url})...") + try: + response = requests.get(url, timeout=5) + if response.status_code == 200: + print(f"✅ Success: {response.json()}") + else: + print(f"❌ Failed: Status {response.status_code}, Response: {response.text}") + except requests.exceptions.ConnectionError: + print("❌ Failed: Connection refused. Is the service running on port 18000?") + except Exception as e: + print(f"❌ Error: {e}") + +def test_extract_feature(image_path): + """测试人脸特征提取接口""" + url = f"{PYTHON_ALGO_URL}/api/extract_feature" + print(f"\n[Testing] Face Feature Extraction ({url})...") + + if not os.path.exists(image_path): + print("❌ Error: Test image not found.") + return + + try: + with open(image_path, 'rb') as f: + files = {'image': f} + response = requests.post(url, files=files, timeout=10) + + if response.status_code == 200: + result = response.json() + if result.get('success'): + dim = result.get('feature_dim') + print(f"✅ Success: Feature extracted. Dimension: {dim}") + else: + # 预期内失败，因为我们的假脸可能过不了检测，但这证明接口通了 + print(f"⚠️ Service Reachable (Logic Result): {result.get('message')}") + else: + print(f"❌ Failed: Status {response.status_code}, Response: {response.text}") + except requests.exceptions.ConnectionError: + print("❌ Failed: Connection refused.") + except Exception as e: + print(f"❌ Error: {e}") + +def test_java_group_list(): + """测试 Java 后端分组列表接口""" + url = f"{JAVA_BACKEND_URL}/api/groups/list" + print(f"\n[Testing] Java Backend Group List ({url})...") + try: + response = requests.get(url, timeout=5) + if response.status_code == 200: + data = response.json() + if data.get('code') == 200: + print(f"✅ Success: Retrieved {len(data.get('data', []))} groups.") + print(f" Response: {json.dumps(data, ensure_ascii=False)}") + else: + print(f"❌ Functional Error: {data}") + else: + print(f"❌ Failed: Status {response.status_code}, Response: {response.text}") + except requests.exceptions.ConnectionError: + print("❌ Failed: Connection refused. Is the service running on port 18080?") + except Exception as e: + print(f"❌ Error: {e}") + +if __name__ == "__main__": + print("=== Face Recognition System Quick Test ===") + + # 1. 准备测试图片 + test_img = create_test_image() + + # 2. 测试算法服务 + test_python_health() + test_extract_feature(test_img) + + # 3. 测试Java后端 + test_java_group_list() + + print("\n=== Test Finished ===") + # 清理生成的测试图 (可选，这里保留以便用户查看) + # if os.path.exists(test_img): + # os.remove(test_img) diff --git a/verify_changes.py b/verify_changes.py new file mode 100644 index 0000000..2ad92d4 --- /dev/null +++ b/verify_changes.py @@ -0,0 +1,78 @@ + +import requests +import json +import os + +# 配置 +BASE_URL = "http://localhost:18080/api" +GROUP_NAME = "TestGroup_Verify" +USER_NAME = "DuplicateTestUser" +TEST_IMG = "verify_face.jpg" + +def create_test_image(): + if not os.path.exists(TEST_IMG): + # 创建一个简单的dummy文件 + with open(TEST_IMG, 'wb') as f: + f.write(b'\xFF\xD8\xFF\xE0' + b'\x00' * 1000) # Fake JPG header + return TEST_IMG + +def run_verification(): + print("=== 开始验证 ===") + + # 1. 创建测试分组 + print("\n1. 创建分组...") + resp = requests.post(f"{BASE_URL}/groups/add", json={"name": GROUP_NAME}) + if resp.status_code == 200 and resp.json()['code'] == 200: + group_id = resp.json()['data']['id'] + print(f"✅ 分组创建成功 ID: {group_id}") + else: + print(f"❌ 分组创建失败: {resp.text}") + return + + # 准备图片 + create_test_image() + files = {'photo': open(TEST_IMG, 'rb')} + + # 2. 添加用户 (第一次) + print("\n2. 添加用户 (预期成功)...") + data = {"name": USER_NAME, "groupId": group_id} + # Re-open file for each request + resp = requests.post(f"{BASE_URL}/users/add", data=data, files={'photo': open(TEST_IMG, 'rb')}) + + if resp.status_code == 200 and resp.json()['code'] == 200: + print(f"✅ 用户创建成功") + else: + # 如果是因为测试图片无法提取特征而失败，也是预期的(说明代码跑到了特征提取那一步) + # 但我们主要验证重名逻辑，所以这里假设如果失败是因为重名则是有问题，如果是因为特征提取则是环境问题 + print(f"⚠️ 用户创建返回: {resp.json().get('msg')}") + + # 3. 添加同名用户 (预期失败) + print("\n3. 再次添加同名用户 (预期被拦截)...") + resp = requests.post(f"{BASE_URL}/users/add", data=data, files={'photo': open(TEST_IMG, 'rb')}) + + res_json = resp.json() + if res_json.get('code') != 200 and "已存在" in str(res_json.get('msg')): + print(f"✅ 成功拦截重名用户: {res_json.get('msg')}") + else: + print(f"❌ 拦截失败或错误信息不匹配: {resp.text}") + + # 4. 测试搜索接口 + print("\n4. 测试人脸搜索接口...") + try: + resp = requests.post(f"{BASE_URL}/users/search", data={"groupId": group_id}, files={'photo': open(TEST_IMG, 'rb')}) + if resp.status_code == 200: + print(f"✅ 接口调用成功: {resp.json()}") + elif resp.status_code == 404: + print(f"✅ 接口调用成功 (未找到匹配 - 符合预期): {resp.json()}") + else: + print(f"❌ 接口调用异常: {resp.status_code} - {resp.text}") + except Exception as e: + print(f"❌ 请求异常: {e}") + + print("\n=== 验证结束 ===") + +if __name__ == "__main__": + try: + run_verification() + except Exception as e: + print(f"Fatal Error: {e}")