# RimoChan/Vtuber_Tutorial

【教程】从零开始的自制Vtuber！

Repository: https://github.com/RimoChan/Vtuber_Tutorial
Canonical: https://ross.abutalabs.com/products/vtuber_tutorial
Language: Python
License: NOASSERTION
License Family: other
Last push: 2024-08-13T02:48:57+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2334, "days_push": 750, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1140, forks 82 (observed 2026-08-28T04:03:44.446135+00:00)

## What it is
A Chinese-language tutorial series teaching how to build your own Vtuber from scratch, covering facial capture with a webcam through to character rendering. It uses Python with OpenCV, Dlib, and NumPy, and is written iteratively so each chapter yields a working Vtuber.

## Use cases
- learn how to make a vtuber avatar from scratch
- understand how webcam face tracking works
- build head pose tracking with facial landmarks
- learn facial capture with dlib and opencv
- create an animated character driven by my face
- study computer vision through a fun project

## When to choose
- you want a step-by-step, code-driven introduction to vtuber creation
- you want to learn facial landmark detection and head angle estimation in Python
- you prefer iterative tutorials where each chapter produces a working result

## When to avoid
- you need a production-ready vtuber application rather than a learning exercise
- you cannot read Chinese, as the tutorial is written in Chinese
- you want polished best-practice code - the author warns some techniques are intentionally unconventional

## Facets
- artifact type: learning-resource
- maturity: active
- function: computer-vision, image-processing, graphics, machine-learning
- domain: tutorials, computer-vision, graphics, artificial-intelligence
- platform: python, cross-platform
- tags: vtuber, face-tracking, facial-capture, dlib, opencv, tutorial-series, avatar-rendering

## Member repositories
- RimoChan/Vtuber_Tutorial (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:44.446135+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:35:26.471441+00:00, confidence not recorded.
  - readme: https://github.com/RimoChan/Vtuber_Tutorial (fetched 2026-08-28T04:03:44.446135+00:00, sha 37f6e9613b61)
- Data as of 2026-08-30T08:39:29.467469+00:00.