fossasia/visdom

Large scale 3D point cloud visualization pane

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#686 opened on Oct 28, 2019

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 (5 comments) (0 reactions) (0 assignees)Python (9,831 stars) (1,152 forks)batch import
Needs Investigationenhancementhelp wanted

Description

Is your feature request related to a problem? Please describe. It will be convenient if Visdom support point cloud visualization in deep learning about 3D vision, like project using PointNet.

Describe the solution you'd like Considering large scale point cloud collected for autonomous driving or 3D reconstruction, a visualization using WebGL maybe a good choice, which supports mouse interaction.

Describe alternatives you've considered A clear and concise description of any alternative solutions or features you've considered.

Additional context Add any other context or screenshots about the feature request here.

Contributor guide

Tech stack
pythonjavascript
Domain
frontenddata
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
4
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
over 1 week
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
mostly clear
Prerequisites
Familiarity with WebGLUnderstanding of Visdom's architecturePython backend development3D point cloud data formats
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
20
Research direction
Visdom's frontend uses JavaScript for rendering; investigate how existing plots are drawn (likely using Plotly or similar) and consider integrating a WebGL based library like Three.js for point cloud visualization. Review the Python backend code for data streaming and serialization, particularly the communication protocol. Additionally, check for any prior work or discussions in related issues or PRs within the repository.