{"id":14033214,"url":"https://github.com/daavoo/pyntcloud","last_synced_at":"2025-05-13T19:13:25.086Z","repository":{"id":39351705,"uuid":"69888255","full_name":"daavoo/pyntcloud","owner":"daavoo","description":"pyntcloud is a Python library for working with 3D point clouds.","archived":false,"fork":false,"pushed_at":"2025-03-15T11:51:53.000Z","size":15852,"stargazers_count":1447,"open_issues_count":59,"forks_count":226,"subscribers_count":44,"default_branch":"main","last_synced_at":"2025-04-26T16:40:14.688Z","etag":null,"topics":["3d","3d-deep-learning","3d-graphics","3d-models","3d-point-clouds","deep-learning","point-clouds","python","python-library"],"latest_commit_sha":null,"homepage":"http://pyntcloud.readthedocs.io","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/daavoo.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"docs/contributing.rst","funding":null,"license":"LICENSE.md","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2016-10-03T16:16:44.000Z","updated_at":"2025-04-24T02:39:44.000Z","dependencies_parsed_at":"2023-02-18T18:45:24.345Z","dependency_job_id":"d340a8c9-5ed6-4e12-b68c-34490f12fd55","html_url":"https://github.com/daavoo/pyntcloud","commit_stats":{"total_commits":837,"total_committers":38,"mean_commits":"22.026315789473685","dds":0.08721624850657106,"last_synced_commit":"cab0c7f5a51f6e5136fed1d90dd805853c823386"},"previous_names":[],"tags_count":13,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/daavoo%2Fpyntcloud","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/daavoo%2Fpyntcloud/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/daavoo%2Fpyntcloud/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/daavoo%2Fpyntcloud/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/daavoo","download_url":"https://codeload.github.com/daavoo/pyntcloud/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251085143,"owners_count":21533821,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["3d","3d-deep-learning","3d-graphics","3d-models","3d-point-clouds","deep-learning","point-clouds","python","python-library"],"created_at":"2024-08-12T01:01:08.319Z","updated_at":"2025-04-27T05:55:51.892Z","avatar_url":"https://github.com/daavoo.png","language":"Python","readme":"# Making point clouds fun again\n\n![pyntcloud logo](https://raw.githubusercontent.com/daavoo/pyntcloud/master/docs/images/pyntcloud_logo.png)\n\n\n**pyntcloud** is a Python library for working with 3D point clouds leveraging the power of the Python scientific stack.\n\n- [Examples](https://github.com/daavoo/pyntcloud/tree/master/examples).\n- [Documentation](http://pyntcloud.readthedocs.io/en/latest/)\n\n## Installation\n\n```bash\npip install pyntcloud\n```\n\n## Quick Overview\n\nYou can access most of pyntcloud's functionality from its core class: PyntCloud.\n\nWith PyntCloud you can perform complex 3D processing operations with minimum lines of\ncode. For example you can:\n\n- Load a PLY point cloud from disk.\n- Add 3 new scalar fields by converting RGB to HSV.\n- Build a grid of voxels from the point cloud.\n- Build a new point cloud keeping only the nearest point to each occupied voxel center.\n- Save the new point cloud in numpy's NPZ format.\n\nWith the following concise code:\n\n```python\nfrom pyntcloud import PyntCloud\n\ncloud = PyntCloud.from_file(\"some_file.ply\")\n\ncloud.add_scalar_field(\"hsv\")\n\nvoxelgrid_id = cloud.add_structure(\"voxelgrid\", n_x=32, n_y=32, n_z=32)\n\nnew_cloud = cloud.get_sample(\"voxelgrid_nearest\", voxelgrid_id=voxelgrid_id, as_PyntCloud=True)\n\nnew_cloud.to_file(\"out_file.npz\")\n```\n\n## Integration with other libraries\n\npyntcloud offers seamless integration with other 3D processing libraries.\n\nYou can create / convert PyntCloud instances from / to many 3D processing libraries using the `from_instance` / `to_instance` methods:\n\n- [Open3D](https://www.open3d.org)\n\n```python\nimport open3d as o3d\nfrom pyntcloud import PyntCloud\n\n# FROM Open3D\noriginal_triangle_mesh = o3d.io.read_triangle_mesh(\"diamond.ply\")\ncloud = PyntCloud.from_instance(\"open3d\", original_triangle_mesh)\n\n# TO Open3D\ncloud = PyntCloud.from_file(\"diamond.ply\")\nconverted_triangle_mesh = cloud.to_instance(\"open3d\", mesh=True)  # mesh=True by default\n```\n\n- [PyVista](https://docs.pyvista.org)\n\n```python\nimport pyvista as pv\nfrom pyntcloud import PyntCloud\n\n# FROM PyVista\noriginal_point_cloud = pv.read(\"diamond.ply\")\ncloud = PyntCloud.from_instance(\"pyvista\", original_point_cloud)\n\n# TO PyVista\ncloud = PyntCloud.from_file(\"diamond.ply\")\nconverted_triangle_mesh = cloud.to_instance(\"pyvista\", mesh=True)\n```\n","funding_links":[],"categories":["pointcloud","Libraries"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdaavoo%2Fpyntcloud","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdaavoo%2Fpyntcloud","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdaavoo%2Fpyntcloud/lists"}