torch-ransac3d 1.0.35

A high-performance implementation of 3D RANSAC (Random Sample Consensus) algorithm using PyTorch and CUDA.

A high-performance implementation of 3D RANSAC algorithm using PyTorch and CUDA.
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Installation

Requirements: torch

Install with Pypi :

pip install torch-ransac3d

Example Usage

import torch
from torch_ransac3d.line import line_fit

points = torch.rand(1000,3)
direction, intercept, inliers = line_fit(points)

Currently other supported geometries include planes and spheres.

Credit:

This is based on the work done at https://github.com/leomariga/pyRANSAC-3D/

Contact

Maintainer: Harry Dobbs
Email: [e-mail]