# llSourcell/Learn_Computer_Vision

This is the curriculum for "Learn Computer Vision" by Siraj Raval on Youtube

Repository: https://github.com/llSourcell/Learn_Computer_Vision
Canonical: https://ross.abutalabs.com/products/learn_computer_vision
License Family: other
Last push: 2021-08-12T07:50:43+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": 2606, "days_push": 1847, "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 1122, forks 345 (observed 2026-08-28T04:03:40.010545+00:00)

## What it is
An 8-week self-study curriculum for learning computer vision, created by Siraj Raval to accompany his YouTube course. It lists weekly video lectures, reading assignments (mainly from Szeliski's textbook), and hands-on projects using Python, OpenCV, and TensorFlow.

## Use cases
- learn computer vision from scratch
- find a structured CV study plan
- practice OpenCV projects like object detection and tracking
- supplement a computer vision course with reading assignments
- prepare for a career in computer vision
- learn image processing, optical flow, and segmentation

## When to choose
- you want a free, structured self-study path into computer vision
- you prefer project-based learning with OpenCV and TensorFlow
- you want curated video lectures and textbook readings in one place

## When to avoid
- you need maintained, up-to-date course material or support
- you want runnable software or code rather than a curriculum outline
- you need a licensed or formally supported educational resource

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: computer-vision, image-processing, machine-learning
- domain: computer-vision, education, tutorials, machine-learning
- platform: python
- tags: curriculum, opencv, tensorflow, siraj-raval, youtube-course, self-study

## Member repositories
- llSourcell/Learn_Computer_Vision (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:40.010545+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 2026-08-30T06:40:56.212460+00:00, confidence not recorded.
  - readme: https://github.com/llSourcell/Learn_Computer_Vision (fetched 2026-08-28T04:03:40.010545+00:00, sha 81763283588f)
- Data as of 2026-08-30T08:39:29.467469+00:00.