feat: initial commit - massive-cloud point cloud processing system

alg/point_porj/archive/relative_code/SOR.py

@@ -0,0 +1,60 @@
+import open3d as o3d
+import numpy as np
+from scipy.spatial import KDTree
+from plyfile import PlyData
+def chamfer_distance(pcd1, pcd2):
+    """
+    计算两个点云之间的 CD 距离（Chamfer Distance）
+
+    Args:
+        pcd1: Open3D 点云对象1
+        pcd2: Open3D 点云对象2
+
+    Returns:
+        cd: Chamfer Distance 值
+        cd1: 点云1 到 点云2 的平均距离
+        cd2: 点云2 到 点云1 的平均距离
+    """
+    # 获取点坐标
+    points1 = np.asarray(pcd1.points)
+    points2 = np.asarray(pcd2.points)
+
+    # 构建 KD-Tree 加速最近邻搜索
+    tree1 = KDTree(points1)
+    tree2 = KDTree(points2)
+
+    # 计算 points1 中每个点到 points2 的最近距离
+    dist1, _ = tree2.query(points1, k=1)
+    cd1 = np.mean(dist1 ** 2)  # 平方距离的平均值
+
+    # 计算 points2 中每个点到 points1 的最近距离
+    dist2, _ = tree1.query(points2, k=1)
+    cd2 = np.mean(dist2 ** 2)  # 平方距离的平均值
+
+    # 总 CD 距离（双向平均）
+    cd = cd1 + cd2
+
+    return cd, cd1, cd2
+
+pcd = o3d.io.read_point_cloud("E:\point_distance\data\part_car_head.ply")
+colors = np.tile([1, 0, 0], (len(pcd.points), 1))
+pcd.colors = o3d.utility.Vector3dVector(colors)
+# ply_data = PlyData.read(r"E:\point_distance\data\part_car_head.ply")
+# colors=np.asarray(ply_data.colors)
+# with open("E:\point_distance\data\part_car_head.ply", 'r',encoding="utf-8") as f:
+#     lines = f.readlines()
+#     for line in lines[:30]:  # 打印头部
+#         print(line.strip())
+# o3d.visualization.draw_geometries([pcd])
+# points = np.asarray(pcd.points)
+# colors = np.asarray(pcd.colors)
+# normals = np.asarray(pcd.normals)
+cl, ind = pcd.remove_statistical_outlier(nb_neighbors=20, std_ratio=50.0)
+inlier_cloud = pcd.select_by_index(ind)
+colors=np.tile([0,1,0],(len(inlier_cloud.points),1))
+inlier_cloud.colors=o3d.utility.Vector3dVector(colors)
+o3d.visualization.draw_geometries([inlier_cloud])
+o3d.visualization.draw_geometries([pcd])
+o3d.visualization.draw_geometries()
+cd,cd1,cd2=chamfer_distance(pcd1=pcd,pcd2=inlier_cloud)
+print(cd)