leandromoreira/digital_video_introduction

★ 16,211Jupyter NotebookAudience · developerComplexity · 2/5LicenseSetup · moderate

Mindmap

mindmap
  root((repo))
    What it teaches
      Video fundamentals
      Codec internals
      Streaming basics
    Key concepts
      Frame types
      Compression steps
      Color encoding
    Codecs covered
      H264 H265
      VP9 and AV1
    Hands-on
      Docker exercises
      ffmpeg tools
      Jupyter notebooks

mindmap root((repo)) What it teaches Video fundamentals Codec internals Streaming basics Key concepts Frame types Compression steps Color encoding Codecs covered H264 H265 VP9 and AV1 Hands-on Docker exercises ffmpeg tools Jupyter notebooks

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Things people build with this

USE CASE 1

Learn how codecs like H.264 and AV1 compress video by working through interactive frame-level exercises.

USE CASE 2

Understand how adaptive streaming works before building a video delivery or transcoding feature in a product.

USE CASE 3

Use the Docker-based exercises to explore video frames and images interactively with bundled ffmpeg tools.

Tech stack

PythonJupyter NotebookDockerffmpegmediainfo

Getting it running

Difficulty · moderate Time to first run · 30min

Requires Docker to run the interactive exercises with bundled ffmpeg and mediainfo tools.

Use freely for any purpose, including commercial use, as long as you keep the copyright notice, BSD 3-Clause.

In plain English

digital_video_introduction is a self-paced tutorial that teaches the fundamentals of digital video, how images and video work, how codecs compress them, and how streaming services deliver them over the internet. It is aimed at software developers and engineers new to the area, but the author tries to make it readable for anyone, using simple vocabulary, diagrams, and hands-on exercises. The material walks through the topic in the order you would need to understand it. It starts with basic terminology, what an image is (a 2D matrix of pixels), how colour is encoded with red/green/blue planes, what bit depth, resolution and aspect ratio mean, then moves into how video squeezes out redundant data: chroma subsampling, the different frame types (I, P and B), and the temporal and spatial prediction tricks codecs use. From there it builds up a generic video codec step by step (partitioning, prediction, transform, quantization, entropy coding such as VLC and arithmetic coding, and bitstream formatting), with examples from H.264, H.265, VP9 and AV1. The final sections cover online streaming, progressive download versus adaptive streaming, and content protection. You would use this repository if you are getting started in video engineering, working on a product that touches encoding or streaming, or curious about how video compression works. Many sections have hands-on exercises that run inside Docker containers, using bundled ffmpeg and mediainfo tools and a Jupyter server to explore images and frames interactively. The project is BSD-3-Clause licensed and ships translations in Chinese, Japanese, Italian, Korean, Russian, Brazilian Portuguese and Spanish.

Copy-paste prompts

Prompt 1

Walk me through the digital_video_introduction section on I-frames, P-frames, and B-frames and explain why they matter for file size.

Prompt 2

Set up the digital_video_introduction Docker environment and run the exercise that shows how chroma subsampling reduces video file size.

Prompt 3

I'm building a video streaming feature, which sections of digital_video_introduction cover adaptive streaming and progressive download?

Prompt 4

Explain how the entropy coding step in the generic codec walkthrough from digital_video_introduction reduces file size in practice.

Prompt 5

After reading digital_video_introduction, help me write an ffmpeg command that transcodes a video to H.264 with a target bitrate and explain each flag.

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