mirror of
https://github.com/graphdeco-inria/gaussian-splatting
synced 2025-06-26 18:18:11 +00:00
58 lines
2.1 KiB
Python
58 lines
2.1 KiB
Python
import open3d as o3d
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import numpy as np
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import os
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def pcd_2_ply(pcd_file_path,ply_file_path):
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point_cloud = o3d.io.read_point_cloud(pcd_file_path)
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o3d.io.write_point_cloud(ply_file_path, point_cloud)
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print(f"Converted {pcd_file_path} to {ply_file_path}")
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def pcd_2_colmap_txt(pcd_file, txt_file, is_white=False):
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'''
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is_white: 是否将点云颜色设置为白色
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'''
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point_cloud = o3d.io.read_point_cloud(pcd_file)
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points = np.asarray(point_cloud.points)
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colors = np.asarray(point_cloud.colors)
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print(f"正在写入COLMAP TXT文件: {txt_file}")
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with open(txt_file, 'w') as f:
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f.write('# 3D point list with one line of data per point\n')
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f.write('# POINT_ID, X, Y, Z, R, G, B, ERROR\n')
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f.write('# Number of points: {}\n'.format(len(points)))
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for i, point in enumerate(points):
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x, y, z = point
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if is_white:
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r, g, b = 255, 255, 255
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else:
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r, g, b = colors[i]
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r,g,b = int(r * 255), int(g * 255), int(b * 255)
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error = 0
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# 空的观察列表 (IMAGE_ID, POINT2D_IDX)
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# 写入一行
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f.write(f"{i} {x:.6f} {y:.6f} {z:.6f} {r} {g} {b} {error}\n")
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print(f"Converted {pcd_file} to Colmap TXT in: {txt_file}")
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def voxel_downsample_and_save(voxel_size, input_ply_path, output_ply_path):
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"""
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从PLY文件读取点云，进行体素化降采样，并保存结果。
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Args:
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input_ply_path (str): 输入PLY文件路径。
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voxel_size (float): 体素大小。
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output_ply_path (str): 保存降采样后点云的PLY文件路径。
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"""
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# 读取输入点云
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pcd = o3d.io.read_point_cloud(input_ply_path)
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print(f"raw points len : {len(pcd.points)}")
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# 体素化降采样
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pcd_downsampled = pcd.voxel_down_sample(voxel_size)
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print(f"downsample points len : {len(pcd_downsampled.points)}")
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# 保存降采样后的点云
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o3d.io.write_point_cloud(output_ply_path, pcd_downsampled)
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print(f"降采样后的点云已保存到 {output_ply_path}，体素大小：{voxel_size}") |