# harleyszhang/cv_note

记录cv算法工程师的成长之路，分享计算机视觉和模型压缩部署技术栈笔记。https://harleyszhang.github.io/cv_note/

Repository: https://github.com/harleyszhang/cv_note
Canonical: https://ross.abutalabs.com/products/cv_note
Language: Python
License: Apache-2.0
License Family: permissive
Topics: deep-learning, interview-questions, computer-vision, machine-learning-algorithms, cpp11, python3
Last push: 2026-05-10T10:31:11+00:00

## Health v2 (maintenance only)
Score: 69/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 81, release rhythm 35, longevity 100
- inputs: {"age_days": 2721, "days_push": 115, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2638, forks 390 (observed 2026-08-28T04:07:06.369772+00:00)

## What it is
A curated collection of study notes documenting the growth path of a computer vision algorithm engineer, covering deep learning fundamentals, model compression, and deployment techniques. It also promotes a paid course on building an LLM inference framework with Triton and PyTorch.

## Use cases
- prepare for computer vision algorithm engineer interviews
- learn model compression and quantization techniques
- study model deployment on embedded devices
- review deep learning fundamentals and interview questions
- follow a structured CV engineer learning roadmap

## When to choose
- you want free, organized notes on CV algorithms and model deployment
- you are preparing for algorithm engineer job interviews
- you prefer Chinese-language learning material for computer vision

## When to avoid
- you need production-ready CV software or libraries
- you want English-language documentation
- you need a maintained tool rather than study notes

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, deep-learning, developer-tools
- domain: computer-vision, deep-learning, tutorials, education
- platform: python, cpp, cross-platform
- tags: cv-notes, model-compression, model-deployment, interview-preparation, study-notes, llm-inference

## Member repositories
- harleyszhang/cv_note (main) score 69

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:06.369772+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 2026-08-30T02:19:11.764845+00:00, confidence not recorded.
  - readme: https://github.com/harleyszhang/cv_note (fetched 2026-08-28T04:07:06.369772+00:00, sha 68abaeca0d56)
- Data as of 2026-08-30T08:39:29.467469+00:00.