GitHub / neka-nat / probreg
Python package for point cloud registration using probabilistic model (Coherent Point Drift, GMMReg, SVR, GMMTree, FilterReg, Bayesian CPD)
JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/neka-nat%2Fprobreg
PURL: pkg:github/neka-nat/probreg
Stars: 919
Forks: 150
Open issues: 17
License: mit
Language: Python
Size: 52.1 MB
Dependencies parsed at: Pending
Created at: over 6 years ago
Updated at: 3 days ago
Pushed at: about 1 year ago
Last synced at: 2 days ago
Commit Stats
Commits: 267
Authors: 8
Mean commits per author: 33.38
Development Distribution Score: 0.037
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/neka-nat/probreg
Topics: 3d, coherent-point-drift, dual-quaternion, dual-quaternion-skinning, expectation-maximization-algorithm, filterreg, gaussian-mixture-models, non-rigid-registration, open3d, point-cloud, point-cloud-registration, registration, rigid-transformations, variational-inference
Funding Links https://github.com/sponsors/neka-nat