How to compare video scene detectors
Aider implemented three scene-change analyzers for a local video app. The developer compared their images across multiple videos and tuned the code and thresholds.
news.ycombinator.comSuggested prompt
Suggested prompt written by Agents In Use, not the source author. Replace bracketed inputs and review tool permissions first.
Suggest scene-change detection methods for [local video application]. Explain their tradeoffs, then implement [selected methods] behind a shared interface so I can compare extracted frames across [sample videos].
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Sourced account- Source poster / publisher
- carpo
- Original account
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- Published
- Source link checked
- Reported result
- The author reports pretty good image-extraction results after an afternoon, including implementation, visual comparisons, code inspection and threshold tuning.
- Human involvement
- The author researched methods, wrote a comparison script, visually checked images and read and tweaked the generated code.
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How the agent did it
- Ask Aider for methods to detect sufficient scene changes in videos.
- Research the suggested methods and request three implementations.
- Run each analyzer across multiple videos using a test script.
The author was building a local video library application and wanted to extract images when a scene changed sufficiently. They asked Aider in an IDE terminal what approaches were available. Aider returned seven methods, which the author researched before choosing three for implementation.
Aider then created an interface, three implementations and a factory for obtaining the different analyzers. This gave the author several working approaches to compare rather than committing immediately to a single method. They say that part took about an hour.
The author wrote a test script that looped over multiple videos and ran each analyzer against them. They visually inspected the resulting images to decide which approach worked best. They also read the generated code to understand its behavior, made tweaks, adjusted thresholds and reran the comparisons. The reported outcome was pretty good results after an afternoon of work, with much of the time spent on visual comparison and tuning. The post does not name the algorithms or identify a winning analyzer. Who it's for: developers adding scene-based image extraction who can evaluate representative videos and inspect the resulting frames.
Prompt
Suggested prompt (written by Agents In Use, not the author's)
Source: Hacker News · carpo
Frequently asked questions
How were the scene-detection approaches selected?
Aider suggested seven methods. The author researched them and asked it to implement three.
How did the author check the generated analyzers?
They wrote a script to run every analyzer across multiple videos, visually compared the extracted images, inspected the code, adjusted thresholds and reran it.
More details
Remaining steps
- Inspect the images and code, adjust thresholds, and rerun comparisons.
About this account
Aider proposed alternatives and implemented the selected analyzers; the author controlled selection, testing and tuning.
Platform: Hacker News. Attribution: https://news.ycombinator.com/item?id=43578673. Prompt: Suggested (written by Agents In Use, not the author's). Sourced by the Agents In Use pipeline.
Credit: carpo on Hacker News
Source published
Added to Agents In Use
Source checked
Tools and topics
Aider · IDE terminal · Video test script
Video analysis · Scene detection · Visual testing
Editorial completeness: 100/100. Measures documented fields, not agent performance or verified outcomes.