tolik518 / tolik518/factorion-bot

Optical Character Recognition (OCR)

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#316 4 comments 0 reactions 0 assignees View on GitHub

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enhancement proposal
Dominant language
Rust
Stars
51
Forks
8
PR merge metrics
No merged PRs in 30d

Description

Recognizing factorials directly in a image could be a fun addition and would give the bot a much wider coverage. As far as I have seen most OCR crates are fairly easy to integrate.

Downsides:

  • slower response times/latency (since currently we're working on the comments sequentially)
  • higher resource use with OCR
  • false positives/negatives
    • might make the bot look dumb

Crates

I don't have a strong preference right now, but from what I have seen floneum looks promising as it uses models which could work best with structured inputs.
Traditional OCR like tesseract would probably be a lot less resource hungry, but less accurate and would probably need more configuration. Tesseract biggest upside by far is that it should be more resource-efficient than "model-based" OCRs

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

No file, test, or entry point is named. Start by reviewing how the bot currently processes comments sequentially, then compare floneum with Tesseract for image recognition, latency, resource use, and false positives. Done would require a decided OCR approach and an agreed integration scope.

Written by the indexing model from the issue text.

Assessment

Tech stack
rust
Domain
computer-vision
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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