{"library":"point-cloud-utils","title":"Point Cloud Utils","description":"A Python library for common tasks on 3D point clouds and meshes, including sampling, distance computation (chamfer, Hausdorff, Earth Mover's), normal estimation, mesh reconstruction, and more. Current version: 0.34.0. Released under MIT license (since v0.30.0). Active development with frequent releases.","language":"python","status":"active","last_verified":"Fri May 01","install":{"commands":["pip install point-cloud-utils"],"cli":null},"imports":["import point_cloud_utils as pcu","from point_cloud_utils import chamfer_distance"],"auth":{"required":false,"env_vars":[]},"quickstart":{"code":"import point_cloud_utils as pcu\nimport numpy as np\n\n# Load a point cloud from a PLY file\nverts, faces = pcu.load_mesh_vf(\"bunny.ply\")\n\n# Compute chamfer distance between two point clouds\npcd1 = np.random.randn(100, 3).astype(np.float32)\npcd2 = np.random.randn(200, 3).astype(np.float32)\nchamfer_dist, _ = pcu.chamfer_distance(pcd1, pcd2)\nprint(\"Chamfer distance:\", chamfer_dist)\n\n# Downsample point cloud\nsampled_indices = pcu.downsample_point_cloud_uniform(pcd1, 50)\nsampled_pcd = pcd1[sampled_indices]","lang":"python","description":"Basic usage: load mesh, compute chamfer distance, and downsample.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":null}