diff --git a/.vscode/settings.json b/.vscode/settings.json
new file mode 100644
index 0000000..a8c2003
--- /dev/null
+++ b/.vscode/settings.json
@@ -0,0 +1,5 @@
+{
+    "python-envs.defaultEnvManager": "ms-python.python:conda",
+    "python-envs.defaultPackageManager": "ms-python.python:conda",
+    "python-envs.pythonProjects": []
+}
\ No newline at end of file
diff --git a/Ai_tottle/ai_tottle_api copy.py b/Ai_tottle/ai_tottle_api copy.py
new file mode 100644
index 0000000..12d14cd
--- /dev/null
+++ b/Ai_tottle/ai_tottle_api copy.py	
@@ -0,0 +1,370 @@
+from sanic import Sanic, json, Blueprint,response
+from sanic.exceptions import Unauthorized
+from sanic.response import json as json_response
+from sanic_cors import CORS
+import numpy as np
+import logging
+import uuid
+import os,traceback
+import asyncio
+from ai_image import process_images  # 你实现的图片处理函数
+from queue import Queue
+from map_find import map_process_images
+from yolo_train import auto_train
+import torch
+from yolo_photo import map_process_images_with_progress # 引入你的处理函数
+from tiles import TilesetProcessor
+# 日志配置
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+logger = logging.getLogger(__name__)
+
+###################################################################################验证中间件和管理件##############################################################################################
+
+async def token_and_resource_check(request):
+    # --- Token 验证 ---
+    token = request.headers.get('X-API-Token')
+    expected_token = request.app.config.get("VALID_TOKEN")
+    if not token or token != expected_token:
+        logger.warning(f"Unauthorized request with token: {token}")
+        raise Unauthorized("Invalid token")
+
+    # --- GPU 使用率检查 ---
+    try:
+        if torch.cuda.is_available():
+            num_gpus = torch.cuda.device_count()
+            max_usage_ratio = request.app.config.get("MAX_GPU_USAGE", 0.9)  # 默认90%
+
+            for i in range(num_gpus):
+                used = torch.cuda.memory_reserved(i)
+                total = torch.cuda.max_memory_reserved(i)
+                ratio = used / total if total else 0
+
+                logger.info(f"GPU {i} Usage: {ratio:.2%}")
+
+                if ratio > max_usage_ratio:
+                    logger.warning(f"GPU {i} usage too high: {ratio:.2%}")
+                    return json_response({
+                        "status": "error",
+                        "message": f"GPU resource busy (GPU {i} at {ratio:.2%}). Try later."
+                    }, status=503)
+    except Exception as e:
+        logger.error(f"GPU check failed: {e}")
+
+    return None  # 允许请求继续
+
+##################################################################################################################################################################################################    
+#创建Sanic应用
+app = Sanic("ai_Service_v2")
+CORS(app) # 允许跨域请求
+task_progress = {}
+
+@app.middleware("request")
+async def global_middleware(request):
+    result = await token_and_resource_check(request)
+    if result:
+        return result
+
+# 配置Token和最大GPU使用率
+app.config.update({
+    "VALID_TOKEN": "Beidou_b8609e96-bfec-4485-8c64-6d4f662ee44a",
+    "MAX_GPU_USAGE": 0.9
+})
+    
+######################################################################地图切割相关的API########################################################################################################
+#创建地图的蓝图
+map_tile_blueprint = Blueprint('map', url_prefix='/map/')
+app.blueprint(map_tile_blueprint)
+
+# @map_tile_blueprint.post("/compare_tilesets")
+# async def compare_tilesets(request):
+#     '''
+#     接口：/map/compare_tilesets
+#     输入 JSON:
+#     {
+#     "tileset1": "path/to/tileset1/tileset.json",
+#     "tileset2": "path/to/tileset2/tileset.json",
+#     "bounds": [500000, 3000000, 500100, 3000100],
+#     "resolution": 1.0,
+#     "output": "results"
+#     }
+#     输出 JSON:
+#     {
+#     "success": true,
+#     "message": "分析完成",
+#     "data": {
+#         "csv_path": "results/height_differences.csv",
+#         "heatmap_path": "results/height_difference_heatmap.png",
+#         "summary": {
+#         "mean": 0.28,
+#         "max": 1.10,
+#         "min": -0.85,
+#         "std": 0.23
+#         }
+#     }
+#     }
+#     '''
+#     try:
+#         body = request.json
+
+#         # 参数提取与验证
+#         tileset1 = body.get("tileset1")
+#         tileset2 = body.get("tileset2")
+#         bounds = body.get("bounds")
+#         resolution = body.get("resolution", 1.0)
+#         output = body.get("output", "results")
+
+#         if not all([tileset1, tileset2, bounds]):
+#             return response.json({"success": False, "message": "参数不完整"}, status=400)
+
+#         processor = TilesetProcessor(tileset1, tileset2, resolution)
+
+#         if not processor.set_analysis_area(bounds):
+#             return response.json({"success": False, "message": "设置分析区域失败"}, status=400)
+
+#         if not processor.sample_heights():
+#             return response.json({"success": False, "message": "高度采样失败"}, status=500)
+
+#         processor.export_results(output)
+
+#         # 汇总统计结果
+#         valid_differences = processor.height_difference_grid[~np.isnan(processor.height_difference_grid)]
+#         summary = {
+#             "mean": float(np.mean(valid_differences)),
+#             "max": float(np.max(valid_differences)),
+#             "min": float(np.min(valid_differences)),
+#             "std": float(np.std(valid_differences))
+#         }
+
+#         return response.json({
+#             "success": True,
+#             "message": "分析完成",
+#             "data": {
+#                 "csv_path": os.path.join(output, "height_differences.csv"),
+#                 "heatmap_path": os.path.join(output, "height_difference_heatmap.png"),
+#                 "summary": summary
+#             }
+#         })
+
+#     except Exception as e:
+#         traceback.print_exc()
+#         return response.json({"success": False, "message": str(e)}, status=500)
+    
+#语义识别
+@map_tile_blueprint.post("/uav")
+async def process_handler(request):
+    """
+    接口：/map/uav
+    输入 JSON:
+    {
+    "urls": [
+        "http://example.com/img1.jpg",
+        "http://example.com/img2.jpg"
+    ],
+    "yaml_name": "config",
+    "bucket_name": "300bdf2b-a150-406e-be63-d28bd29b409f",
+    "bucket_directory": "2025/seg"
+    "model_path": "deeplabv3plus_best.pth"
+    }
+    输出 JSON:
+        {
+    "code": 200,
+    "msg": "success",
+    "data": [
+        "http://minio.example.com/uav-results/2025/seg/result1.png",
+        "http://minio.example.com/uav-results/2025/seg/result2.png"
+    ]
+    }
+    
+    """
+    try:
+        body = request.json
+        urls = body.get("urls", [])
+        yaml_name = body.get("yaml_name")
+        bucket_name = body.get("bucket_name")
+        bucket_directory = body.get("bucket_directory")
+        model_path = os.path.join("map", "checkpoints", body.get("model_path"))
+
+        # 校验参数
+        if not urls or not isinstance(urls, list):
+            return json({"code": 400, "msg": "Missing or invalid 'urls'"})
+        if not all([yaml_name, bucket_name, bucket_directory]):
+            return json({"code": 400, "msg": "Missing required parameters"})
+
+        # 调用图像处理函数
+        result = map_process_images(urls, yaml_name, bucket_name, bucket_directory,model_path)
+        return json(result)
+
+    except Exception as e:
+        return json({"code": 500, "msg": f"Server error: {str(e)}"})
+    
+######################################################################yolo相关的API########################################################################################################
+#创建yolo的蓝图
+yolo_tile_blueprint = Blueprint('yolo', url_prefix='/yolo/')
+app.blueprint(yolo_tile_blueprint)
+
+# YOLO URL APT
+# 存储任务进度和结果（内存示例，可用 Redis 或 DB 持久化）
+
+@yolo_tile_blueprint.post("/process_images")
+async def process_images(request):
+    """
+    {
+  "urls": [
+    "http://example.com/image1.jpg",
+    "http://example.com/image2.jpg",
+    "http://example.com/image3.jpg"
+  ],
+  "yaml_name": "your_minio_config",
+  "bucket_name": "my-bucket",
+  "bucket_directory": "2025/uav-results",
+  "model_path": "deeplabv3plus_best.pth"
+}
+    """
+    data = request.json
+    urls = data.get("urls")
+    yaml_name = data.get("yaml_name")
+    bucket_name = data.get("bucket_name")
+    bucket_directory = data.get("bucket_directory")
+    uav_model_path = data.get("uav_model_path")
+
+    if not urls or not yaml_name or not bucket_name or not uav_model_path:
+        return response.json({"code": 400, "msg": "Missing parameters"}, status=400)
+
+    task_id = str(uuid.uuid4())
+    task_progress[task_id] = {"status": "pending", "progress": 0, "result": None}
+
+    # 启动后台任务
+    asyncio.create_task(run_image_processing(task_id, urls, yaml_name, bucket_name, bucket_directory, uav_model_path))
+
+    return response.json({"code": 200, "msg": "Task started", "task_id": task_id})
+
+@yolo_tile_blueprint.get("/task_status/<task_id>")
+async def task_status(request, task_id):
+    progress = task_progress.get(task_id)
+    if not progress:
+        return response.json({"code": 404, "msg": "Task not found"}, status=404)
+    return response.json({"code": 200, "msg": "Task status", "data": progress})
+
+async def run_image_processing(task_id, urls, yaml_name, bucket_name, bucket_directory, uav_model_path):
+   
+
+    try:
+        task_progress[task_id]["status"] = "running"
+        task_progress[task_id]["progress"] = 10  # 开始进度
+
+        # 下载、推理、上传阶段分别更新进度
+        def progress_callback(stage, percent):
+            task_progress[task_id]["status"] = stage
+            task_progress[task_id]["progress"] = percent
+
+        result = await asyncio.to_thread(
+            map_process_images_with_progress,
+            urls, yaml_name, bucket_name, bucket_directory, uav_model_path, progress_callback
+        )
+
+        task_progress[task_id]["status"] = "completed"
+        task_progress[task_id]["progress"] = 100
+        task_progress[task_id]["result"] = result
+
+    except Exception as e:
+        task_progress[task_id]["status"] = "failed"
+        task_progress[task_id]["progress"] = 100
+        task_progress[task_id]["result"] = str(e)
+        
+# YOLO检测API
+@yolo_tile_blueprint.post("/picture")
+async def yolo_detect_api(request):
+    try:
+        
+        detect_data = request.json
+        
+        # 解析必要字段
+        image_list = detect_data.get("image_list")
+        yolo_model = detect_data.get("yolo_model", "best.pt")
+        class_filter = detect_data.get("class", None)
+        minio_info = detect_data.get("minio", None)
+
+        if not image_list:
+            return json_response({"status": "error", "message": "image_list is required"}, status=400)
+
+        if not minio_info:
+            return json_response({"status": "error", "message": "MinIO information is required"}, status=400)
+
+        # 创建临时文件夹
+        input_folder = f"./temp_input_{str(uuid.uuid4())}"
+        output_folder = f"./temp_output_{str(uuid.uuid4())}"
+
+        # 执行图像处理
+        result = await asyncio.to_thread(
+            process_images,
+            yolo_model=yolo_model,
+            image_list=image_list,
+            class_filter=class_filter,
+            input_folder=input_folder,
+            output_folder=output_folder,
+            minio_info=minio_info
+        )
+
+        # 返回处理结果
+        return json_response(result)
+
+    except Exception as e:
+        logger.error(f"Error occurred while processing request: {str(e)}", exc_info=True)
+        return json_response({
+            "status": "error",
+            "message": f"Internal server error: {str(e)}"
+        }, status=500)
+        
+# YOLO自动训练
+@yolo_tile_blueprint.post("/train")
+async def yolo_train_api(request):
+    """
+    自动训练模型
+    输入 JSON:
+    {
+        "db_host": str,
+        "db_database": str,
+        "db_user": str,
+        "db_password": str,
+        "db_port": int,
+        "model_id": int,
+        "img_path": str,
+        "label_path": str,
+        "new_path": str,
+        "split_list": List[float],
+        "class_names": Optional[List[str]],
+        "project_name": str
+    }
+    输出 JSON:
+    {
+        "base_metrics": Dict[str, float],
+        "best_model_path": str,
+        "final_metrics": Dict[str, float]
+    }
+
+    """
+    try:
+        # 修改为直接访问 request.json 而不是调用它
+        data = request.json
+        
+
+        if not data:
+            return json_response({"status": "error", "message": "data is required"}, status=400)
+
+        # 执行图像处理
+        result = await asyncio.to_thread(
+            auto_train,
+            data
+        )
+        # 返回处理结果
+        return json_response(result)
+    
+    except Exception as e:
+        logger.error(f"Error occurred while processing request: {str(e)}", exc_info=True)
+        return json_response({
+            "status": "error",
+            "message": f"Internal server error: {str(e)}"
+        }, status=500)
+
+if __name__ == '__main__':
+    app.run(host="0.0.0.0", port=12366, debug=True,workers=1)
diff --git a/Ai_tottle/ai_tottle_api.py b/Ai_tottle/ai_tottle_api.py
index ed733fb..a86b9d4 100644
--- a/Ai_tottle/ai_tottle_api.py
+++ b/Ai_tottle/ai_tottle_api.py
@@ -75,80 +75,6 @@ app.config.update({
 map_tile_blueprint = Blueprint('map', url_prefix='/map/')
 app.blueprint(map_tile_blueprint)
 
-@map_tile_blueprint.post("/compare_tilesets")
-async def compare_tilesets(request):
-    '''
-    接口：/map/compare_tilesets
-    输入 JSON:
-    {
-    "tileset1": "path/to/tileset1/tileset.json",
-    "tileset2": "path/to/tileset2/tileset.json",
-    "bounds": [500000, 3000000, 500100, 3000100],
-    "resolution": 1.0,
-    "output": "results"
-    }
-    输出 JSON:
-    {
-    "success": true,
-    "message": "分析完成",
-    "data": {
-        "csv_path": "results/height_differences.csv",
-        "heatmap_path": "results/height_difference_heatmap.png",
-        "summary": {
-        "mean": 0.28,
-        "max": 1.10,
-        "min": -0.85,
-        "std": 0.23
-        }
-    }
-    }
-    '''
-    try:
-        body = request.json
-
-        # 参数提取与验证
-        tileset1 = body.get("tileset1")
-        tileset2 = body.get("tileset2")
-        bounds = body.get("bounds")
-        resolution = body.get("resolution", 1.0)
-        output = body.get("output", "results")
-
-        if not all([tileset1, tileset2, bounds]):
-            return response.json({"success": False, "message": "参数不完整"}, status=400)
-
-        processor = TilesetProcessor(tileset1, tileset2, resolution)
-
-        if not processor.set_analysis_area(bounds):
-            return response.json({"success": False, "message": "设置分析区域失败"}, status=400)
-
-        if not processor.sample_heights():
-            return response.json({"success": False, "message": "高度采样失败"}, status=500)
-
-        processor.export_results(output)
-
-        # 汇总统计结果
-        valid_differences = processor.height_difference_grid[~np.isnan(processor.height_difference_grid)]
-        summary = {
-            "mean": float(np.mean(valid_differences)),
-            "max": float(np.max(valid_differences)),
-            "min": float(np.min(valid_differences)),
-            "std": float(np.std(valid_differences))
-        }
-
-        return response.json({
-            "success": True,
-            "message": "分析完成",
-            "data": {
-                "csv_path": os.path.join(output, "height_differences.csv"),
-                "heatmap_path": os.path.join(output, "height_difference_heatmap.png"),
-                "summary": summary
-            }
-        })
-
-    except Exception as e:
-        traceback.print_exc()
-        return response.json({"success": False, "message": str(e)}, status=500)
-    
 #语义识别
 @map_tile_blueprint.post("/uav")
 async def process_handler(request):
diff --git a/Ai_tottle/temp.glb b/Ai_tottle/temp.glb
new file mode 100644
index 0000000..a60447e
Binary files /dev/null and b/Ai_tottle/temp.glb differ
diff --git a/Ai_tottle/tiles copy.py b/Ai_tottle/tiles copy.py
new file mode 100644
index 0000000..7aedeab
--- /dev/null
+++ b/Ai_tottle/tiles copy.py	
@@ -0,0 +1,234 @@
+import os
+import logging
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+from matplotlib.colors import LinearSegmentedColormap
+from shapely.geometry import Polygon, Point
+from tqdm import tqdm
+from py3dtiles.tileset import TileSet
+import requests
+
+# 日志配置
+logger = logging.getLogger("TilesetProcessor")
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+
+
+class TilesetProcessor:
+    """3D Tiles数据集处理器，用于加载、分析和比较两个3D Tiles模型"""
+
+    def __init__(self, tileset_path1, tileset_path2, resolution=1.0, polygon_points=None):
+        self.tileset1 = self._load_tileset(tileset_path1)
+        self.tileset2 = self._load_tileset(tileset_path2)
+        self.resolution = resolution
+        self.analysis_area = None
+        self.height_difference_grid = None
+        self.grid_bounds = None
+
+        if polygon_points:
+            self.set_analysis_area(polygon_points=polygon_points)
+
+    def _load_tileset(self, path_or_url):
+        try:
+            logger.info(f"加载3D Tiles数据集: {path_or_url}")
+            if path_or_url.startswith("http://") or path_or_url.startswith("https://"):
+                resp = requests.get(path_or_url)
+                resp.raise_for_status()
+                tileset_json = resp.json()
+                tileset = TileSet.from_dict(tileset_json)
+            else:
+                tileset = TileSet.from_file(path_or_url)
+            logger.info(f"成功加载，包含 {len(tileset.root.children)} 个根瓦片")
+            return tileset
+        except Exception as e:
+            logger.error(f"加载数据集失败（路径: {path_or_url}）: {e}")
+            raise
+
+    def set_analysis_area(self, bounds=None, polygon_points=None):
+        if polygon_points:
+            self.analysis_area = Polygon(polygon_points)
+            min_x = min(p[0] for p in polygon_points)
+            min_y = min(p[1] for p in polygon_points)
+            max_x = max(p[0] for p in polygon_points)
+            max_y = max(p[1] for p in polygon_points)
+            self.grid_bounds = (min_x, min_y, max_x, max_y)
+            logger.info(f"设置多边形分析区域: {polygon_points}")
+        elif bounds:
+            min_x, min_y, max_x, max_y = bounds
+            self.analysis_area = Polygon([
+                (min_x, min_y),
+                (max_x, min_y),
+                (max_x, max_y),
+                (min_x, max_y)
+            ])
+            self.grid_bounds = bounds
+            logger.info(f"设置矩形分析区域: {bounds}")
+        else:
+            logger.error("请提供 bounds 或 polygon_points")
+            return False
+
+        logger.info(f"分析区域面积: {self.analysis_area.area:.2f} 平方米")
+        return True
+
+    def sample_heights(self):
+        if self.analysis_area is None:
+            logger.error("请先设置分析区域")
+            return False
+
+        logger.info("开始在分析区域内采样高度值...")
+
+        min_x, min_y, max_x, max_y = self.grid_bounds
+        rows = int((max_y - min_y) / self.resolution) + 1
+        cols = int((max_x - min_x) / self.resolution) + 1
+
+        self.height_difference_grid = np.full((rows, cols), np.nan, dtype=np.float32)
+
+        total_points = rows * cols
+        logger.info(f"创建了 {rows}x{cols}={total_points} 个采样点")
+
+        with tqdm(total=total_points, desc="采样高度点") as pbar:
+            for i in range(rows):
+                for j in range(cols):
+                    x = min_x + j * self.resolution
+                    y = min_y + i * self.resolution
+                    point = Point(x, y)
+
+                    if not self.analysis_area.contains(point):
+                        pbar.update(1)
+                        continue
+
+                    height1 = self._sample_height_at_point(self.tileset1, x, y)
+                    height2 = self._sample_height_at_point(self.tileset2, x, y)
+
+                    if height1 is not None and height2 is not None:
+                        self.height_difference_grid[i, j] = height2 - height1
+
+                    pbar.update(1)
+
+        valid_differences = self.height_difference_grid[~np.isnan(self.height_difference_grid)]
+        if len(valid_differences) > 0:
+            logger.info("高度变化统计:")
+            logger.info(f"  平均变化: {np.mean(valid_differences):.2f}m")
+            logger.info(f"  最大上升: {np.max(valid_differences):.2f}m")
+            logger.info(f"  最大下降: {np.min(valid_differences):.2f}m")
+            logger.info(f"  变化标准差: {np.std(valid_differences):.2f}m")
+        else:
+            logger.warning("未找到有效的高度差异数据")
+
+        return True
+
+    def _sample_height_at_point(self, tileset, x, y, max_depth=3):
+        def find_tile(tile, depth=0):
+            bbox = tile.bounding_volume.box
+            min_x_tile = bbox[0] - bbox[3]
+            max_x_tile = bbox[0] + bbox[3]
+            min_y_tile = bbox[1] - bbox[4]
+            max_y_tile = bbox[1] + bbox[4]
+
+            if not (min_x_tile <= x <= max_x_tile and min_y_tile <= y <= max_y_tile):
+                return None
+
+            if (tile.content is not None and depth >= max_depth) or not tile.children:
+                return tile
+
+            for child in tile.children:
+                result = find_tile(child, depth + 1)
+                if result is not None:
+                    return result
+
+            return None
+
+        tile = find_tile(tileset.root)
+        if tile is None or tile.content is None:
+            return None
+
+        try:
+            # 简化模拟返回瓦片中心高度加随机偏移
+            return tile.bounding_volume.box[2] + np.random.uniform(-0.5, 0.5)
+        except Exception as e:
+            logger.warning(f"获取瓦片高度失败: {e}")
+            return None
+
+    def export_results(self, output_dir="results"):
+        if self.height_difference_grid is None:
+            logger.error("请先采样高度值")
+            return
+
+        os.makedirs(output_dir, exist_ok=True)
+
+        csv_path = os.path.join(output_dir, "height_differences.csv")
+        logger.info(f"导出CSV文件: {csv_path}")
+
+        min_x, min_y, max_x, max_y = self.grid_bounds
+        rows, cols = self.height_difference_grid.shape
+
+        data = []
+        for i in range(rows):
+            for j in range(cols):
+                if not np.isnan(self.height_difference_grid[i, j]):
+                    x = min_x + j * self.resolution
+                    y = min_y + i * self.resolution
+                    data.append({
+                        'x': x,
+                        'y': y,
+                        'height_difference': self.height_difference_grid[i, j]
+                    })
+
+        df = pd.DataFrame(data)
+        df.to_csv(csv_path, index=False)
+
+        self._generate_heatmap(output_dir)
+
+        logger.info(f"结果已导出到 {output_dir} 目录")
+
+    def _generate_heatmap(self, output_dir):
+        colors = [(0.0, 0.0, 1.0), (1.0, 1.0, 1.0), (1.0, 0.0, 0.0)]
+        cmap = LinearSegmentedColormap.from_list('height_diff_cmap', colors, N=256)
+
+        data = self.height_difference_grid.copy()
+        valid_mask = ~np.isnan(data)
+
+        if not np.any(valid_mask):
+            logger.warning("没有有效的高度差异数据，无法生成热图")
+            return
+
+        data[~valid_mask] = 0
+
+        plt.figure(figsize=(12, 10))
+        plt.imshow(data, cmap=cmap, origin='lower',
+                   extent=[self.grid_bounds[0], self.grid_bounds[2],
+                           self.grid_bounds[1], self.grid_bounds[3]],
+                   alpha=0.9)
+
+        cbar = plt.colorbar()
+        cbar.set_label('高度变化 (米)', fontsize=12)
+
+        plt.title('两个3D Tiles模型的高度变化分布', fontsize=16)
+        plt.xlabel('X坐标 (米)', fontsize=12)
+        plt.ylabel('Y坐标 (米)', fontsize=12)
+
+        heatmap_path = os.path.join(output_dir, "height_difference_heatmap.png")
+        plt.savefig(heatmap_path, dpi=300, bbox_inches='tight')
+        plt.close()
+
+        logger.info(f"热图已保存到: {heatmap_path}")
+
+
+if __name__ == "__main__":
+    tileset1_url = "http://8.137.54.85:9000/300bdf2b-a150-406e-be63-d28bd29b409f/dszh/1748398014403562192_OUT/B3DM/tileset.json"
+    tileset2_url = "http://8.137.54.85:9000/300bdf2b-a150-406e-be63-d28bd29b409f/dszh/1748325943733189898_OUT/B3DM/tileset.json"
+    polygon_coords = [
+        (102.2232, 29.3841),
+        (102.2261, 29.3845),
+        (102.2263, 29.3821),
+        (102.2231, 29.3818)
+    ]
+    resolution = 0.5
+    output_dir = "output_results"
+
+    processor = TilesetProcessor(tileset1_url, tileset2_url, resolution, polygon_coords)
+    if processor.sample_heights():
+        processor.export_results(output_dir)
+        print("分析完成！结果已导出到指定目录。")
+    else:
+        print("高度采样失败，无法完成分析。")
diff --git a/Ai_tottle/tiles.py b/Ai_tottle/tiles.py
index 1584373..f6ceba0 100644
--- a/Ai_tottle/tiles.py
+++ b/Ai_tottle/tiles.py
@@ -1,265 +1,418 @@
 import os
+import requests
 import numpy as np
-import pandas as pd
-import py3dtiles
-from py3dtiles import Tileset, BoundingVolumeBox
+from py3dtiles.tileset.content import B3dm
+from pyproj import Proj, Transformer
 from shapely.geometry import Polygon, Point
-import matplotlib.pyplot as plt
-from matplotlib.colors import LinearSegmentedColormap
-import argparse
-from tqdm import tqdm
-import logging
+from shapely.ops import unary_union
+import math
+from urllib.parse import urljoin
+from pygltflib import GLTF2
 
-# 配置日志
-logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
-logger = logging.getLogger(__name__)
+# 目标区域经纬度坐标（转换为多边形）
+region_coords = [
+    [102.22321717600258, 29.384100779345513],
+    [102.22612442019208, 29.384506810595088],
+    [102.22638603372953, 29.382061071072794],
+    [102.22311237980807, 29.38186133280733],
+    [102.22321717600258, 29.384100779345513]  # 闭合多边形
+]
 
-class TilesetProcessor:
-    """3D Tiles数据集处理器，用于加载、分析和比较两个3D Tiles模型"""
+# 创建多边形对象
+region_polygon = Polygon(region_coords)
+
+# 两个3D Tiles模型的URL
+tileset_urls = [
+    "http://8.137.54.85:9000/300bdf2b-a150-406e-be63-d28bd29b409f/dszh/1748398014403562192_OUT/B3DM/tileset.json",
+    "http://8.137.54.85:9000/300bdf2b-a150-406e-be63-d28bd29b409f/dszh/1748325943733189898_OUT/B3DM/tileset.json"
+]
+
+# 坐标系转换
+wgs84 = Proj(init='epsg:4326')  # WGS84经纬度
+web_mercator = Proj(init='epsg:3857')  # Web墨卡托投影
+
+def adjust_z_in_transform(tileset_path, output_path=None, delta_z=0):
+    import json
+    import numpy as np
+
+    if not os.path.exists(tileset_path):
+        print(f"❌ tileset.json 文件不存在: {tileset_path}")
+        return
+
+    with open(tileset_path, 'r', encoding='utf-8') as f:
+        data = json.load(f)
+
+    root = data.get('root', {})
+
+    # 插入默认 transform
+    if 'transform' not in root:
+        print("⚠️ 未找到 transform 字段，使用单位矩阵")
+        root['transform'] = [
+            1, 0, 0, 0,
+            0, 1, 0, 0,
+            0, 0, 1, 0,
+            0, 0, 0, 1
+        ]
+
+    transform = np.array(root['transform']).reshape(4, 4)
+    print(f"原始 Z 平移: {transform[3, 2]}")
+    transform[3, 2] += delta_z
+    print(f"修正后 Z 平移: {transform[3, 2]}")
+
+    root['transform'] = transform.flatten().tolist()
+    data['root'] = root
+
+    if output_path is None:
+        output_path = tileset_path.replace(".json", f"_adjusted_z{int(delta_z)}.json")
+
+    with open(output_path, 'w', encoding='utf-8') as f:
+        json.dump(data, f, indent=2)
+
+    print(f"✅ 高度调整完成，输出文件: {output_path}")
+
+def download_tileset(tileset_url):
+    """下载tileset.json数据"""
+    try:
+        response = requests.get(tileset_url)
+        response.raise_for_status()
+        return response.json()
+    except Exception as e:
+        print(f"下载tileset失败: {e}")
+        return None
+
+def extract_vertices(gltf_bytes):
+    try:
+        with open("temp.glb", "wb") as f:
+            f.write(gltf_bytes)
+
+        gltf = GLTF2().load("temp.glb")
+
+        for mesh in gltf.meshes:
+            for primitive in mesh.primitives:
+                if not hasattr(primitive.attributes, "POSITION"):
+                    continue
+
+                accessor_idx = primitive.attributes.POSITION
+                accessor = gltf.accessors[accessor_idx]
+                buffer_view = gltf.bufferViews[accessor.bufferView]
+                buffer = gltf.buffers[buffer_view.buffer]
+
+                byte_offset = (buffer_view.byteOffset or 0) + (accessor.byteOffset or 0)
+                byte_length = accessor.count * 3 * 4  # 3 floats per vertex
+
+                data_bytes = gltf.binary_blob()[byte_offset: byte_offset + byte_length]
+                vertices = np.frombuffer(data_bytes, dtype=np.float32).reshape((accessor.count, 3))
+
+                return vertices
+
+    except Exception as e:
+        print(f"提取顶点数据失败: {e}")
+
+    return np.array([])
+
+def find_closest_vertex(vertices, lon, lat):
+    """找到离目标点最近的顶点"""
+    if not vertices:
+        return None
     
-    def __init__(self, tileset_path1, tileset_path2, resolution=1.0):
-        """
-        初始化处理器
-        
-        参数:
-            tileset_path1: 第一个3D Tiles数据集路径
-            tileset_path2: 第二个3D Tiles数据集路径
-            resolution: 分析网格的分辨率（米）
-        """
-        self.tileset1 = self._load_tileset(tileset_path1)
-        self.tileset2 = self._load_tileset(tileset_path2)
-        self.resolution = resolution
-        self.analysis_area = None
-        self.height_difference_grid = None
-        self.grid_bounds = None
-        
-    def _load_tileset(self, path):
-        """加载3D Tiles数据集"""
-        try:
-            logger.info(f"加载3D Tiles数据集: {path}")
-            tileset = Tileset.from_file(path)
-            logger.info(f"成功加载，包含 {len(tileset.root.children)} 个根瓦片")
-            return tileset
-        except Exception as e:
-            logger.error(f"加载数据集失败: {e}")
-            raise
+    # 计算距离并找到最近的顶点
+    min_distance = float('inf')
+    closest_vertex = None
     
-    def set_analysis_area(self, bounds):
-        """
-        设置分析区域
-        
-        参数:
-            bounds: 分析区域边界元组 (min_x, min_y, max_x, max_y)
-        """
-        min_x, min_y, max_x, max_y = bounds
-        self.analysis_area = Polygon([
-            (min_x, min_y),
-            (max_x, min_y),
-            (max_x, max_y),
-            (min_x, max_y)
-        ])
-        self.grid_bounds = bounds
-        logger.info(f"设置分析区域: {bounds}")
-        logger.info(f"分析区域面积: {self.analysis_area.area:.2f} 平方米")
-        return True
+    for vertex in vertices:
+        v_lon, v_lat, v_z = vertex
+        # 计算经纬度距离（简化为平面距离）
+        distance = math.hypot(v_lon - lon, v_lat - lat)
+        if distance < min_distance:
+            min_distance = distance
+            closest_vertex = vertex
     
-    def sample_heights(self):
-        """在分析区域内采样两个模型的高度值并计算差异"""
-        if self.analysis_area is None:
-            logger.error("请先设置分析区域")
-            return False
+    return closest_vertex
+
+def compare_heights(heights1, heights2, tolerance=0.5):
+    """比较两个高度数据集，找出差异"""
+    # 找到所有点的并集
+    all_points = set(heights1.keys()).union(set(heights2.keys()))
+    differences = []
+    
+    for point in all_points:
+        h1 = heights1.get(point, None)
+        h2 = heights2.get(point, None)
         
-        logger.info("开始在分析区域内采样高度值...")
-        
-        # 创建网格
-        min_x, min_y, max_x, max_y = self.grid_bounds
-        rows = int((max_y - min_y) / self.resolution) + 1
-        cols = int((max_x - min_x) / self.resolution) + 1
-        
-        # 初始化高度差异网格
-        self.height_difference_grid = np.zeros((rows, cols), dtype=np.float32)
-        self.height_difference_grid[:] = np.nan  # 初始化为NaN，表示未采样
-        
-        # 对每个网格点进行采样
-        total_points = rows * cols
-        logger.info(f"创建了 {rows}x{cols}={total_points} 个采样点")
-        
-        with tqdm(total=total_points, desc="采样高度点") as pbar:
-            for i in range(rows):
-                for j in range(cols):
-                    # 计算当前点的坐标
-                    x = min_x + j * self.resolution
-                    y = min_y + i * self.resolution
-                    point = Point(x, y)
-                    
-                    # 检查点是否在分析区域内
-                    if not self.analysis_area.contains(point):
-                        pbar.update(1)
-                        continue
-                    
-                    # 采样两个模型的高度
-                    height1 = self._sample_height_at_point(self.tileset1, x, y)
-                    height2 = self._sample_height_at_point(self.tileset2, x, y)
-                    
-                    # 计算高度差异
-                    if height1 is not None and height2 is not None:
-                        self.height_difference_grid[i, j] = height2 - height1
-                    
-                    pbar.update(1)
-        
-        # 统计结果
-        valid_differences = self.height_difference_grid[~np.isnan(self.height_difference_grid)]
-        if len(valid_differences) > 0:
-            logger.info(f"高度变化统计:")
-            logger.info(f"  平均变化: {np.mean(valid_differences):.2f}m")
-            logger.info(f"  最大上升: {np.max(valid_differences):.2f}m")
-            logger.info(f"  最大下降: {np.min(valid_differences):.2f}m")
-            logger.info(f"  变化标准差: {np.std(valid_differences):.2f}m")
+        # 检查是否有一个模型在该点没有数据
+        if h1 is None or h2 is None:
+            differences.append({
+                'point': point,
+                'height1': h1,
+                'height2': h2,
+                'difference': None,
+                'type': 'missing_data'
+            })
         else:
-            logger.warning("未找到有效的高度差异数据")
-            
-        return True
+            # 检查高度差异是否超过容忍度
+            diff = abs(h1 - h2)
+            if diff > tolerance:
+                differences.append({
+                    'point': point,
+                    'height1': h1,
+                    'height2': h2,
+                    'difference': diff,
+                    'type': 'height_difference'
+                })
     
-    def _sample_height_at_point(self, tileset, x, y, max_depth=3):
-        """在指定点采样3D Tiles模型的高度值"""
-        # 找到包含该点的瓦片
-        def find_tile(tile, depth=0):
-            # 检查点是否在瓦片边界框内
-            bbox = tile.bounding_volume.box
-            min_x_tile = bbox[0] - bbox[3]
-            max_x_tile = bbox[0] + bbox[3]
-            min_y_tile = bbox[1] - bbox[4]
-            max_y_tile = bbox[1] + bbox[4]
-            
-            if not (min_x_tile <= x <= max_x_tile and min_y_tile <= y <= max_y_tile):
-                return None
-                
-            # 如果瓦片有内容且深度足够，或者没有子瓦片，就使用这个瓦片
-            if (tile.content is not None and depth >= max_depth) or not tile.children:
-                return tile
-                
-            # 否则递归查找子瓦片
-            for child in tile.children:
-                result = find_tile(child, depth + 1)
-                if result is not None:
-                    return result
-                    
+    return differences
+
+def get_b3dm_from_tile_json(json_url):
+    try:
+        response = requests.get(json_url)
+        response.raise_for_status()
+        data = response.json()
+
+        # 递归查找 b3dm uri
+        def find_b3dm_uri(node):
+            if 'content' in node and 'uri' in node['content']:
+                uri = node['content']['uri']
+                if uri.endswith('.b3dm'):
+                    return uri
+            if 'children' in node:
+                for child in node['children']:
+                    result = find_b3dm_uri(child)
+                    if result:
+                        return result
             return None
-            
-        # 找到包含该点的最详细瓦片
-        tile = find_tile(tileset.root)
-        if tile is None or tile.content is None:
+
+        root = data.get('root', {})
+        b3dm_uri = find_b3dm_uri(root)
+        if not b3dm_uri:
+            print(f"{json_url} 中找不到 content.uri")
             return None
-            
-        # 从瓦片内容中获取高度
+
+        base_url = os.path.dirname(json_url)
+        full_b3dm_url = urljoin(base_url + '/', b3dm_uri)
+        return full_b3dm_url
+
+    except Exception as e:
+        print(f"解析 JSON {json_url} 时出错: {e}")
+        return None
+
+    
+def get_heights_in_region(tileset_url, sample_density=10):
+    """获取区域内的高度数据"""
+    tileset_json = download_tileset(tileset_url)
+    if not tileset_json:
+        return {}
+
+    tiles_in_region = get_tiles_in_region(tileset_json, tileset_url)
+    if not tiles_in_region:
+        print(f"在{tileset_url}中未找到区域内的瓦片")
+        return {}
+
+    min_lon, min_lat = min(p[0] for p in region_coords), min(p[1] for p in region_coords)
+    max_lon, max_lat = max(p[0] for p in region_coords), max(p[1] for p in region_coords)
+    lon_steps = np.linspace(min_lon, max_lon, sample_density)
+    lat_steps = np.linspace(min_lat, max_lat, sample_density)
+
+    heights = {}
+
+    for tile_info in tiles_in_region:
         try:
-            # 这里是简化的模拟实现，实际应该解析瓦片内容
-            # 例如，使用py3dtiles中的TileContent.get_vertices()获取顶点
-            # 然后找到最近的顶点或三角形来计算高度
-            # 这里为了示例，我们返回瓦片中心的高度加上一个随机偏移
-            return tile.bounding_volume.box[2] + np.random.uniform(-0.5, 0.5)
+            response = requests.get(tile_info['url'])
+            response.raise_for_status()
+            b3dm_data = response.content
+
+            # ✅ 尝试解析为 b3dm
+            try:
+                gltf_bytes = parse_b3dm(b3dm_data)
+            except Exception:
+                # 可能 tile_info['url'] 是 JSON，不是真 b3dm
+                print(f"尝试从 {tile_info['url']} 获取真实 b3dm 地址...")
+                actual_b3dm_url = get_b3dm_from_tile_json(tile_info['url'])
+                if not actual_b3dm_url:
+                    print(f"跳过：无法从 {tile_info['url']} 获取有效 b3dm")
+                    continue
+                response = requests.get(actual_b3dm_url)
+                response.raise_for_status()
+                b3dm_data = response.content
+                gltf_bytes = parse_b3dm(b3dm_data)
+
+            # ✅ 模拟解析 glb
+            vertices = extract_vertices(gltf_bytes)
+            if not vertices.size:
+                continue
+
+            # ✅ 应用变换
+            transformed_vertices = [transform_point(v, tile_info['transform']) for v in vertices]
+            transformer = Transformer.from_crs("EPSG:3857", "EPSG:4326", always_xy=True)
+            wgs84_vertices = []
+            for x, y, z in transformed_vertices:
+                lon, lat = transformer.transform(x, y)
+                wgs84_vertices.append((lon, lat, z))
+
+            for lon in lon_steps:
+                for lat in lat_steps:
+                    if point_in_region(lon, lat):
+                        closest_vertex = find_closest_vertex(wgs84_vertices, lon, lat)
+                        if closest_vertex:
+                            key = (round(lon, 6), round(lat, 6))
+                            heights[key] = closest_vertex[2]
+
         except Exception as e:
-            logger.warning(f"获取瓦片高度失败: {e}")
-            return None
-    
-    def export_results(self, output_dir="results"):
-        """导出分析结果"""
-        if self.height_difference_grid is None:
-            logger.error("请先采样高度值")
-            return
-            
-        os.makedirs(output_dir, exist_ok=True)
-        
-        # 导出CSV文件
-        csv_path = os.path.join(output_dir, "height_differences.csv")
-        logger.info(f"导出CSV文件: {csv_path}")
-        
-        # 创建DataFrame
-        min_x, min_y, max_x, max_y = self.grid_bounds
-        rows, cols = self.height_difference_grid.shape
-        
-        data = []
-        for i in range(rows):
-            for j in range(cols):
-                if not np.isnan(self.height_difference_grid[i, j]):
-                    x = min_x + j * self.resolution
-                    y = min_y + i * self.resolution
-                    data.append({
-                        'x': x,
-                        'y': y,
-                        'height_difference': self.height_difference_grid[i, j]
-                    })
-                    
-        df = pd.DataFrame(data)
-        df.to_csv(csv_path, index=False)
-        
-        # 生成热图
-        self._generate_heatmap(output_dir)
-        
-        logger.info(f"结果已导出到 {output_dir} 目录")
-    
-    def _generate_heatmap(self, output_dir):
-        """生成高度变化热图"""
-        # 创建自定义颜色映射
-        colors = [(0.0, 0.0, 1.0), (1.0, 1.0, 1.0), (1.0, 0.0, 0.0)]  # 蓝-白-红
-        cmap = LinearSegmentedColormap.from_list('height_diff_cmap', colors, N=256)
-        
-        # 准备数据
-        data = self.height_difference_grid.copy()
-        valid_mask = ~np.isnan(data)
-        
-        if not np.any(valid_mask):
-            logger.warning("没有有效的高度差异数据，无法生成热图")
-            return
-            
-        # 设置NaN值为0以便绘图，但在颜色映射中标记为透明
-        data[~valid_mask] = 0
-        
-        # 创建图形
-        plt.figure(figsize=(12, 10))
-        plt.imshow(data, cmap=cmap, origin='lower', 
-                   extent=[self.grid_bounds[0], self.grid_bounds[2], 
-                           self.grid_bounds[1], self.grid_bounds[3]],
-                   alpha=0.9)
-        
-        # 添加颜色条
-        cbar = plt.colorbar()
-        cbar.set_label('高度变化 (米)', fontsize=12)
-        
-        # 设置标题和坐标轴
-        plt.title('两个3D Tiles模型的高度变化分布', fontsize=16)
-        plt.xlabel('X坐标 (米)', fontsize=12)
-        plt.ylabel('Y坐标 (米)', fontsize=12)
-        
-        # 保存图形
-        heatmap_path = os.path.join(output_dir, "height_difference_heatmap.png")
-        plt.savefig(heatmap_path, dpi=300, bbox_inches='tight')
-        plt.close()
-        
-        logger.info(f"热图已保存到: {heatmap_path}")
+            print(f"处理瓦片 {tile_info['url']} 时出错: {e}")
+            continue
+
+    return heights
+
+def get_tiles_in_region(tileset_json, tileset_base_url):
+    """获取区域内的所有瓦片"""
+    tiles_in_region = []
+
+    # 去除 tileset.json 得到根路径
+    tileset_root_url = tileset_base_url.rsplit('/', 1)[0]
+
+    def recursive_search(tile, parent_transform=None):
+        tile_transform = tile.get('transform', [1,0,0,0, 0,1,0,0, 0,0,1,0, 0,0,0,1])
+        combined_transform = multiply_matrices(parent_transform, tile_transform) if parent_transform else tile_transform
+
+        if 'boundingVolume' in tile and is_bounding_volume_intersects_region(tile['boundingVolume']):
+            if 'content' in tile and 'uri' in tile['content']:
+                # 修复URL拼接
+                tile_url = urljoin(tileset_root_url + '/', tile['content']['uri'])
+                tiles_in_region.append({
+                    'url': tile_url,
+                    'transform': combined_transform
+                })
+
+            if 'children' in tile:
+                for child in tile['children']:
+                    recursive_search(child, combined_transform)
+
+    if 'root' in tileset_json:
+        recursive_search(tileset_json['root'])
+
+    return tiles_in_region
+
+def is_bounding_volume_intersects_region(bounding_volume):
+    """检查边界体是否与区域相交"""
+    # 简化实现，实际需要根据不同边界体类型实现
+    if 'region' in bounding_volume:
+        # region格式: [west, south, east, north, minHeight, maxHeight]
+        region = bounding_volume['region']
+        bv_polygon = Polygon([
+            [region[0], region[1]],
+            [region[2], region[1]],
+            [region[2], region[3]],
+            [region[0], region[3]],
+            [region[0], region[1]]
+        ])
+        return region_polygon.intersects(bv_polygon)
+    elif 'box' in bounding_volume:
+        # 对于box类型，需要转换到经纬度后再判断
+        # 这里简化处理，返回True让更细致的检查在后续进行
+        return True
+    elif 'sphere' in bounding_volume:
+        # 对于sphere类型，简化处理
+        return True
+    return False
+
+def multiply_matrices(a, b):
+    """计算两个4x4矩阵的乘积"""
+    result = [0.0] * 16
+    for i in range(4):
+        for j in range(4):
+            result[i*4 + j] = a[i*4 + 0] * b[0*4 + j] + \
+                             a[i*4 + 1] * b[1*4 + j] + \
+                             a[i*4 + 2] * b[2*4 + j] + \
+                             a[i*4 + 3] * b[3*4 + j]
+    return result
+
+def parse_b3dm(b3dm_data: bytes):
+    """
+    解析 b3dm 文件，返回 glb 二进制数据
+    """
+    import struct
+
+    if b3dm_data[:4] != b'b3dm':
+        raise ValueError("不是有效的 b3dm 文件")
+
+    # 读取 header（28 字节）
+    header = struct.unpack('<4sIIIIII', b3dm_data[:28])
+    _, version, byte_length, ft_json_len, ft_bin_len, bt_json_len, bt_bin_len = header
+
+    glb_start = 28 + ft_json_len + ft_bin_len + bt_json_len + bt_bin_len
+    glb_bytes = b3dm_data[glb_start:]
+
+    return glb_bytes
+
+def point_in_region(lon, lat):
+    """判断点是否在目标区域内"""
+    return region_polygon.contains(Point(lon, lat))
+
+def transform_point(point, matrix):
+    """应用变换矩阵到点"""
+    x, y, z = point
+    x_out = x * matrix[0] + y * matrix[4] + z * matrix[8] + matrix[12]
+    y_out = x * matrix[1] + y * matrix[5] + z * matrix[9] + matrix[13]
+    z_out = x * matrix[2] + y * matrix[6] + z * matrix[10] + matrix[14]
+    return (x_out, y_out, z_out)
 
 def main():
-    parser = argparse.ArgumentParser(description='分析两个3D Tiles模型指定区域的高度变化')
-    parser.add_argument('--tileset1', required=True, help='第一个3D Tiles数据集路径')
-    parser.add_argument('--tileset2', required=True, help='第二个3D Tiles数据集路径')
-    parser.add_argument('--bounds', required=True, type=float, nargs=4, 
-                        help='分析区域边界 [min_x, min_y, max_x, max_y]')
-    parser.add_argument('--resolution', type=float, default=1.0, help='采样分辨率（米）')
-    parser.add_argument('--output', default='results', help='输出目录')
-    
-    args = parser.parse_args()
-    
-    processor = TilesetProcessor(args.tileset1, args.tileset2, args.resolution)
-    
-    # 设置分析区域
-    if processor.set_analysis_area(args.bounds):
-        if processor.sample_heights():
-            processor.export_results(args.output)
-            print("分析完成！结果已导出到指定目录。")
-        else:
-            print("高度采样失败，无法完成分析。")
+    sample_density = 20
+
+    print("正在从第一个3D Tiles模型提取区域高度数据...")
+    heights1 = get_heights_in_region(tileset_urls[0], sample_density)
+
+    print("正在从第二个3D Tiles模型提取区域高度数据...")
+    heights2 = get_heights_in_region(tileset_urls[1], sample_density)
+
+    if not heights1 or not heights2:
+        print("无法获取足够的高度数据进行比较")
+        return
+
+    # 计算平均高度
+    avg1 = np.mean(list(heights1.values()))
+    avg2 = np.mean(list(heights2.values()))
+
+    print(f"\n模型1 平均高度: {avg1:.2f} 米")
+    print(f"模型2 平均高度: {avg2:.2f} 米")
+
+    delta = avg1 - avg2
+    print(f"高度差: {delta:.2f} 米")
+
+    # 🔧 自动统一高度
+    if abs(delta) > 0.5:
+        print("\n⚙️ 正在统一高度基准（修改模型2的 transform）...")
+        # tileset_urls[1] 是远程 URL，下载后调整
+        try:
+            ts2_url = tileset_urls[1]
+            response = requests.get(ts2_url)
+            response.raise_for_status()
+            with open("tileset_model2.json", "w", encoding="utf-8") as f:
+                f.write(response.text)
+
+            adjust_z_in_transform("tileset_model2.json", "tileset_model2_adjusted.json", delta_z=delta)
+        except Exception as e:
+            print(f"❌ 调整高度失败: {e}")
     else:
-        print("设置分析区域失败，无法进行分析。")
+        print("\n✅ 高度差异在容忍范围内，无需调整")
+
+    # 🔍 差异分析
+    print("\n正在分析详细差异点...")
+    differences = compare_heights(heights1, heights2, 0.5)
+
+    if differences:
+        print(f"共发现 {len(differences)} 处显著高度差异:")
+        for i, diff in enumerate(differences[:10], 1):  # 仅显示前10条
+            lon, lat = diff['point']
+            print(f"\n位置 {i}: 经度 {lon}, 纬度 {lat}")
+            print(f"模型1高度: {diff['height1']:.2f}米")
+            print(f"模型2高度: {diff['height2']:.2f}米")
+            if diff['difference'] is not None:
+                print(f"差异: {diff['difference']:.2f}米")
+            else:
+                print("差异: 一个模型在该位置没有数据")
+    else:
+        print("两个模型在指定区域高度基本一致 ✅")
+
 
 if __name__ == "__main__":
-    main()    
\ No newline at end of file
+    main()
diff --git a/Ai_tottle/tileset_model2.json b/Ai_tottle/tileset_model2.json
new file mode 100644
index 0000000..efa8690
--- /dev/null
+++ b/Ai_tottle/tileset_model2.json
@@ -0,0 +1 @@
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diff --git a/Ai_tottle/tileset_model2_adjusted.json b/Ai_tottle/tileset_model2_adjusted.json
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