diff --git a/face_crop_1_scale_0.3.jpg b/face_crop_1_scale_0.3.jpg
deleted file mode 100644
index b1ebc77..0000000
Binary files a/face_crop_1_scale_0.3.jpg and /dev/null differ
diff --git a/face_crop_1_scale_0.6.jpg b/face_crop_1_scale_0.6.jpg
deleted file mode 100644
index 171acc5..0000000
Binary files a/face_crop_1_scale_0.6.jpg and /dev/null differ
diff --git a/quick_test_api.py b/quick_test_api.py
deleted file mode 100644
index a1b3089..0000000
--- a/quick_test_api.py
+++ /dev/null
@@ -1,103 +0,0 @@
-
-import requests
-import json
-import cv2
-import numpy as np
-import os
-
-# 配置服务地址
-JAVA_BACKEND_URL = "http://localhost:18080"
-PYTHON_ALGO_URL = "http://localhost:18000"
-
-def create_test_image(filename="test_face.jpg"):
-    """创建一张简单的测试图片（如果不存在）"""
-    if not os.path.exists(filename):
-        print(f"Creating test image: {filename}...")
-        # 创建一个 640x480 的黑色图像
-        img = np.zeros((480, 640, 3), np.uint8)
-        # 画一个简单的圆代表"脸" (虽然检测不到，但可以测试文件上传流程)
-        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/result_detected.jpg b/result_detected.jpg
deleted file mode 100644
index a9bc226..0000000
Binary files a/result_detected.jpg and /dev/null differ
diff --git a/result_detected_scale_0.3.jpg b/result_detected_scale_0.3.jpg
deleted file mode 100644
index 6691c05..0000000
Binary files a/result_detected_scale_0.3.jpg and /dev/null differ
diff --git a/result_detected_scale_0.6.jpg b/result_detected_scale_0.6.jpg
deleted file mode 100644
index f995fe5..0000000
Binary files a/result_detected_scale_0.6.jpg and /dev/null differ
diff --git a/test_detect_face.py b/test_detect_face.py
deleted file mode 100644
index 1ce6d11..0000000
--- a/test_detect_face.py
+++ /dev/null
@@ -1,126 +0,0 @@
-import requests
-import cv2
-import numpy as np
-import os
-import json
-import argparse
-import sys
-
-# 配置服务地址
-PYTHON_ALGO_URL = "http://192.168.0.37:18000"
-
-def get_default_image_path():
-    """获取一个默认存在的测试图片路径"""
-    # 尝试找一个存在的真实图片
-    potential_paths = [
-        r"C:\Users\24830\Desktop\人脸.jpg",
-    ]
-    for path in potential_paths:
-        if os.path.exists(path):
-            return path
-    return None
-
-def detect_and_draw(image_path, expand_scale=0.0):
-    url = f"{PYTHON_ALGO_URL}/api/detect_face"
-    print(f"\n[Processing] Image: {image_path}")
-    print(f"[API URL] {url}")
-    print(f"[Expand Scale] {expand_scale}")
-    
-    if not os.path.exists(image_path):
-        print(f"❌ Error: Image file not found: {image_path}")
-        return
-
-    try:
-        # 1. 准备发送请求
-        # 读取图片用于显示/画框
-        img_array = np.fromfile(image_path, dtype=np.uint8)
-        original_img = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
-        
-        if original_img is None:
-             print(f"❌ Error: Failed to read image using opencv: {image_path}")
-             return
-
-        # 2. 调用API
-        data = {'expand_scale': expand_scale}
-        with open(image_path, 'rb') as f:
-            files = {'image': f}
-            # 注意: 使用 data=data 发送表单数据，而不是 params=params (查询参数)
-            response = requests.post(url, files=files, data=data, timeout=10)
-        
-        if response.status_code != 200:
-            print(f"❌ Failed: Status {response.status_code}, Response: {response.text}")
-            return
-
-        result = response.json()
-        print("\n=== API Response ===")
-        print(json.dumps(result, indent=2))
-
-        # 3. 处理结果并画图
-        if result.get('success'):
-            faces = result.get('faces', [])
-            count = len(faces)
-            print(f"\n✅ Success: Detected {count} faces.")
-            
-            # 创建副本用于画图
-            draw_img = original_img.copy()
-
-            for i, face in enumerate(faces):
-                x1 = int(face['x1'])
-                y1 = int(face['y1'])
-                x2 = int(face['x2'])
-                y2 = int(face['y2'])
-                score = face['score']
-                
-                # 画矩形框
-                # 颜色 (B, G, R) - 绿色
-                color = (0, 255, 0)
-                thickness = 2
-                cv2.rectangle(draw_img, (x1, y1), (x2, y2), color, thickness)
-                
-                # 写文字
-                label = f"Face {i+1}: {score:.2f}"
-                cv2.putText(draw_img, label, (x1, y1 - 10), 
-                           cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
-                
-                print(f"  - Face {i+1}: Box({x1}, {y1}, {x2}, {y2}), Score: {score:.4f}")
-
-                # 保存裁剪的人脸图观察效果
-                face_crop = original_img[y1:y2, x1:x2]
-                if face_crop.size > 0:
-                    crop_filename = f"face_crop_{i+1}_scale_{expand_scale}.jpg"
-                    cv2.imencode('.jpg', face_crop)[1].tofile(crop_filename)
-                    print(f"    Saved crop: {crop_filename}")
-
-            # 4. 保存结果图
-            output_filename = f"result_detected_scale_{expand_scale}.jpg"
-            cv2.imencode('.jpg', draw_img)[1].tofile(output_filename)
-            print(f"\n✅ Result image saved to: {os.path.abspath(output_filename)}")
-            
-        else:
-            print(f"⚠️ API logic returned failure: {result.get('message')}") 
-
-    except Exception as e:
-        print(f"❌ Error: {e}")
-        import traceback
-        traceback.print_exc()
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description='Face Detection API Test Script')
-    parser.add_argument('image_path', nargs='?', help='Path to the image file')
-    parser.add_argument('--scale', type=float, default=0.6, help='Expand scale (default: 0.0)')
-    
-    args = parser.parse_args()
-    
-    target_path = args.image_path
-    
-    if not target_path:
-        default_path = get_default_image_path()
-        if default_path:
-            print(f"No image path provided, using default found: {default_path}")
-            target_path = default_path
-        else:
-            print("Usage: python test_detect_face.py <path_to_image> [--scale 0.3]")
-            print("Error: No image path provided and no default test image found.")
-            sys.exit(1)
-            
-    detect_and_draw(target_path, args.scale)
diff --git a/verify_changes.py b/verify_changes.py
deleted file mode 100644
index 2ad92d4..0000000
--- a/verify_changes.py
+++ /dev/null
@@ -1,78 +0,0 @@
-
-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}")