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README..md

@@ -1,44 +0,0 @@
-## 做什么事情
-学习 brep 的sdf表示
-
-## 意义
-- brep方便控制
-- sdf方便运算和智能生成
-
-## 怎么做
-### 数据准备
-数据源： furniture
-文件结构
-    brep( .step )
-        train
-            chair
-                chair_1.brep
-                chair_2.brep
-        test
-        val
-    sdf ( .npz )
-        train
-            chair
-                chair_1.sdf.npz
-                chair_2.sdf.npz
-
-数据结构
-
-
-### brep to mesh
-基本思路：采样，然后三角化
-
-- 重采样
-    《Mesh Generation from CAD Models》: sharp edge 
-
-
-### mesh to sdf
-基本思路：体素，然后积分
-
-
-
-
-docker
-```
-docker run -it -v /mnt/disk2/dataset:/data -v $(pwd):/app --name brep_sdf ubuntu:22.04 
-```

brep2sdf/data/data.py

@@ -4,10 +4,14 @@ from torch.utils.data import Dataset
 import numpy as np
 import pickle
 from brep2sdf.utils.logger import setup_logger
-
+from .utils import process_brep_data
 # 设置日志记录器
 logger = setup_logger('dataset')
 
+
+
+
+
 class BRepSDFDataset(Dataset):
     def __init__(self, brep_dir:str, sdf_dir:str, split:str='train'):
         """
@@ -82,19 +86,20 @@ class BRepSDFDataset(Dataset):
                         logger.error(f"  {key}: type={type(value)}, dtype={value.dtype}, shape={value.shape}")
             raise
 
+
     def _load_brep_file(self, brep_path):
         """加载B-rep特征文件"""
         try:
             with open(brep_path, 'rb') as f:
                 brep_data = pickle.load(f)
             
-            features = {}
+            brep_data = {}
             
             # 1. 处理几何数据（不等长序列）
             for key in ['surf_wcs', 'surf_ncs', 'edge_wcs', 'edge_ncs']:
                 if key in brep_data:
                     try:
-                        features[key] = [
+                        brep_data[key] = [
                             torch.from_numpy(np.array(x, dtype=np.float32)) 
                             for x in brep_data[key]
                         ]
@@ -114,7 +119,7 @@ class BRepSDFDataset(Dataset):
                 if key in brep_data:
                     try:
                         data = np.array(brep_data[key], dtype=np.float32)
-                        features[key] = torch.from_numpy(data)
+                        brep_data[key] = torch.from_numpy(data)
                     except Exception as e:
                         logger.error(f"Error converting {key}:")
                         logger.error(f"  Type: {type(brep_data[key])}")
@@ -128,7 +133,7 @@ class BRepSDFDataset(Dataset):
                 if key in brep_data:
                     try:
                         data = np.array(brep_data[key], dtype=np.int32)
-                        features[key] = torch.from_numpy(data)
+                        brep_data[key] = torch.from_numpy(data)
                     except Exception as e:
                         logger.error(f"Error converting {key}:")
                         logger.error(f"  Type: {type(brep_data[key])}")
@@ -136,8 +141,9 @@ class BRepSDFDataset(Dataset):
                             logger.error(f"  Shape: {brep_data[key].shape}")
                             logger.error(f"  dtype: {brep_data[key].dtype}")
                         raise ValueError(f"Failed to convert {key}: {str(e)}")
-            
-            return features
+            feature_embedder = process_brep_data(brep_data, 70,70,1,)
+
+            return feature_embedder
             
         except Exception as e:
             logger.error(f"\nError loading B-rep file: {brep_path}")

brep2sdf/data/test.py

@@ -0,0 +1,121 @@
+import os
+import pickle
+import numpy as np
+import logging
+from datetime import datetime
+
+# 创建logs目录
+log_dir = 'logs'
+os.makedirs(log_dir, exist_ok=True)
+
+# 创建logger
+logger = logging.getLogger(__name__)
+logger.setLevel(logging.INFO)
+
+# 生成日志文件名（使用时间戳）
+timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
+log_file = os.path.join(log_dir, f'brep_log_{timestamp}.log')
+
+# 创建文件处理器
+file_handler = logging.FileHandler(log_file, encoding='utf-8')
+file_handler.setLevel(logging.INFO)
+
+# 创建控制台处理器
+console_handler = logging.StreamHandler()
+console_handler.setLevel(logging.INFO)
+
+# 创建格式器
+formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+file_handler.setFormatter(formatter)
+console_handler.setFormatter(formatter)
+
+# 添加处理器到logger
+logger.addHandler(file_handler)
+logger.addHandler(console_handler)
+
+# 防止日志重复
+logger.propagate = False
+
+def _load_brep_file(brep_path) -> dict:
+    """加载并打印B-rep数据结构"""
+    try:
+        # 加载B-rep特征
+        with open(brep_path, 'rb') as f:
+            brep_data = pickle.load(f)
+            
+        # 打印数据结构
+        logger.info(f"\nData structure from {os.path.basename(brep_path)}:")
+        logger.info(brep_data.keys())
+        
+        # 1. 几何数据
+        if 'surf_wcs' in brep_data:
+            logger.info(f"  surf_wcs: list of {len(brep_data['surf_wcs'])} arrays")
+            for i, surf in enumerate(brep_data['surf_wcs']):
+                logger.info(f"    surface {i}: shape={np.array(surf).shape}, type={type(surf)}")
+                
+        if 'surf_ncs' in brep_data:
+            logger.info(f"  surf_ncs: list of {len(brep_data['surf_ncs'])} arrays")
+            for i, surf in enumerate(brep_data['surf_ncs']):
+                logger.info(f"    surface {i}: shape={np.array(surf).shape}, type={type(surf)}")
+                
+        if 'edge_wcs' in brep_data:
+            logger.info(f"  edge_wcs: list of {len(brep_data['edge_wcs'])} arrays")
+            for i, edge in enumerate(brep_data['edge_wcs']):
+                logger.info(f"    edge {i}: shape={np.array(edge).shape}, type={type(edge)}")
+                
+        if 'edge_ncs' in brep_data:
+            logger.info(f"  edge_ncs: list of {len(brep_data['edge_ncs'])} arrays")
+            for i, edge in enumerate(brep_data['edge_ncs']):
+                logger.info(f"    edge {i}: shape={np.array(edge).shape}, type={type(edge)}")
+        
+        # 2. 顶点数据
+        if 'corner_wcs' in brep_data:
+            logger.info(f"  corner_wcs: shape={brep_data['corner_wcs'].shape}, type={type(brep_data['corner_wcs'])}")
+            
+        if 'corner_unique' in brep_data:
+            logger.info(f"  corner_unique: shape={brep_data['corner_unique'].shape}, type={type(brep_data['corner_unique'])}")
+        
+        # 3. 包围盒数据
+        if 'surf_bbox_wcs' in brep_data:
+            logger.info(f"  surf_bbox_wcs: shape={brep_data['surf_bbox_wcs'].shape}, type={type(brep_data['surf_bbox_wcs'])}")
+            
+        if 'edge_bbox_wcs' in brep_data:
+            logger.info(f"  edge_bbox_wcs: shape={brep_data['edge_bbox_wcs'].shape}, type={type(brep_data['edge_bbox_wcs'])}")
+        
+        # 4. 邻接关系数据
+        if 'edgeFace_adj' in brep_data:
+            logger.info(f"  edgeFace_adj: shape={brep_data['edgeFace_adj'].shape}, type={type(brep_data['edgeFace_adj'])}")
+            
+        if 'edgeCorner_adj' in brep_data:
+            logger.info(f"  edgeCorner_adj: shape={brep_data['edgeCorner_adj'].shape}, type={type(brep_data['edgeCorner_adj'])}")
+            
+        if 'faceEdge_adj' in brep_data:
+            logger.info(f"  faceEdge_adj: shape={brep_data['faceEdge_adj'].shape}, type={type(brep_data['faceEdge_adj'])}")
+            
+        return brep_data
+        
+    except Exception as e:
+        logger.error(f"Error loading brep from {brep_path}: {str(e)}")
+        raise
+
+
+def test_load_brep():
+    """测试加载B-rep文件的功能"""
+    try:
+        
+        # 测试文件路径（请替换为你实际的测试文件路径）
+        test_file = "/home/wch/brep2sdf/test_data/pkl/train/chair_1105.pkl"
+        
+        
+            
+        # 测试加载功能
+        loaded_data = _load_brep_file(test_file)
+        
+        logger.info("测试成功完成！")
+        
+    except Exception as e:
+        logger.error(f"测试失败: {str(e)}")
+        raise
+
+if __name__ == '__main__':
+    test_load_brep()